The analysis results will appear as shown below. Specify GPA as the Y variable and GMAT as the X variable. Select Solutions > Analysis >Interactive Data Analysis. Select BUSI6220 as the destination library and GPAVSGMAT as the Member name.
Import the Excel data file by selecting File > Import Data > MS Excel > Next. Your new library should now appear as a new yellow icon.ġ.4.2. Type BUSI6220 as the name of the new library, and an appropriate folder location in the Path box. IN the SAS environment, you will need to create a library called BUSI6220 and convert the data file GPAvsGMAT.xls from Excel format to SAS format. Simple Regression in SAS 9.3 Open SAS 9.3. This will produce the output: Regression Analysis: GPA versus GMAT The regression equation is GPA = - 1.70 + 0.00840 GMATĪnalysis of Variance Source Regression Residual Error Totalġ.4.
#Regression excel 2010 Pc
Start MINITAB 16 for Windows, available from the Statistics menu of the standard COB PC configuration. Dependent Variable: GPAĬoefficients Unstandardized Standardized Coefficients Coefficients Model 1ġ.3. Regression Variables Entered/Removed Model 1 Confirm that variable names should be read from the first row of data.ġ.2.2. Start IBM SPSS Statistics 20, available from the Statistics menu of the standard COB PC configuration. In case Data Analysis is not found under Tools, add it under Tools > Add-Ins.ġ.2. Then fill out the popup window the same way as shown for Excel 2010. Open the Excel Worksheet GPAvsGMAT.xls and select Tools > Data Analysis > Regression. Data Analysis is now available under Excel’s Data tab.ġ.1c. To get the Data Analysis tool in Excel 2007, first click on the Office button (top left corner), and select Excell options > Add-Ins > Go > Select Data Analysis Toolpack & Toolpack VBA. This will produce the output: SUMMARY OUTPUT Regression Statistics Multiple R 0.8086001 R Square 0.6538342 Adjusted R Square 0.6346027 Standard Error 0.4350142 Observations 20 ANOVA df Regression Residual Total Then fill out the popup window as shown below, specifying GPA as the Y variable and GMAT as the X variable:
Open the Excel Worksheet GPAvsGMAT.xls and select Data Analysis > Regression. Data Analysis is now available under Excel’s Data tab. To get the Data Analysis tool, first click on File > Options > Add-Ins > Go > Select Data Analysis Toolpack & Toolpack VBA. As you can see, there are a number of ways to use the LINEST function for nonlinear curve fitting in Excel. Since the LINEST function returns b and log10(a), we’ll have to find a with the following formula: =LINEST(LOG10(yvalues),LOG10(xvalues),TRUE,FALSE) With the equation in this form, the LINEST function to return b and log 10 (a) can be set up like this: A power function has the form:Īgain, we can “linearize” it by taking the base 10 log of both sides of the equation to obtain: =EXP(number) Fitting a Power Function to DataĪ power function curve can be fit to data using LINEST in much the same way that we do it for an exponential function. Which, in an Excel spreadsheet, translates to: The second value returned by this array formula is ln(a), so to get just “a”, we would simply use the exponential function: =LINEST(ln(y_values),x_values,TRUE,FALSE) Now we can use LINEST to get ln(a) and b by entering ln(y) as the argument for the y_values: First, take the natural log of both sides of the equation to get the following: It’s a little trickier to get the parameter values a and b for this equation because first we need to do a little algebra to make the equation take on a “linear” form.