Assessment instructions: Regression is a statistical tool used to understand and quantify the relation between two or more variables. Regressions range from simple models to overly complex equations. The two primary uses for regression in business are forecasting and optimisation. In addition to helping managers predict such things as future demand for their products, regression analysis helps fine-tune manufacturing and delivery processes

This essay focuses on applying regression methods. data set are on excel sheet in the table below{ blow is the data set given) to analyse and make a managerial report. This essay requires to focus on the key learning on linear and multiple regression and how they apply to real-life situations.

Case problem: Consumer Research, Inc.

Consumer Research, Inc., is an independent agency that conducts research on consumer attitudes and behaviours for a variety of firms. In one study, a client asked for an investigation of consumer characteristics that can be used to predict the amount charged by credit card users. Data were collected on annual income, household size, and annual credit card charges for a sample of 20 consumers. Managerial Report: Use the regression technique, students need to include the following in their report. 1) Develop estimated regression equations, first using annual income as the independent variable and then using household size as the independent variable. Which variable is the better predictor of annual credit card charges? Discuss your findings

2) Develop an estimated regression equation with annual income and household size as the independent variables. Discuss your findings.

3) Discuss the need for other independent variables that could be added to the model. What additional variables might be helpful?

Lycamobile .Ill @, y 30 66 1 21:41 Assignment Two. Data set 8 GA . . . fx 1 V A B C Income ($1000s) Household Size Amount Charged ($) IN 54 4016 W 39 3159 A 32 5100 UT 59 4742 6 31 1864 55 4070 8 37 2731 40 3348 10 66 4764 11 51 4110 U - NO A W N - A W W A N - N N O A N C 12 25 4208 13 48 4219 14 27 2477 15 33 O 2514 16 65 4214 17 63 4965 18 42 4412 19 37 2448 20 62 2995 21 21 4171 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 00 00 -70 O