Aims and Objective

The aim of this assessment is to develop and evaluate data-driven models based on simple and multiple regression models. It allows students to develop

and demonstrate the application of the methods of ordinary least squares using Excel. The assessment will consist of statistical analysis, graphs, analysis

and written report explaining your results and findings. This should be no more than 1500 words and should be typed, using ICP house style.

Advice about writing the report:

Use an introduction to set the aim of the report explaining the problem you are examining.

Structure the main body which should comprise of a discussion of your results.

Summarise the main regression results including the estimated regression line, estimated regression coefficients, standard errors, t-ratios, coefficient of

determination and present regression summary analysis.

Carry out hypothesis tests on regression coefficients and interpret your findings.

Explain your graphs of regression line and statistical results clearly in the report.

Summarise your findings/conclusion at the end of the report.

Answer all the questions.

Use references based on all the literature you have used in compiling this report. Use APA referencing system.

Pay attention to the overall presentation, structure and ensure logical development of ideas.

Assessment Criteria

Demonstrating competence in the production and presentation of results from Microsoft EXCEL

Understanding of methods employed,

Providing appropriate analysis, explanation and interpretation of results,

Structuring and presenting the report clearly,

LIBU105_Business Statistics_201801

Coursework Brief

Assignment;

Examine a time series data of demand for coffee in United Kingdom

from 1990 to 2016. As part of this assignment you will examine the market demand of

coffee model and evaluate the significance of variables influencing consumer behaviour.

In section A, use a simple two variable model to investigate the relationship between

demand and real price of coffee and real disposable income separately. You are expected to

analyse the regression results and comment on your findings.

In section B, you are expected to use multiple regression analysis and comment on your

findings.

Data

The following data is provided in an excel file and can be downloaded. The table show a

time series data of demand for coffee, the real price of coffee, and the real personal

disposable income of the consumer over the years (1990 to 2016) in the United Kingdom.

Download the data from M.S Excel file in module and answer the following questions in part

A and B. Remember you are expected to conduct descriptive statistics and inference

statisitics for the both sections

Section (A) Simple Linear Regression Model [40 marks]

1). Plot a separate scatter diagrams of demand for coffee, Y, against, ?1, real price of coffee

and for demand for coffee Y, and real personal disposable income, ?2. Comment on kind of

relationship that exit?

2). Assuming that the demand for coffee, ?, and real price of coffee, ?1, are linked by a

linear relationship, estimate this regression by Ordinary Least Squares (OLS) method, clearly

showing all your calculations (Excel can used for all the computations). [10 marks]

?? = ?(?? ) + ?? = ?? + ???1? + ?? [1]

3). Estimate the coefficient of determination – ?2 and comment on its value. Carry out an

appropriate test at 5% significance level for the explanatory power of the model.

LIBU105_Business Statistics_201801

4). Assuming that annual demand for coffee, ?, and real personal disposable income level,

?2 are linked by a linear relationship, estimate this regression by Ordinary Least Squares

(OLS) method using Excel:

?? = ?(?? ) + ?? = ?2 + ?2?2? + ?? [2]

5). Carry out an appropriate test at 5% significance level for the explanatory power of the

model, using the information in the regression summary output. [4 marks]

Section (B) Multiple Regression Analysis

It is reasonable to assume that demand for coffee depends on both the real price of coffee

and real disposable income. Use multiple regression analysis to investigate the relationship

between ? ??? ?1 ??? ?2 .

6). Estimate the following linear regression model using the data set:

?? = ?(?? ) + ? = ?3 + ?3?1 + ?4?2 ?? [3]

7). Compare the estimated coefficient for the real price of coffee, ?1, from the regression

equation (1) in section A and multiple regression equation (3) in section (B). Are they

different? If so, why? Explain your answer.

8). Tabulate the value of the coefficient of multiple determination, ?2 for the multiple

regression model? Explain the difference between the co-efficient of determination from

the first estimated linear regression (1) in section A and in section B – regression equation

(3).

9). Provide a conclusion based on all your findings in this assignments and hence comment

on the validity of the above regression models used in section (A and B). [10 marks]

10). What other variable(s) in your opinion could influence the demand for coffee in United

Kingdom. Provide a clear thought explanation for your reason.