Rguroo

One-Way

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'PlantGrowthX' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the ANOVA option.

3. Select a Dataset and Response variable.

4. Under the one-way tab select a Factor variable and set a Significance Level.

   

5. Click the preview icon to see the result.

   

Two-Way

The Randomized Block Design

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'PlantGrowthX' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the ANOVA option.

3. Select a Dataset and Response variable.

4. Click the Two-Way tab and select Factor A and Factor B variables and set a Significance Level.

   

5. Click the preview icon to see the result.

   

The Factorial Design

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'PlantGrowthX' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the ANOVA option.

3. Select a Dataset and Response variable.

4. Click the Two-Way tab and select Factor A and Factor B. Select the Interaction (A X B) checkbox and set a Significance Level.

5. Select the checkbox next to the Diagnostics button. Click on the Diagnostics button. In the ANOVA Diagnostics dialog that opens select Response Interaction Plot and other desired diagnostics.

   

6. Click the preview icon to see the result.

   

Binomial Probability (cdf)

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Use the Probability dropdown menu and choose the Probability Calculator then select the Discrete option.

2. Select the option Values ⇒ Probability.

3. Select Binomial as the Distribution, and enter the Number of Trials and Probability of Success.

4. Select the option Below from the dropdown menu, then type the Number of Successes in the text field.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon to see the result.

   

Binomial Probability (pdf)

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Use the Probability dropdown menu and choose the Probability Calculator then select the Discrete option.

2. Select the option Values ⇒ Probability.

3. Select Binomial as the Distribution, and enter the Number of Trials and Probability of Success.

4. Select the option Equal from the dropdown menu, then type the Number of Successes in the text field.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon .

   

Binomial Probability Distribution

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Use the Probability dropdown menu and choose the Probability Calculator then select the Discrete option.

2. Select the option Values ⇒ Probability.

3. Select Binomial as the Distribution and enter the Number of Trials and Probability of Success.

4. Select the option Equal from the dropdown menu. Then type the Number of Successes in the text field to the right.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon .

   

Critical Value

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Use the Probability dropdown menu and choose the Probability Calculator then select the Continuous option.

2. Select the option Probability ⇒ Values.

3. Select Chi-Square as the Distribution, and enter the Degrees of Freedom (DF). Leave other parameters at default values.

4. Select the option Upper Tail from the dropdown menu, then type the desired probability in the text field.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon .

   

Right Tailed Probability (cdf)

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Use the Probability dropdown menu and choose the Probability Calculator then select the Continuous option.

2. Select the option Values ⇒ Probability.

3. Select Chi-Square as the Distribution, and enter the Degrees of Freedom (DF). Leave other parameters at default values.

4. Select the option Above from the dropdown menu, then type the desired value in the text field.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon .

   

Test for Association

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'Cowles' dataset found in the 'car' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Contingency Table option.

3. Select a Dataset, Factor 1 and Factor 2 variables. If data are in tabular form, where frequencies are given as a separate variable, select the Frequency variable.

4. Under the Test of Independence section, check the Chi-Square checkbox (with graph, if desired). Set the Significance Level.

   

5. Click the preview icon to see the result.

   

Test for Goodness of Fit

Test for Goodness of Fit with Dataset

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'starburst' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Goodness of Fit option.

3. Select a Dataset and a Factor variable. If your data are in tabular form, where frequencies are given as a separate variable, select the Frequency variable.

4. (optional) Under the Null Probability column, type in probabilities for each level. Probabilities can be typed in as fractions or decimals. If the Null Probability column is left blank, equal probability for all levels will be assumed.

5. Under the Test of Hypothesis section, check the Chi-Square checkbox (with graph, if desired), then set the Significance Level.

   

6. Click the preview icon .

   

Test for Goodness of Fit without Dataset

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Goodness of Fit option.

2. To enter data for each level, click the + sign at the bottom right corner of the middle table. Double click each cell to enter data. An easy way to move between cells is to use the tab key on your keyboard.

   1. Enter a level name and a corresponding label name under the columns Level and Label, respectively.

   2. Enter the observed count for the level under Obs. Count column.

   3. Enter the null probability for the level under Null Probability. If the Null Probability column is left blank, equal probability for all levels will be assumed.

3. Under the Test of Hypothesis section, check the Chi-Square checkbox (with graph, if desired), then set the Significance Level.

   

4. Click the preview icon .

   

Left Tailed Probability (cdf)

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Use the Probability dropdown menu and choose the Probability Calculator, then select the Continuous option.

2. Select the option Values ⇒ Probability.

3. Select Chi-Square as the Distribution and enter the Degrees of Freedom (DF). Leave the other parameters at default values.

4. Select the option Below from the dropdown menu, then type the desired value in the text field.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon .

   

Confidence Intervals for Standard Deviation and Variance

Using Raw Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose Variance Inference and the One Population option.

3. Select a Dataset and a Variable. The values for Sample S.d. and Sample Size will be calculated and fill in automatically.

4. For Population Parameter select σ or σ², for confidence interval for standard deviation or variance, respectively.

5. In the Confidence Interval section, input the desired Confidence Level and select the Chi-Square checkbox.

6. Click the preview icon to see the result.

   

Using Summary Statistics

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose Variance Inference and the One Population option.

2. Enter the values for Sample S.d. and Sample Size.

3. For Population Parameter select σ or σ², for confidence interval for standard deviation or variance, respectively.

4. Write a Variable Label for the parameter in the text box for σ = S. d. of or σ² = Variance of.

5. In the Confidence Interval section, input the desired Confidence Level and select the Chi-Square checkbox.

6. Click the preview icon to see the result.

   

Two Sample Proportions z-Interval

Using Raw Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Proportion Inference option, then select the Two Populations option. This opens the Basics dialog.

