Linear regression

INDIVIDUAL ASSIGNMENT (10%)

BSTD101: BUSINESS STATISTICS

SEMESTER: NOVEMBER 2014

LINEAR REGRESSION

To complete this assignment, each student needs to analyse the following questions INDIVIDUALLY by using the same data set collected in your group assignment.

Objective:

Upon successful completion of this subject, students will be able to:

· Identify the dependent and independent variable used.

· Correctly put, read and interpret computer generated output using Excel.

· Using linear regression equation for prediction.

Instructions:

1) Please ensure the following details included in your assignment to avoid reduction in marks:

1. Complete Assignment Cover page (as attached in MIB)

2. Please use Times New Roman with a font size12 and line spacing: 1.5. Every page should be numbered.

3. All Excel outputs, answers and Excel database of survey should be copied and paste into the Microsoft Word document.

4. All part answers, graphs and charts must be properly labelled. [Handwritten answers will be disregarded.]

5. Complete Assignment Feedback form (as attached in MIB)

2) Late submissionwill deduct 5 marks of the total marks (25%). Late assignment after the 24 hours will not be accepted and will be recorded as a non- submission.

Scenario:

You and your group members are at a marketing research firm and asked to do the following project:

By using the same data of monthly income/pocket money and the time spent for car wash per month in the attached excel spreadsheet, carry out the following correlation and regression analysis.

1. Identify and state clearly the independent and dependent variable. [2 marks]

2. Use Excel to generate a summary output for regression analysis. [2 marks]

3. Based on the summary output,

a. Develop a regression equation [1 mark]

b. Interpret the value of y-intercept and slope. [3 marks]

4. Based on your analysis, do you think that the dependent variable is explained by the independent variable? Explain your reasons. [4 marks]

5. Explain on the reliability of using the regression equation to predict the dependent variable [5 marks]

6. State TWO more independent variables which may influence the dependent variable. [2 marks]