1  Data Type:
Specify the data type you have for your dependent variable (Y). The available options are:
 
2  Model Type:
Specify the type of regression model you want to build. The available options if the number of input variables is one are:
 
3  Model Reduction:
Specify if you want to use model reduction. When you build your model inputoutput and input(s), sometimes, not all inputs are statistically significant. Some of the input variables may have no impact on the model output. We can not include those terms in the final model in such cases. The model reduction setting lets you pick whether you want to include all or only significant terms. The following options are available:
 
4  Model Reduction Alpha: Specify the model reduction alpha value. This value will be used to reduce your regression model. The software starts with the full model and drops those nonsignificant terms until a fully significant model remains. The default value for model reduction alpha is 10%.  
5  Help Button: Click on this button to open the help file for this topic.  
6  Flowchart: Click on this button to open the flowchart for regression. The flowchart shows the logic of which analysis you need to perform depending on your specific situation.  
7  Cancel Button: Click on this button to cancel all changes to the settings and exit this dialog box.  
8  OK Button: Click on this button to save all changes and compute the outputs for this analysis. 
1  Num Factors: Specify the number of input variables. The software will fit a simple regression model if the number of input variables is 1. The software will fit a multiple regression model if the number of input variables exceeds 1. 
2  Search Data: The available data displays all the columns of data that are available for analysis. You can use the search bar to filter this list and speed up finding the right data for analysis. Enter a few characters in the search field, and the software will filter and display the filtered data in the Available Data box. 
3  Available Data: The available data box contains the list of data available for analysis. If your workbook has no data in tabular format, this box will display "No Data Found." The information displayed in this box includes the row number, whether the data is Numeric (N) or Text (T), and the name of the column variable. Note that the software displays data from all the tables in the current workbook. Even though data within the same table have unique column names, columns across different tables can have similar names. Hence, it is crucial that you not only specify the column name but also the table name. 
4  Add or View Data: Click on this button to add more data to your workbook for analysis or to view more details about the data listed in the available data box. When you click on this button, it opens the Data Editor dialog box, where you can import more data into your workbook. You can also switch from the list view to a table view to see the individual data values for each column. 
4a  View Selection: Click on this button to view the data specified for this analysis. The data can be viewed in a tabular format or a graphical summary. 
5  Select Button: Click on this button to select the data for analysis. Any data you choose for the analysis is moved to the right. To select a column, click on the columns in the Available Databox to highlight them and then click on the Select Button. A second method to choose the data is to doubleclick on the columns in the list of Available Data. Finally, you can drag and drop the columns you are interested in by holding down the select columns using your left mouse key and dragging and dropping them in one of the boxes on the right. 
6  Response Variable:
The list box header will be displayed in black if the right number of data columns is specified. If sufficient data has not been specified, then the list box header will be displayed in red color. Note that you can doubleclick on any of the columns in this box to remove them from the box. In this list box, specify the response or the dependent variable. Note that you can only specify one column. 
7  Continuous Factors:
The data you specify for this analysis depends on the options in the Setup tab. Specify the columns containing the inputs or independent variables under Factor Variables. Note that you can only specify up to N columns for the factor variables. N is the number of input variables specified in the Setup dialog box. Make sure that all the columns contain numeric values. 
8  Categorical Factors: If you have any discrete factors, they need to be specified in the list of categorical factors. Note that these factors can be in text format. You need to have at least one continuous variable. The categorical factors are internally converted to continuous factors using dummy variables. For example, a categorical factor named shift has three levels: 1st Shift, 2nd Shift, and 3rd Shift. The first shift is Shift.1, the second shift is Shift.2, and the third shift is Shift.3. You can use these variables in model terms if you want to build a regression model manually. 
9  Required Data: The code for the required data specifies what data can be specified for that box. An example code is N: 24. If the code starts with an N, you must select only numeric columns. If the code begins with a T, you can select numeric and text columns. The numbers to the right of the colon specify the minmax values. For example, if the minmax values are 24, you must select a minimum of 2 columns of data and a maximum of 4 columns in this box. If the minimum value is 0, then no data is required to be specified for this box. 
1  Standardize Continuous Factors:
By default, the continuous factors will be used asis to fit a model between the inputs and outputs. However, in some cases, you may want to modify your input variables before they fit the model. The available options are:
 