3. Select a Dataset.

4. In the Response/Success section, select a Response variable and the level indicating Success. Optionally, you can type in a label for Failure.

5. In the Population section, select a variable for Population that indicates the population (explanatory variable). If your data is in tabular form, you can select the numerical variable that includes the Frequency for each level.

6. In the Data Summary tab, for each of Population 1 and Population 2 choose the corresponding Level. Clicking on the refresh button will load the Sample Size, # of Successes, and Proportion of Success for each population.

   

7. Select the Test of Hypothesis tab and specify the Alternative Hypothesis p1 – p2, Significance Level, and select the Large Sample z checkbox.

   

8. Click the preview icon to see the result.

   

Using Summary Statistics

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Proportion Inference option, then select the Two Populations option. This opens the Basics dialog.

2. In the Response/Success section, Type in a label for the Response variable and a label for Success. Optionally, you can type in a label for Failure.

3. In the Population section, type in a label for the population variable.

4. In the Data Summary tab, for each of Population 1 and Population 2 type in the following: Label , Sample size, and # of Successes.

5. Choose the corresponding Level. Clicking on the refresh button will load the Sample Size, # of Successes, and Proportion of Success for each population.

   

6. Select the Confidence Interval tab and specify the Confidence Level and select the Large Sample z checkbox.

   

7. Click the preview icon to see the result.

   

Two Sample t-Interval (Independent Samples)

Using Raw Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Mean Inference option, then select the One & Two Population option.

3. Select a Dataset, Variable 1, and Variable 2. The summary statistics in the Summary tab will be automatically populated. (Note: If the populations are identified by a categorical variable, you would use the option of Variable and By Factor.)

4. Open the Population 1-2 tab, then the Confidence Interval tab. Set the Confidence Level and select the t-statistic checkbox.

   

5. Click the preview icon to see the result.

   

Using Summary Statistics

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Mean Inference option, then select the One & Two Population option.

2. In the Summary tab

   1. Under the Population 1 Section, type Label, Sample Mean, Sample S.d. (or Pop. S.d.), and Sample Size for Population 1.

   2. Under the Population 2 Section, type Label, Sample Mean, Sample S.d. (or Pop. S.d.), and Sample Size for Population 2.

      

3. Open the Population 1-2 tab, then the Confidence Interval tab. Set the Confidence Level and select the t-statistic checkbox.

   

4. Click the preview icon to see the result.

   

Two Sample t-Interval (Dependent Samples, Paired Difference)

Using Raw Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'LA CountyOzoneRandom' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Mean Inference option, then select the One & Two Population option.

3. Select a Dataset, Variable 1, and Variable 2. The summary statistics in the Summary tab will be automatically populated. Note: If the populations are identified by a categorical variable, you would use the option of Variable and By Factor. Also, the number of cases for both populations must be the same for paired data.

4. Select the Paired Data checkbox. The summary data for paired differences will show in the Summary tab.

5. Open the Population 1-2 tab, then the Confidence Interval tab. Set the Confidence Level and select the t-statistic checkbox.



6. Click the preview icon to see the result.

   

Using Summary Statistics

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Mean Inference option then the One & Two Population option.

2. Under the Summary tab select the Paired Data checkbox.

3. In the Paired Difference section of the Summary tab and enter your data:

   1. Type in a Label.

   2. In the Sample Mean textbox, type the mean of the paired differences

   3. In the Sample S.d. textbox, type the sample standard deviation of the paired differences

   4. In the Sample Size textbox, type the sample size.

      

4. Open the Population 1-2 tab, then the Confidence Interval tab. Set the Confidence Level and select the t-statistic checkbox.

   

5. Click the preview icon to see the result.

   

Two Sample z-Interval

Using Raw Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'LA CountyOzoneRandom' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Mean Inference option, then select the One & Two Population option.

3. Select a Dataset, Variable 1, and Variable 2. The summary statistics in the Summary tab will be automatically populated. (Note: If the populations are identified by a categorical variable, you would use the option of Variable and By Factor.)

4. Open the Population 1-2 tab, then open the Confidence Interval tab. Set the Confidence Level and select the z-statistic checkbox.

   

5. Click the preview icon to see the result.

   

Using Summary Statistics

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Mean Inference option, then select the One & Two Population option.

2. In the Summary tab

   1. Under the Population 1 Section, type Label, Sample Mean, Pop. S.d., and Sample Size for Population 1.

   2. Under the Population 2 Section, type Label, Sample Mean, Pop. S.d., and Sample Size for Population 2.

      

3. Open the Population 1-2 tab, then the Confidence Interval tab. Set the Confidence Level and select the z-statistic checkbox.

   

4. Click the preview icon to see the result.

   

Proportion

Using Raw Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'Cowles' dataset found in the 'car' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Proportion Inference then the One Population option.

3. Select a Dataset, Factor variable, and Success level. The summary statistics will be automatically populated.

4. Under the Confidence Interval section, set the Confidence Level and select the checkboxes for Binomial (Exact) and Large Sample z.

   

5. Click the preview icon to see the result.

   

Using Summary Statistics

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Proportion Inference then the One Population option.

2. Fill in labels for Factor, Success, and optionally Failure.

3. Fill in values for Sample Size and # of Success.

4. Under the Confidence Interval section, set the Confidence Level and select the checkboxes for Binomial (Exact) and Large Sample z.

   

5. Click the preview icon to see the result.

   

t-Interval

Using Raw Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'LA CountyOzoneRandom' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose Mean Inference and the One Population option.

3. Select a Dataset and a Variable.

4. Under the Confidence Interval tab select the t-statistic checkbox, and your desired Confidence Level.



5. Click the preview icon to see the result.

   

Using Summary Statistics

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose Mean Inference and the One Population option.

