![]() ![]() Therefore, product sales are created as the dependent variable and product prices are created as the independent variable.įor example, researchers have collected annual time series data from 2011 to 2020. ![]() In this case study, it is estimated that product prices affect product sales. Here, researchers can collect time series data consisting of product sales and price variables. Therefore, product price data is needed because the goal is to determine product sales predictions. On this occasion, Kanda Data will discuss product sales prediction estimates based on a simple linear regression equation. ![]() Several approaches can be used to predict product sales using regression. Product sales predictions can be estimated using linear regression. Predict product sales using linear regression Furthermore, researchers can enter the value of the price variable, and then product sales predictions can be obtained. The accuracy and precision of the product sales prediction depend on the P-value and the coefficient of determination of the equation created. Based on the regression estimation equation, it can be used to predict product sales in the next period. The intercept value and the estimated coefficient of the price variable are obtained based on the estimation results using time series data.įurthermore, using the estimation from the linear regression analysis, we can construct the regression estimation equation. Estimating the regression equation based on empirical data owned by the company can be used to predict product sales the next time.įor example, a company aims to observe the effect of price on product sales. In business management, linear regression can be used to predict sales. ![]()
0 Comments
Leave a Reply. |