labels on regression in data analysis excel

#Labels on regression in data analysis excel how to#
#Labels on regression in data analysis excel series#

The first stage is to input all product sales variable data (Y) into the Input Y Range, then click the up arrow to open as in the following picture: At this stage, to be able to process multiple linear regression analysis data, it is necessary to input the Y variable and the X variable. After the regression is clicked, a new Regression window will appear. In the next step, please select regression from the available analysis tools. After clicking on Data Analysis, a Data Analysis window will appear containing various analysis tools provided by Microsoft Excel, as shown in the image below: From the various options in the upper right corner, click the Data Analysis menu. Data Analysis Procedureįirstly, the steps for processing multiple linear regression analysis data are to open the Microsoft Excel file that has been inputted with the variables to be tested.

#Labels on regression in data analysis excel how to#

In the previous article, I have written how to activate the Data Analysis menu in Microsoft Excel. The data that has been inputted in Microsoft Excel can then be directly processed using the Data Analysis menu. Then the data is inputted into Microsoft Excel, as detailed in the table below:

#Labels on regression in data analysis excel series#

The data collected is time series data with particular objects and consists of several periods. Data has been collected every three months (quarterly) based on the company’s 15 observations (n) secondary data. The manager determines product sales as the dependent variable/response (Y), advertising costs, and marketing staff as independent variables/ predictors, respectively, as X 1 and X 2. Variable specifications are carried out on the dependent and independent variables to be analyzed. Data were collected quarterly from the 4th quarter of 2016 to the 2nd quarter of 2020.

For example, a manager observes how advertising costs and marketing staff can influence product sales in a company XYZ. Multiple linear regression analysis is intended to test the effect of independent variables on the dependent variable, where the number of independent variables is 2. It is important to test this assumption to obtain the best linear unbiased estimator. In various research results that have been published, linear regression using the ordinary least square method is the most dominant one used by researchers. Most of the regression equation specifications compiled are single equations with assumptions that must be fulfilled. Regression was selected because it can answer the estimated influence of one variable on other variables at one time and several times (time series). Although the regression consists of linear and non-linear regression, linear regression is the most widely chosen data analysis method by researchers. Regression analysis is very popular for researchers, both for writing a bachelor thesis, master thesis, and dissertation thesis, decision-making at the company level, and scientific development. Therefore, a basic understanding of statistics needs to be understood by those conducting research activities. The research hypotheses prepared at the beginning of the proposal need to be tested statistically so that the correct findings can be obtained. Data analysis methods not following statistical theory and scientific principles can potentially cause errors in making research conclusions. The selection of data analysis methods is important in determining the study’s results.