2. Fill out the values for Sample Mean, Sample S.d., and Sample Size.

3. Write a label for the parameter in the text box μ = Mean of.

4. Under the Confidence Interval tab select the t-statistic checkbox, and your desired Confidence Level.

   

5. Click the preview icon to see the result.

   

z-Interval

Using Raw Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'LA CountyOzoneRandom' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Mean Inference and the One Population option.

3. Select a Dataset and a Variable. If the population standard deviation is known, type it in the Pop. S.d. textbox.

4. Under the Confidence Interval tab select the z-statistic checkbox, and your desired Confidence Level.

   

5. Click the preview icon to see the result.

   

Using Summary Statistics

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose Mean Inference and the One Population option.

2. Fill out the values for Sample Mean, Pop. S.d., and Sample Size.

3. Write a label for the parameter in the text box μ = Mean of.

4. Under the Confidence Interval tab select the z-statistic checkbox, and your desired Confidence Level.

   

5. Click the preview icon to see the result.

   

One Variable

Method 1: Five number summary, Trimmed Mean, Weighted Mean, Mode, Percentiles

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Numerical Summaries option. The Numerical Summaries dialog opens.

3. Select a Dataset. Move a variable to Selected column. If weighted mean is desired, choose the weight variable in the Frequency dropdown.

4. Click the Univariate button and select the desired summary statistics. For Trimmed Mean, select Truncated Mean, and enter percentage (or count). For percentiles select the Quantiles checkbox, and list your desired percentages, separated by commas, in the Percentage textbox.

   

5. Click the preview icon to see the result.

   

Method 2: One Variable (Mean, Median, Q1, Q3, Min, Max)

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Data toolbox on the left-hand side of the Rguroo window. Use the Functions dropdown menu and choose the Summary Statistic option.

3. Select a Dataset and Numerical variable. Using the checkboxes, select the statistics desired.

   

4. Click the preview icon to see the result and select “All Observations” in the output.

   

Two Variable

1. See Creating a Data Frame to input your data. Here we use a dataset with two variables.

   

2. Open the Data toolbox on the left-hand side of the Rguroo window. Use the Functions dropdown menu and choose the Summary Statistic option.

3. Select a Dataset, Numerical variable, and Frequency variable. Using the checkboxes, select the statistics desired. The Frequency variable will be used to create weights.

   

4. Click the preview icon . Choose "All Observations".

   

Computing Expectation and Variance for a Discrete Probability Distribution

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'Profit_Probability' dataset found in the 'Rguroo Users Guide' repository.

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Numerical Summaries.

3. Select the Dataset that contains your probability distribution. One column would be values and another column would consist of probabilities.

4. Move the variable consisting of values to the Selected column by clicking on the variable and then dragging and dropping.

5. From the Frequency dropdown select the variable that contains the probabilities.

6. Click on the Univariate button and select Mean, Population Variance, and Population Std. Dev.

   

7. Click the preview icon to see the result.

   

F-Probability (cdf)

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Use the Probability dropdown menu and choose the Probability Calculator then select the Continuous option.

2. Select the option Values => Probability.

3. Select F as the Distribution, and enter the Num. DF and Denom. DF.

4. Select the option Below from the dropdown menu, then type the desired value in the text field.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon . Choose "All Observations".

   

Bar Charts

Displaying Qualitative Data Graphically

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Plots toolbox on the left-hand side of the Rguroo window. Use the Create Plot dropdown menu and choose the Barplot option. The Barplot dialog opens.

3. Select a Dataset. To create a barplot with categories across the x-axis, click the Categorical tab (this is the default tab).

4. Select a Factor 1 variable, adjust the other options appropriately, and add a title. If your data is in the form of a frequency table in the Frequency dropdown select the name of the column that consists of frequencies.

   

5. Click the preview icon to see the result.

   

Side-by-Side Bar Charts

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Plots toolbox on the left-hand side of the Rguroo window. Use the Create Plot dropdown menu and choose the Barplot option. The Barplot dialog opens.

3. Select a Dataset. To create a barplot with categories across the x-axis, click the Categorical tab (this is the default tab).

4. Select a Factor 1 and Factor 2 variables and select the Side by Side option. Adjust the other options appropriately. If your data is in the form of a frequency table in the Frequency dropdown select the name of the column that consists of frequencies.

   

5. Click the preview icon to see the result.

   

Stacked Bar Charts

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Plots toolbox on the left-hand side of the Rguroo window. Use the Create Plot dropdown menu and choose the Barplot option. The Barplot dialog opens.

3. Select a Dataset. To create a barplot with categories across the x-axis, click the Categorical tab (this is the default tab).

4. Select a Factor 1 and Factor 2 variables and select the Stacked option. Adjust the other options appropriately. If your data is in the form of a frequency table in the Frequency dropdown select the name of the column that consists of frequencies.

   

5. Click the preview icon to see the result.

   

Box Plot

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Plots toolbox on the left-hand side of the Rguroo window. Use the Create Plot dropdown menu and choose the Boxplot option.

3. Select a Dataset, Numerical variable, and Factor variable. Adjust the other options appropriately and add a title.

4. Click the preview icon .

   

Dot Plots

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'Titanic' dataset found in the 'R datasets' repository.

   

2. Open the Plots toolbox on the left-hand side of the Rguroo window. Use the Create Plot dropdown menu and choose the Dotplot option.

3. Select a Dataset and Numerical variable. Adjust the other options appropriately and add a title.

   

4. Click the preview icon .

   

Histograms

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Plots toolbox on the left-hand side of the Rguroo window. Use the Create Plot dropdown menu and choose the Histogram option.

3. Select a Dataset and Variable. Adjust the other options appropriately and add a title.

   

4. Click the preview icon .

   

Line Graph

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'AirPassengers' dataset found in the 'R datasets' repository.

