Sales Prediction for Northern Household Goods Case Study

Sales Prediction for Northern Household Goods - Case Study Example ion is the commonly used model in management sciences while its application is significantly noted in the areas of social sciences and natural sciences as well. However, in simpler terms, the statistical technique is used in order to determine the level of predicted variable on the basis of each amount of the predictor. Furthermore, the application of bipolar regression is dying out because one outcome variable in indeed influenced by multitude of the inputs such as the level of one’s organizational commitment is influenced by supervisory behaviors of the company, his or her pay-scale and nature of the job. In the given case, an organization is interested in developing a scatter diagram of the relationship between retail sales and disposal incomes of the family then the company is also looking to develop a linear regression model between the abovementioned variables. The 95% confidence interval about population data’s slope and finally, it is required to determine the l evel of sales if income of the household remains constant at the level of $58000. The p-value associated with X as a predictor of Y highlights that the relationship between the two variables is statistically significant. The lower and upper bound values determined in the preceding table for B represent a following 95% confidence interval: - In the light of established linear model, we can assume that the company can sell 23963 units if the household income would be 58000. However, we can establish that sales can be successfully predicted with the help of entering the level of household incomes of the