2  Reference Categorical Factors: By default, the levels of the categorical factors are sorted, and the last value in this list is assumed to be the reference or the baseline value. If you want to change the reference level to be used for the categorical factor, pick the level you want to use from the dropdown list. Note that this will modify the equation that will fit your data. To refresh the model terms, make sure to click on the refresh button at the top of the dialog box.  
3  Model Equation:
The model equation that is fit to your data between the output variable (Y) and the input variables (X1, X2, etc.) is shown in this box. The model terms should be separated by the plus (+) sign. For example, if your input variables are Weight and Length, then the model terms could be Weight + Length + Weight * Length + Weight^2. This will build a regression model with four terms, and the regression model will consider these terms. Ensure that your matrix is not singular when you specify the manual regression terms. For example, if you specify a term that does not exist in your input data set, all values in that input column for that variable will contain 0 values, and your matrix will be singular; hence, you cannot build that model. Another scenario could be a model like A + A*B + A. Here, the A column is repeated twice, making the model singular, and you cannot obtain a solution.  
4  Include Constant: This checkbox specifies if you want to include the constant term in your model equation. For example, if you fit a simple linear model between Y and X, then with the constant, the equation would be Y = mX + Constant, and without the constant term, the equation would be Y = mX. Use the model that makes sense for your particular case. If constants are included, then when X = 0, the model output will have a Constant (intercept) value. If no constant is used, the model intercept value is 0.0, meaning Y is also zero when X is zero. That is, the bestfit line passes through the origin. 
1  Confidence Level: Specify the confidence level for this analysis. This value is used to determine the prediction and confidence intervals. The default value for confidence level is 95%.  
2  Save Results:
You can store some of the calculated results on the worksheet. The following checks can be stored. Select the checkboxes for the variables you are interested in, and the software will store these values in the worksheet. The available variables are:
 
3  Fitted Line Plots:
You can display a fitted line plot between the input and output if you have a single input variable, X, and a response variable, Y. The raw data points are displayed as a scatter plot, and the best fit is shown as a line. On top of the fitted line plot, we can also include the confidence and prediction intervals. Specify if you want to superimpose the confidence or prediction interval on the regression plot. These intervals are plotted based on the confidence level specified in your analysis. If we were to take many samples from the population and calculate a confidence interval for each sample, the actual parameter would be expected to fall within the interval in a certain percentage of cases. The typical confidence levels are 95% or 99%. The following options are available:

0  Pick Charts: Select the charts you would like to display for this analysis. 
1  Title: The system will automatically pick a title for your chart. However, if you want to override that with your title, you can specify a title for your chart here. Note that this input is optional. 
2  Sub Title: The system will automatically pick a subtitle for your chart. However, if you want to override that with your subtitle, specify a subtitle for your chart here. Note that this input is optional. 
3  X Label: The system will automatically pick a label for the xaxis. However, if you would like to override that with your label for the xaxis, you can specify a different label here. Note that this input is optional. 
4  Y Label: The system will automatically pick a label for the yaxis. However, if you would like to override that with your label for the yaxis, you can specify a different label here. Note that this input is optional. 
5  X Axis: The system will automatically pick a scale for the xaxis. However, if you would like to override that with your values for the xaxis, you can specify them here. The format for this input is to specify the minimum, increment, and maximum values separated by a semicolon. For example, if you specify 10;20, the minimum xaxis scale is set at 10, and the maximum xaxis scale is set at 20. If you specify 10;2;20, then, in addition to minimum and maximum values, the xaxis increment is set at 2. Note that this input is optional. 
6  Y Axis: The system will automatically pick a scale for the yaxis. However, if you would like to override that with your values for the yaxis, you can specify them here. The format for this input is to specify the minimum, increment, and maximum values separated by a semicolon. For example, if you specify 10;20, the minimum yaxis scale is set at 10, and the maximum yaxis is set at 20. If you specify 10;2;20, then, in addition to minimum and maximum values, the yaxis increment is set at 2. Note that this input is optional. 
7  Horizontal Lines: You can specify the values here if you want to add a few extra horizontal reference lines on top of your chart. The format for this input is numeric values separated by semicolon. For example, if you specify 12;15, two horizontal lines are plotted at Y = 12 and Y = 15, respectively. Note that this input is optional. 
8  Vertical Lines: You can specify the values here if you want to add a few extra vertical reference lines on top of your chart. The format for this input is numeric values separated by semicolon. For example, if you specify 2;5, two vertical lines are plotted at X = 2 and X = 5, respectively. Note that this input is optional. 
1  Item: The lefthand side shows the major tabs and the items checked within each section 
2  Status: The righthand side shows the status of the checks. 
3  Overall Status: The overall status of all the checks for the given analysis is shown here. The overall status check shows a green thumpsup sign if everything is okay and a red thumpsdown sign if any checks have not passed. Note that you cannot proceed with generating analysis results for some analyses if the overall status is not okay. 
1  Model: The model analyzed in the current worksheet is displayed in this section. Note that if no model has been studied yet, you cannot make predictions using this dialog box. You will need first to generate a model using the Analysis Setup and Compute Outputs buttons. You can use a model to make predictions only when a model has been developed and saved to the worksheet. 
2  Date: The date shows the date the model was developed and saved to the worksheet. Note that once a model has been saved, it can be used for predictions. You don't need to use Compute Outputs to update the model. You can share this worksheet with other users, and they can enter their inputs and generate the predicted model outputs using the model equation. 
3  Inputs: Specify the input values you want to use to make the prediction. You will need to specify all the model inputs to make a prediction. A blank value of input will be taken as a value of 0. 
4  Predict Button: Click on the >> button to make the prediction. This will use the model equation and the inputs you have specified to generate the model outputs. 
5  Outputs: The outputs from the model are displayed in this section. Currently, the outputs are only displayed in this dialog box and not on the worksheet. You will need to manually copy the solution to your worksheet if you would like to save this value. 
6  Cancel Button: Click on this button to close this dialog box. 