   

2. Open the Plots toolbox on the left-hand side of the Rguroo window. Use the Create Plot dropdown menu and choose the Scatterplot option.

3. Select a Dataset, Predictor Variable, and Response Variable. Adjust the other options appropriately and add a title.

4. Check the Line checkbox found in the Superimpose section.

   

5. Click the preview icon .

   

Multivariate/Multidimensional

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Plots toolbox on the left-hand side of the Rguroo window. Use the Create Plot dropdown menu and choose the Scatterplot option.

3. Select a Dataset, Predictor Variable, and Response Variable.

4. Select a Factor Variable which will be used to color the points. Adjust the other options appropriately and add a title.

   

5. Click the preview icon .

   

Time Series Plot

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'AirPassengers' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Time Series option.

3. Select a dataset from the Dataset dropdown menu.

4. Under Numerical Variables, drag and drop a variable into the Selected column.

5. In the bottom left under Time Series Plot, check the Lines checkbox.

   

6. Click the preview icon .

   

Normal Probability Plot

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Mean Inference and the One Population option.

3. Select a Dataset and select a Variable.

4. Select the Normal Probability Plot checkbox.

   

5. Click the preview icon to see the result.

   

Pareto Chart

1. Create a Barplot.

2. In the Barplot dialog Bar Order dropdown, select Decreasing Value.

   

3. Click the preview icon to see the results.

   

Pie Chart

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Plots toolbox on the left-hand side of the Rguroo window. Use the Create Plot dropdown menu and choose the Piechart option.

3. Select a Dataset and Factor variable. Adjust the other options appropriately and add a title.

   

4. Click the preview icon .

   

Scatterplot

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cereal' dataset found in the 'R datasets' repository.

   

2. Open the Plots toolbox on the left-hand side of the Rguroo window. Use the Create Plot dropdown menu and choose the Scatterplot option.

3. Select a Dataset and check Show Correlation and LS Equation checkbox.

4. In the Variable section, select Predictor (x) and Response (y) variables.

   

5. (Optional) If you would like to see the least squares line and its equation in the Superimpose section, select the LS line checkbox.

6. Click the preview icon .

   

Stem and Leaf Plots

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Plots toolbox on the left-hand side of the Rguroo window. Use the Create Plot dropdown menu and choose the Stem and Leaf option.

3. Select a Dataset and Variable.

4. Select Scale and adjust the other options appropriately.

   

5. Click the preview icon to see the result.

   

Standard Deviation and Variance

Using Raw Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose Variance Inference and the One Population option.

3. Select a Dataset and a Variable.

4. For Population Parameter select σ or σ², for testing a hypothesis about a standard deviation or variance, respectively.

5. In the Test of Hypothesis section

   1. Input your alternative hypothesis next to Alternative σ text box.

   2. Select the Chi-Square checkbox.

   3. Enter the Significance Level.

   

6. Click the preview icon to see the result.

   

Using Summary Statistics

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose Variance Inference and the One Population option.

2. Enter the values for Sample S.d. and Sample Size.

3. For Population Parameter select σ or σ², for hypothesis testing about a standard deviation or variance, respectively.

4. Write a Variable Label for the parameter in the text box for σ = S. d. of or σ² = Variance of.

5. In the Test of Hypothesis section

   1. Input your alternative hypothesis next to Alternative σ text box.

   2. Select the Chi-Square checkbox.

   3. Enter the Significance Level.

   

6. Click the preview icon to see the result.

   

One Proportion z-Test

Using Raw Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'Cowles' dataset found in the 'car' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Proportion Inference then the One Population option.

3. Select a Dataset and Factor variable and Success level. The summary statistics will be automatically populated.

4. Under the Test of Hypothesis section, set the Alternative Hyp p: (the alternative hypothesis), select the checkbox Large Sample z (p=p0), and set the Significance Level.

   

5. Click the preview icon to see the result.

   

Using Summary Statistics

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Proportion Inference then the One Population option.

2. Fill in labels for Factor, Success, and optionally Failure.

3. Input numerical values for Sample Size, and # of Successes.

4. Under the Test of Hypothesis section, set the Alternative Hyp p: (the alternative hypothesis), select the checkbox Large Sample z (p=p0), and set the Significance Level.

   

5. Click the preview icon to see the result.

   

t-Test

Using Raw Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'LA cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose Mean Inference and the One Population option.

3. Select a Dataset and a Variable. The sample statistics will automatically populate.

4. Click the Test of Hypothesis tab and

   1. Type in Significance Level.

   2. Select one of <,>, != and a value for the Alternative hypothesis.

   3. Select the t-statistic checkbox

      

5. Click the preview icon to see the result.

   

Using summary statistics:

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose Mean Inference and the One Population option.

2. Fill out the values for Sample Mean, Sample S.d., and Sample Size.

3. Write a label for the parameter in the text box μ = Mean of.

4. Click the Test of Hypothesis tab and

   1. Type in Significance Level.

   2. Select one of <,>, != and a value for the Alternative hypothesis μ.

   3. Select the t-statistic checkbox.

      

5. Click the preview icon to see the result.

   

Two Sample Proportion z-Test

Using Raw Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Proportion Inference option, then select the Two Populations option. This opens the Basics dialog.

3. Select a Dataset.

4. In the Response/Success section, select a Response variable and the level indicating Success. Optionally, you can type in a label for Failure.

5. In the Population section, select a variable for Population that indicates the population (explanatory variable). If your data is in tabular form, you can select the numerical variable that includes the Frequency for each level.

6. In the Data Summary tab, for each of Population 1 and Population 2 choose the corresponding Level. Clicking on the refresh button will load the Sample Size, # of Successes, and Proportion of Success for each population.

