It would probably be easiest to type “=B2*C2” to directly target the cells with the desired numbers. Then, go ahead and multiply the two numbers in Row 2 together in this new column, as seen in the image below. We now want to label the next column with the word “Multiply”, as we are going to use it to multiply the rows’ numbers together. This means we want to predict the value of an employee’s job performance when their job satisfaction is 5 and their social desirability is 1. In this example, let’s choose the values of “5” for job satisfaction and “1” for social desirability. Then, you want to enter your specified values for job satisfaction and social desirability in the cells below the “1”. Now, we want to label the first empty column and add a “1” under the label. If you are confused by this, be sure to check out my YouTube video on “Inferences with Regression”.įirst, we are going to copy-and-paste our labels and unstandardized beta coefficients into a new Excel window. 379*SD, before adding all of it together to obtain our predicted value. So, we are going to use Excel to multiply. As you can see, the unstandardized regression equation from these results was: y =. We multiply these coefficients by the specified values of the predictors to predict our outcome. We will want to predict the outcome by using the unstandardized beta coefficients, which are just labeled “coefficients” in the Excel output. The results of your regression should look like the following: If you need help conducting this analysis for this example, please refer to my guide on Regression in Excel. In the example, it would be job satisfaction and social desirability predicting job performance. Go ahead and run your regression using all the predictors. In the dataset, we are investigating the relationships of job satisfaction and social desirability with job performance. If you don’t have a dataset, you can download the example dataset here. To estimate a value of the outcome given certain values of the predictor(s), however, we need to first conduct a regression analysis. Estimate someone’s weight given their height.Estimate a company’s revenue given its market share and location.Estimate the value of job performance given specific values of job satisfaction and conscientiousness.For instance, you could use regression to… Once you obtain your regression results, specifically your unstandardized beta coefficients, you can use these results to estimate values of the outcome given specified values of the predictor(s). If you need a refresher on regression, please check out my other guide on Regression in Excel. If you have any questions after reading, please email me at determines the liner relationship between predictor(s) and an outcome. This page provides a step-by-step guide on how to use regression for prediction in Excel. It can also allow researchers to predict the value of an outcome given specific values of the predictors. Regression can provide numerical estimates of the relationships between multiple predictors and an outcome.
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