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The objective of this assignment is to give students the opportunity to practice solving real

marketing research problems with data.

Detailed instruction on how to complete the assignment is available in “Assignment 2 – Guide”

section of this document.

Here are some general requirements for the assignment.

1. The due date/time of the assignment is by 11:59pm on Friday in week 11 (May 20

).

2. The assignment is individual work. Collaboration with your peers or any third party is

strictly prohibited

3. One copy is to be uploaded at the “Assignment 2” submission tab on the unit’s Moodle site.

In the rare event that unforeseen technical issues on Moodle prevent you from completing

the submission process, you should email the report to your tutor.

4. You need to first agree to the “plagiarism statement” above before you are allowed to submit

this assignment. Do NOT include cover sheets in your submission.

5. Naming your file for submission – the file name must start with the day and time of your

tutorial and contain your last name. For example, if your tute starts at 2pm on Wednesdays

and your last name is “Smith.” Your file name should be “wed2pm_smith_assignment2.doc”

6. Submission format: Microsoft Word or PDF file. Maximum number of words is

2000(±10%). The word count must be included in the first page of your document.

Exceeding the word count could result in a penalty of up to 10% of your mark for the

assignment

7. Please put references and statistical outputs you may have in the Appendix.

8. Students are required to keep a soft copy of their report until they get the marked report

back.

9. Detailed instructions on how to analyse data and report the research results are available on

the unit’s Moodle site. Please read them carefully before starting your work.

10. Please contact your tutor and/or the lecturer if you have any further questions.

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Assignment 2 – Guide

Case McDonald’s

A research report communicates the result of a study to clients. This assignment requires

you to write a brief research report based on the case “McDonald’s The World’s Number One

Fast-Food Company” and its accompanying dataset (both available on Moodle). The notes below

give you detailed instruction on the assignment. The textbook has a detailed discussion on how to

write a research report (chapter 19). While it can be an excellent source of information for you to

consult, you do not need to read that chapter to complete this assignment.

1. Definition of the research problem (15%)

In this section, you are asked to first identify a management decision problem (MDP) that is

relevant to the case and can be addressed with the attached dataset; and then develop a

corresponding marketing research problem (MRP). The requirement is similar to the problem

definition section in assignment 1. The main differences are that in this task you don’t need to

provide a detailed description of the background of the problem; and you have more material—in

the form of the questionnaire and dataset—to work with.

In approaching this task, I would suggest that you start by carefully reading through the

business case and familiarize yourself with the attached questionnaire and SPSS dataset. What

information has been collected from the target population? What does it tell you about their

behaviour, attitudes and demographics? What are the different types of respondents and how do

they differ from each other in different dimensions? More importantly, how can the company make

use of the information to improve their decision-making. Going through this list of questions would

help you come up with a relevant MDP.

Make sure that you describe your MDP and MRP in detail. For the MDP, define the scope

of the problem. For example, does the problem concern only particular segment of your population,

geographic area or time frame? For the MRP, make sure you describe the necessary components of

the problem and briefly explain how solving the MRP can help you answer the MDP.

2. Research approach (15%)

In this section, you are to develop at least 5 research questions (RQ) and the related

hypotheses. It is required that you generate both the null and alternative hypotheses, which are to

be tested in the data analysis section. While the RQs and hypotheses might not cover all aspects of

the MRP and its different components, they should address the most important aspects of the MRP.

You are likely to find existing literature helpful in developing the RQs and hypotheses from your

MRP. But you are not required to reference them for this assignment.

As you develop the RQs and hypotheses, think about whether the attached dataset contains

the necessary information for you to test them and what analysis techniques you need to use (e.g.

Descriptive, t-tests, ANOVA, Regression, Chi-square test, etc.).

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In presenting the RQs and hypotheses, usage of bullet points and tables is required. In

particular, you need to make clear which RQ each hypothesis corresponds to.

3. Data description and analysis (35%)

(a) Data description

First, briefly describe the data based on the information you have. Consider the following questions

as you work on this section.

1. What is the target population?

2. What is the sample size?

3. What kind of information has been gathered with the questionnaire (e.g., target population’s

attitudes and behaviour towards what? What demographic information is collected)

4. What descriptive characteristics of the sample can be learned from the data (for example,

what can you say about the level of income and education of the survey participants)?

(b) Data analysis

Describe how you plan to test the hypotheses you developed in section 2. For each

hypothesis, indicate what variables from the dataset and statistical techniques are used to perform

the test (for example, “an independent-samples t-test of the difference in loyalty (“Q3”) between

male and female”). If a multiple regression is used to test several hypotheses simultaneously, name

the dependent and independent variables that will be included in the regression.

A number of preparatory steps are likely to be necessary before you start formal hypothesis

testing. These include recoding of certain variables of interest, treating missing variables and

removing potential outliers. Describe them in detail if you undertake any of these measures.

A list of the main techniques discussed in the lecture is provided below. Please note that you

are not required to use ALL the techniques (choose only what is appropriate for your hypotheses).

That being said, appropriate use of a variety of techniques or the usage of more advanced

techniques such as multiple regressions is a necessity for high marks for this section.

You need to consider a number of issues in deciding which technique to choose for a

particular test. For example, certain techniques are only appropriate for interval-scaled data, while

others can be used for both interval- and ordinal-scaled data. Similarly, some techniques only allow

for comparison between two groups, while others allow you to compare the differences between

multiple groups.

List of the main statistical techniques

1. Descriptive statistics (frequencies, descriptive and cross-tabs)

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2. T-tests (dependent/independent samples) can be used to test for differences between means

of subgroups.

3. Chi-square test can be used to test the association between two nominally scaled variables. It

can also be called a test of independence.

4. Analysis of variance (ANOVA) can be used to see whether there are any differences across

the categories of the non-metric variables with respect to any of the metric variables.

5. Correlation analysis measures the degree to which there is a linear association between two

interval or ratio scaled variables.

6. Multiple regression can be used to explain the variance in dependent variables (outcome or

effect variables) using other metric variables as independent variables (causes).

4. Findings and Interpretation (35%)

(a). Reporting of the findings

You are required to report the results of your statistical tests. Include the SPSS output for each

hypothesis tested. Make sure that the output tables are properly labelled and clearly indicate

which hypothesis it tests.

Examples for including SPSS output in your text.

Table 1. Comparing the difference between 2007 and 2011

revenue (H1)

Is the null hypothesis rejected? Clearly state the outcome of each hypothesis test and what it

means in plain English.

Number the tables

Indicate which hypothesis

is being tested

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(b). Discussions of the findings and their managerial implication

Review your findings, what can you conclude about the MRP and MDP in general? In your opinion,

do the results properly address the MRP? Are there any gaps? For example, if one component of

your MRP is about identifying the factors that influence an important decision or attitude of your

target population, what are the factors that you have been able to test with your data analysis? What

factors might be important but you did not test (for example, because data are not available or you

did not develop the relevant hypotheses). Have a short discussion.

Briefly discuss the implication of your findings. For example, how can your client use this

information to run their business more effectively?

Appendices

Please include all SPSS statistical output from which you have derived your results—both

tables and syntax used, including any steps in data cleaning and recoding—in the Appendix.