   

7. Select the Confidence Interval tab and specify the Confidence Level and select the Large Sample z checkbox.

   

8. Click the preview icon to see the result.

   

Using Summary Statistics

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Proportion Inference option, then select the Two Populations option. This opens the Basics dialog.

2. In the Response/Success section, Type in a label for the Response variable and a label for Success. Optionally, you can type in a label for Failure.

3. In the Population section, type in a label for the population variable.

4. In the Data Summary tab, for each of Population 1 and Population 2 type in the following: Label , Sample size, and # of Successes.

5. Choose the corresponding Level. Clicking on the refresh button will load the Sample Size, # of Successes, and Proportion of Success for each population.

   

6. Select the Confidence Interval tab and specify the Confidence Level and select the Large Sample z checkbox.

   

7. Click the preview icon to see the result.

   

Two Sample t-Test (Dependent Samples, Paired Difference)

Using Raw Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'LA CountyOzoneRandom' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Mean Inference option then the One & Two Population option.

3. Select a Dataset, Variable 1, and Variable 2. The summary statistics in the Summary tab will be automatically populated. Note: If the populations are identified by a categorical variable, you would use the option of Variable and By Factor. Also, the number of cases for both populations must be the same for paired data.

4. Select the Paired Data checkbox. The summary data for paired differences will show in the Summary tab.

5. Select the Population 1-2 tab, select the Test of Hypothesis tab, and

   1. type in the Significance Level,

   2. State your alternative hypothesis next to Alternative Hyp. μ_d,

   3. under the Method section select the t-statistic checkbox.

      

6. Click the preview icon .

   

Using Summary Statistics

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Mean Inference option then the One & Two Population option.

2. Under the Summary tab select the Paired Data checkbox.

3. In the Paired Difference section of the Summary tab enter your data:

   1. Type in a Label.

   2. In the Sample Mean textbox, type the mean of the paired differences

   3. In the Sample S.d. textbox, type the sample standard deviation of the paired differences

   4. In the Sample Size textbox, type the sample size.

      

4. Select the Population 1-2 tab, select the Test of Hypothesis tab, and

   1. type in the Significance Level,

   2. State your alternative hypothesis next to Alternative Hyp. μ_d,

   3. under the Method section select the t-statistic checkbox.

      

5. Click the preview icon to see the result.

   

Two Sample t-Test (Independent Samples)

Using Raw Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Mean Inference option then the One & Two Population option.

3. Select a Dataset, Variable 1, and Variable 2. The summary statistics in the Summary tab will be automatically populated. (Note: If the populations are identified by a categorical variable, you would use the option of Variable and By Factor. Then, in the Summary tab, choose a Level for the Factor. In this example the TYPE of car is Domestic or Import).

4. Open the Population 1-2 tab, then under the Test of Hypothesis tab

   1. Type in the Significance Level.

   2. State the Alternative Hypothesis.

   3. Select t-statistic.

   4. Select one of Unequal Variance or Equal Variance.

      

5. Click the preview icon to see the result.

   

Using Summary Statistics

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Mean Inference option then the One & Two Population option.

2. In the Summary tab

   1. Under the Population 1 Section, type Label, Sample Mean, Sample S.d. (or Population S.d.), and Sample Size for population 1.

   2. Under the Population 2 Section, type Label, Sample Mean, Sample S.d. (or Population S.d.), and Sample Size for population 2.

      

3. Open the Population 1-2 tab, then under the Test of Hypothesis tab

   1. Type in the Significance Level.

   2. State the Alternative Hypothesis.

   3. Select t-statistic.

   4. Select one of Unequal Variance or Equal Variance.

      

4. Click the preview icon to see the result.

   

Two Sample z-Test

Using Raw Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'LA CountyOzoneRandom' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Mean Inference option then the One & Two Population option.

3. Select a Dataset, Variable 1, and Variable 2. The summary statistics in the Summary tab will be automatically populated. (Note: If the populations are identified by a categorical variable, you would use the option of Variable and By Factor.)

4. Open the Population 1-2 tab, then under the Test of Hypothesis tab

   1. Type in the Significance Level.

   2. State the Alternative Hypothesis.

   3. Select z-statistic.

      

5. Click the preview icon to see the result.

   

Using Summary Statistics

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Mean Inference option then the One & Two Population option.

2. In the Summary tab

   1. Under the Population 1 Section, type Label, Sample Mean, Sample S.d. (or Population S.d.), and Sample Size for population 1.

   2. Under the Population 2 Section, type Label, Sample Mean, Sample S.d. (or Population S.d.), and Sample Size for population 2.

      

3. Open the Population 1-2 tab, then under the Test of Hypothesis tab

   1. Type in the Significance Level.

   2. State the Alternative Hypothesis.

   3. Select z-statistic.

      

4. Click the preview icon to see the result.

   

z-Test

Using raw data:

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose Mean Inference and the One Population option.

3. Select a Dataset and a Variable. The sample statistics will automatically populate.

4. Click the Test of Hypothesis tab and

   1. Type in Significance Level.

   2. Select one of <,>, != and a value for the Alternative hypothesis.

   3. Select the z-statistic checkbox

      

5. Click the preview icon to see the result.

   

Using summary statistics:

1. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose Mean Inference and the One Population option.

2. Fill out the values for Sample Mean, Sample S.d., and Sample Size.

3. Write a label for the parameter in the text box μ = Mean of.

4. Click the Test of Hypothesis tab and

   1. Type in Significance Level.

   2. Select one of <,>, != and a value for the Alternative hypothesis μ.

   3. Select the z-statistic checkbox.

      

5. Click the preview icon to see the result.

   

Testing the Population Median with the Sign Test

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'LA CountyOzoneRandom' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose Median Inference and the One Population option.

Select a Dataset and a Variable. Type in a label for the parameter in the textbox " M = Median of."

3. In the Test of Hypothesis tab

   1. Type in Significance Level.

   2. Select one of <,>, != and a value for the Alternative hypothesis M.

   3. Select the Sign Test checkbox, and if you want to get a graph, select Graph.

4. Click the preview icon to see the result.

   

Hypothesis Testing – Difference of Medians – Independent Samples

1. Use a dataset in your Rguroo account or recreate the example below by Accessing the Rguroo Data Repository and using the 'LA CountyOzoneRandom' dataset from the 'Rguroo Users Guide' dataset repository in your account.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose Median Inference and the Two Population option.

3. Select a Dataset. If your data are in two separate columns, select Variable 1 and Variable 2. If the population is determined by a factor variable in your dataset, select Variable and By Factor and select Pop 1 Level and Pop 2 Level.

4. In the Test of Hypothesis tab

   1. Type in Significance Level.

   2. Select one of <,>, != and a value for the Alternative hypothesis M1−M2.

5. In the Method section, select the Mann-Whitney checkbox. Note: various options for the Mann-Whitney test are available in the Details section (click the Details button on top to see the options.)

6. Click the preview icon to see the result.

   

Hypothesis Testing – Wilcoxon Signed-Rank or Sign Test – Paired Data

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'MooreBP' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose Median Inference and the Two Population option.

3. Select a Dataset. If your data are in two separate columns, select Variable 1 and Variable 2. If the population is determined by a factor variable in your dataset, Select Variable and Factor and select Pop1 Level or Pop 2 Level.

4. Select the Paired Data checkbox.

5. In the Test of Hypothesis tab

   1. Type in Significance Level.

   2. Select one of <,>, != and a value for the Alternative hypothesis M_d.

6. In the Method section, select the Wilcoxon Signed-Rank and/or Sign Test checkboxes. Note: Various options for these tests are available in the Details section (click the Details button on top to see the options).

7. Click the preview icon to see the result.

   

Inverse Normal

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Select the Probability dropdown menu and choose the Probability Calculator then the Continuous option.

2. Select the option Probability ⇒ Values.

3. Select Normal as the Distribution and enter the Mean and Standard Deviation.

4. Select the option Lower Tail from the dropdown menu, then type the desired area in the text field.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon to see the result.

   

Normal Probability (cdf)

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Select the Probability dropdown menu and choose the Probability Calculator then the Continuous option.

2. Select the option Values ⇒ Probability.

3. Select Normal as the Distribution, and enter the Mean and Standard Deviation.

4. Select the option Below from the dropdown menu, then type the desired value in the text field.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon to see the result.

   

Inverse Normal

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Select the Probability dropdown menu and choose the Probability Calculator then select the Continuous option.

2. Select the option Probability ⇒ Values.

3. Select Normal as the Distribution, and enter the Mean and Standard Deviation.

4. Select the option Lower Tail from the dropdown menu, then type the desired area in the text field.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon .

   

Normal Probability Graph

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Select the Probability dropdown menu and choose the Probability Calculator then select the Continuous option.

2. Select the option Values ⇒ Probability.

3. Select Normal as the Distribution and enter the Mean and Standard Deviation.

4. Select the option Between from the dropdown menu, then type the desired lower tail and upper tail values in the text fields.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon .

   

Poisson Probability (cdf)

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Use the Probability dropdown menu and choose the Probability Calculator, then select the Discrete option.

2. Select the option Values ⇒ Probability.

3. Select Poisson as the Distribution and enter a Mean (lambda) value.

4. Select the option Below from the dropdown menu, then type the Number of Successes in the text field.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon to see the result.

   

Poisson Probability (pdf)

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Use the Probability dropdown menu and choose the Probability Calculator then select the Discrete option.

2. Select the option Values ⇒ Probability.

3. Select Poisson as the Distribution, and enter a Mean (lambda) value.

4. Select the option Equal from the dropdown menu, then type the Number of Successes in the text field.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon .

   

Poisson Probability Distribution

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Use the Probability dropdown menu and choose the Probability Calculator then select the Discrete option.

2. Select the option Values ⇒ Probability.

3. Select Poisson as the Distribution and enter a mean value (lambda).

4. Select the option Equal from the dropdown menu. Then type the Number of Successes in the text field to the right.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon .

   

Hypergeometric Distribution

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Use the Probability dropdown menu and choose the Probability Calculator then the Discrete option.

2. Select the option Values ⇒ Probability.

3. Select Hypergeometric as the Distribution, and enter number of Successes, number of Failures and number of Draws.

4. Select one of the options Equal, Below, Above, Between from the dropdown menu, then type the Number of Successes in the text field.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name (in the left window), if desired.

   

6. Click the preview icon .

   

Hypothesis Testing for the Slope Coefficient

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cereal' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu, choose the Linear Regression, and select the option Simple & Multiple Regression.

3. Select a Dataset.

4. In the Model Specification section, select the Response variable from the dropdown menu. In the Formula textbox, specify the explanatory variable; this can be done by either typing the name of the variable, double-clicking the name of the variable in the Variable column, or by Drag and drop.

   

5. Click the preview icon to see the result. You will see the component of test of hypothesis for parameters under the section Regression Coefficients Estimates and t-Test.

   

Linear Regression Fitted Line Plot with Confidence Interval

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cereal' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu, choose the Linear Regression, and select the option Simple & Multiple Regression.

3. Select a Dataset.

4. In the Model Specification section, select the Response variable from the dropdown menu. In the Formula textbox, specify the model; Either typing the name of the variables or move variables from the Variable list by double-clicking or by Drag and drop. Separate explanatory variables by the plus sign +.

   

5. To obtain a confidence interval for the mean of y given x, open the Details dialog by clicking on the yellow Details button on the top.

   1. Open the section labeled Fitted Values, Predictions, and Interval Estimates.

   2. Select the option Internal Data.

   3. Type in Confidence Level. The default is 95%.

   4. Move the Confidence Interval – Mean Prediction to the Selected column.

      

6. Click the preview icon to see the result.

   

Linear Regression Fitted Line with Prediction Interval

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Linear Regression option, then Simple & Multiple Regression.

3. Select a Dataset, Response, and set up the Formula using the variables and , , and buttons. Here we regress MPG by HP (Horsepower).

   

4. To add additional output to the report, open the Details menu at the top of the Rguroo window. Select the Model Estimates and Diagnostics Graphs tab. Drag-and-drop or use the arrows to move the desired tables and graphs to the right-hand box labeled Selected, these will be included in the report. To include a prediction interval band, select Prediction Interval Band.

   

5. Click the preview icon .

   

Multiple Regression

1. See Creating a Data Frame to input your data, or recreate the example below by Accessing the Rguroo Data Repository and using the 'cereal' dataset found in the 'Rguroo Users Guide' repository.

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Linear Regression option, then Simple & Multiple Regression.

3. Select a Dataset

4. In the Model Specification section, select the Response variable from the dropdown menu. In the Formula textbox, specify the model; Either typing the name of the variables or move variables from the Variable list by double-clicking or by Drag and drop. Separate explanatory variables by the plus sign +.

   

5. Click the preview icon to see the result.

   

Multiple Regression Models with Qualitative Independent Variables

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cereal' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu, choose the Linear Regression, and select the option Simple & Multiple Regression.

3. Select a Dataset.

4. In the Model Specification section, select the Response variable from the dropdown menu. In the Formula textbox, specify the model; Either typing the name of the variables or move variables from the Variable list by double-clicking or by Drag and drop. The explanatory variables can be either quantitative or qualitative. Separate explanatory variables by the plus sign +.

   

5. Click the preview icon to see the result.

   

Regression Prediction Intervals

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cereal' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Linear Regression option, then Simple & Multiple Regression.

3. Select a Dataset/

4. In the Model Specification section, select the Response variable from the dropdown menu. In the Formula textbox, specify the model; Either typing the name of the variables or move variables from the Variable list by double-clicking or by Drag and drop. Separate explanatory variables by the plus sign +.

   

5. To obtain a confidence interval for the prediction of y given x, open the Details dialog by clicking on the yellow Details button on the top.

   1. Open the section labeled Fitted Values, Predictions, and Interval Estimates.

   2. Select the option Internal Data and/or External Data. Note: Data that are not used in fitting the model are called External data. You can add external data to your dataset by setting the corresponding value of the response for each case to NA.

   3. Type in Confidence Level. The default is 95%.

   4. Move the Prediction Interval to the Selected column.

   

6. Click the preview icon to see the result.

   

Simple Linear Regression

1. See Creating a Data Frame to input your data. Or, recreate the example below by Accessing the Rguroo Data Repository and using the 'cereal' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Linear Regression option, then Simple Regression.

3. Select a Dataset.

4. From the Predictor (x) and Response (y) dropdown menus select the predictor and response variables.

   

5. Click the preview icon to see the result.

   

Confidence Intervals for Slope and y-Intercept

1. See Creating a Data Frame to input your data. Or, recreate the example below by Accessing the Rguroo Data Repository and using the 'cereal' dataset found in the 'Rguroo Users Guide' repository.

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu, choose the Linear Regression, and select the option Simple & Multiple Regression.

3. Select a Dataset.

4. In the Model Specification section, select the Response variable from the dropdown menu. In the Formula textbox, specify the model; Either typing the name of the variables or move variables from the Variable list by double-clicking or by Drag and drop. Separate explanatory variables by the plus sign +.

   

5. To obtain a confidence interval for the parameters, open the Details dialog by clicking on the yellow Details button on the top.

   1. Open the first section labeled Model Estimates and Diagnostics Graphs.

   2. In the column labeled Table and Graphs select Parameter Confidence Interval by moving it to the Selected column. (Either use arrows or drag-and-drop).

      

6. Click the preview icon to see the result.

   Note: Confidence level can be set in the Details menu under the section Fitted Values, Predictions, and Interval Estimates. The default value is 95%.

   

Correlation Coefficient

See Multiple Regression.

Coefficient of Determination

See Multiple Regression.

Random Samples

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Use the Probability dropdown menu and choose Random Generator.

2. Select Uniform as the Distribution and enter Min (a), Max (b), and Sample Size.

3. Adjust the other options appropriately, including setting the Seed to allow for Replications, if desired.

   

4. Click the preview icon to see the result.

   

Inverse t

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Use the Probability dropdown menu and choose the Probability Calculator then select the Continuous option.

2. Select Student t as the Distribution, and enter the Degrees of Freedom.

3. Select the option Probability => Values.

4. Select the option Lower Tail from the dropdown menu, then type the desired Area in the text field.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon .

   

t-Probability (cdf)

1. Open the Probability-Simulation toolbox on the left-hand side of the Rguroo window. Use the Probability dropdown menu and choose the Probability Calculator then select the Continuous option.

2. Select the option Values ⇒ Probability.

3. Select Student t as the Distribution, and enter the Degrees of Freedom DF(v). Leave the other parameters at the default values.

4. Select the option Below from the dropdown menu, then type the desired value in the text field.

5. Adjust the other options appropriately, including selecting the Graph option and editing the Calculation Name, if desired.

   

6. Click the preview icon to see the result.

   

Additive and Multiplicative Seasonal Smoothing (The Holt-Winters Method)

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'AirPassengers' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Time Series option.

3. Select a dataset from the Dataset dropdown menu.

4. Under Numerical Variables, drag and drop a variable into the "Selected" column.

5. Under Time Specification, in the text field next to Freq., enter an integer value greater than or equal to 2 representing the number of observations per unit time (4 for quarterly data, 12 for monthly data, etc.). A Freq. value of 12 is used for this example.

6. Click on the Modeling menu .

7. In the Methods and Forecasting tab under Method, check both Holt-Winters' and Graph.

8. In the text fields to the right of Holt-Winters', optionally enter an Alpha, Beta, and/or Gamma value between 0 and 1. If a value is not specified, a default value will be chosen by Rguroo. Default values will be used for this example.

9. In the dropdown menu labeled Holt-Winters' Model Type select "Additive" or "Multiplicative" for the type of seasonal smoothing. Additive will be selected for this example.

   

10. Click the preview icon .

    

Adjusted Exponential Smoothing

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'USAccDeaths' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Time Series option.

3. Select a dataset from the Dataset dropdown menu.

4. Under Numerical Variables, drag and drop a variable into the Selected column.

5. Click on the Modeling menu .

6. In the Methods and Forecasting tab under Method, check both Double Exponential and Graph.

7. In the text fields to the right of Double Exponential, optionally enter an Alpha value and/or a Beta value between 0 and 1. If a value is not specified, a default value will be chosen by Rguroo. Values of 0.5 for Alpha and 0.3 for Beta are used for this example.

   

8. Click the preview icon .

   z

Forecasting Errors

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'USAccDeaths' dataset from the 'R datasets' repository. A portion of the data is shown below.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Time Series option.

3. Select a dataset from the Dataset dropdown menu.

4. Under Numerical Variables, drag and drop a variable into the “Selected” column.

5. Click on the Modeling menu .

6. In the Methods and Forecasting tab under Method, check the modeling method(s) you would like to use (Exponential, Double Exponential, and/or Holt-Winters). Alpha, Beta, and Gamma parameters may be optionally specified in the text fields. For this example, the Exponential and Double Exponential methods were selected with default values of Alpha and Beta being used.

7. Also under Method, check Fitted Values Table.

   

8. Click the preview icon . The fitted values along with the forecasting errors (residuals) for each method sleected are shown in the outputted table labeled “Fitted Values and Residuals for Model Fit”. The first five table rows after performing the Exponential and Double Exponential modeling methods on the USAccDeaths dataset are shown below.

   

Moving Average Plot

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'USAccDeaths' dataset found in the 'R datasets' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Time Series option.

3. Select a dataset from the Dataset dropdown menu.

4. Under Numerical Variables, drag and drop a variable into the Selected column.

5. In the bottom left under Time Series Plot, check both Lines and Moving Average.

6. In the text field to the right of Moving-Average labeled q-Param, enter an integer value equal to the desired number of periods to calculate the moving average over.

   

7. Click the preview icon .

   

Simple Exponential Smoothing

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'USAccDeaths' dataset found in the 'R datasets' repository. A portion of the data is shown below.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Time Series option.

3. Select a dataset from the Dataset dropdown menu.

4. Under Numerical Variables, drag and drop a variable into the Selected column.

5. Click on the Modeling menu .

6. In the Methods and Forecasting tab under Method, check Exponential and Graph.

7. In the text field to the right of Exponential, optionally enter an Alpha value between 0 and 1. If a value is not specified, a default value will be chosen by Rguroo. A value of 0.5 is used for Alpha in this example.

   

8. Click the preview icon .

   

Combination

1. Open the Applets toolbox on the left-hand side of the Rguroo window. Use the to expand the Calculators (Desmos) option and choose the Scientific Calculator.

2. Select the func option to open the functions menu of the calculator.

3. Select nCr and enter the two required parameters separated by a comma, as in $nCr\left(n,r\right)$, where $n=\text{the number of unique objects}$ and $r=\text{the number selected at a time}$.

   

Factorial

1. Open the Applets toolbox on the left-hand side of the Rguroo window. Use the to expand the Calculators (Desmos) option and choose the Scientific Calculator.

2. Select the func option to open the functions menu of the calculator.

3. Enter the desired number and select !.

   

Permutation

1. Open the Applets toolbox on the left-hand side of the Rguroo window. Use the to expand the Calculators (Desmos) option and choose the Scientific Calculator.

2. Select the func option to open the functions menu of the calculator.

3. Select nPr and enter the two required parameters separated by a comma, as in $nPr\left(n,r\right)$, where $n=\text{the number of unique objects}$ and $r=\text{the number of objects selected at a time}$.

   

Qualitative Frequency Distribution

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Tabulation > Categorical option. The Data Tabulation dialog opens.

3. Select a Dataset.

4. Click the green plus sign + at the bottom of the first column. Type a name for your table.

5. Select the qualitative variable that you want to tabulate from the Factor 1 dropdown.

6. Select one or more of Counts, Proportions, or Percentage.

7. Select the order preference: Default, Ascending, or Descending.

   

8. Click the preview icon to see the result.

   

Quantitative Frequency Distribution

Creating Frequency Tables and Relative Frequency Tables for Numerical Variables

1. See Creating a Data Frame to input your data or recreate the example below by Accessing the Rguroo Data Repository and using the 'cardata' dataset found in the 'Rguroo Users Guide' repository.

   

2. Open the Analytics toolbox on the left-hand side of the Rguroo window. Use the Analysis dropdown menu and choose the Tabulation > Numerical (Binning) option. The Binning dialog opens.

3. Select a Dataset, and a numerical Variable for which you like to create a frequency table.

4. Under the Bins section select a method for binning. For the example shown, the bins start at 90 and have a width of 10.

5. Under Report select one or more of Counts, Proportions %, or Cumulative %.

   Note: Under the Binning column you can add more tables by clicking on the green plus sign +.

   

6. Click the preview icon to see the result.