代写Assessment 3: Final Report代写Java程序

日期：2024-10-18 05:29

Assessment 3:  Final Report (35%)

Due Friday 20 October by 11.59 pm via Stream This is a group assignment.

Overview

This document contains the information and requirements for Assessment 3 as well as the workshop guidelines. By following the workshop instructions, you are building towards your final assignment!

Only one team member needs to submit the final report as an MS PowerPoint file with your team surnames and student ID numbers. Please ensure all team member names and IDs are on the front slide of the report. Everyone needs to separately upload their peer evaluation form.

In Assessment 3, you will put into practice what you have learnt in the course. You are required to analyse and interpret a case study data set by using graphs and summary statistics from your SPSS outputs. The data set allows you to use Crosstabs to look for associations between 2 non-metric (nominal and ordinal) variables,t-tests to compare the difference between 2 groups, and ANOVA to compare the differences between 3 or more groups.

In sum, this assessment gives you an opportunity to apply your skills in:

•     Getting familiar with SPSS and practice some simple coding

•     Descriptive Statistics (e.g., graphs,frequency distribution, means, standard deviation)

•     Crosstabs (e.g., Chi-square analysis)

•     Comparing means (e.g., one-way ANOVA, different typesoft-tests)

Please read the following case. Based on this case, you are required to produce a marketing research report using your market analysis and statistical knowledge.

Case Description

Please note that this case is fictitious (made up).

Eurocom - Market Expansion Strategy for New Zealand

IT product and services firms are growing fast in New Zealand. This growth has attracted

international companies seeking new opportunities to expand the market. One of those companies is Eurocom, a Canadian based IT company. Eurocom offers a varied range of IT products such as

laptops, desktop PCs, and printers. The management team of Eurocom is considering expanding    from Canada to New Zealand and aims to target all New Zealand regions. Eurocom intends to first launch laptops. Eurocom believes consumers have different needs, wants, lifestyles, and interests that affect what they look for in a laptop. They feel it is important to identify whether there are

distinct groups of consumers (i.e., market segments) relevant to their business offering. However, they need the help of market researchers to find this out.

Their primary marketing objective is to identify and describe these distinct market segments to target suitable prospects with greater profit potential. Eurocom may need to develop a

differentiated strategy for marketing communications, advertising, and servicing that fits the needs and characteristics of each target segment.

Given the intense competition IT companies now face from alternative devices such as smart-phones

and tablets, Eurocom will need to think carefully about a viable strategy in terms of who to target and how to reach/service each target provided there appears to be sufficient interest in their

business offering.

Eurocom recently hired a consulting team to design and conduct an online survey. Between June and August 2024, they emailed the survey link to 2000 consumers who live throughout New Zealand. The questionnaire and an SPSS data set of the responses to these questions can be downloaded from the Stream site. Assume the sample is representative of New Zealand consumers. Eurocom is unsure of    how to analyse this data set to determine whether they can achieve their marketing objectives. This   is where you and your team come in.

Based on this case the following marketing management decision problems are apparent:

1.    Should Eurocom enter the New Zealand market with laptop products?

2.    If so, who should they target and how?

To investigate these marketing management decision problems, we have formulated six research questions:

1.    What are the demographics of the target market (i.e., the laptop buyers)?

2.    What is the level of interest in laptops in the New Zealand market?

3.    What selection criteria are important in choosing a laptop?

4.    What information sources (i.e., magazines versus the Internet) are more important?

5.    What laptop information sources are important to which target market group (i.e., males versus females)?

6.    What laptopselection criteria are important to which target market group (i.e., different ethnicities)?

Your job is to give answers to each research question by analysing the data and subsequently providing Eurocom with useful information to make their decisions:

1. Should Eurocom enter the New Zealand market with laptop products?

2. If so, who should they target and how?

General Instructions

The weekly labs (or online workshops if you area distance student) will walk you step-by-step through the analysis for each research question to generate the results for your report (that

ultimately should help answer the decision problem). Try to conduct each type of analysis in the lab   session held after the lecture, where the technique is covered. Use your Massey H:drive or one drive to save your work as the SPSS outputs will not save, and you will end up having to rerun the

analysis. All relevant outputs produced by following this sheet should be redesigned andre-

formatted into a practical and “management friendly” reader style. Students should attend one lab   session per week and then work independently within their groups to complete any work that is not finished in the lab sessions.

You will present your findings on the case study discussed in this document in the form. of a report

(created in PowerPoint) directed to Eurocom. The case study described above contains a set of

marketing research questions. Your report should outline the potential for answering those research questions based on your analysis of the data. Your reports should contain ALL of the following

sections:

•     Title Page (Group name, member names & IDs, course number and name, assignment description) (1 slide)

•     Table of Contents with page numbers (1 slide)

•     Brief Introduction section – Survey facts, Project Management (1 slide)

•     Summary of Research Questions

•     Description of Sample

•     Summary of Main Findings (Organised by Research Questions)

•     Recommendations section

•     Appendices

Your report reader expects to see BOTH brief technical explanations of the procedures you followed (should be put into the Appendix), written in your own words, and a translation of the results into meaningful, practical marketing implications for the business discussed in the case described. Any   figures, tables, and graphs included in the report must be formatted so they are easy to read and

must be discussed where they are presented in the report.

Up to 30% of the marks may be deducted for reports that are not concise, poorly formatted, or     which contain excessive spelling and grammatical errors. Use the MS Word spelling and grammar check and have someone proofread your report. Use the active voice, not passive style. writing to achieve conciseness.

Exercises/Questions for Assignment 3

Workshop 1

Open the questionnaire and dataset

1.    Download the sample questionnaire called ‘ Eurocom Questionnaire’ from Stream and save it on your H-drive/OneDrive.

2.    Download the data from the 488 survey respondents in the SPSS file called “ Eurocom Survey Date” on Stream. After saving the SPSS file to your h-drive/one drive, please open the file.

The fictitious data set represents the responses that survey participants gave to the survey

questions.  Read each question one at a time, then check/compare the question with the SPSS data file to see how it is recorded in SPSS. This will help you understand your data.

SPSS opens two screens, one with an output file and one with the dataset. We first focus on the dataset. On the dataset screen, you can see two tabs on the bottom left corner: Data view and Variable view.

Data view: This is where you put all your data. (Responses from people who have filled out a questionnaire/survey)

Variable view: Here, you can give (and change) names to variables corresponding to questions in the questionnaire. You can also define properties here (more about that later).

We first have a look at the Variable view. In total, you should have 31 columns (variables) in your

Data view tab. Each variable relates to one question from your questionnaire. For instance, the first variable is PNO, the Participants Questionnaire Number (a code for each respondent).

The second variable is called Q1, which represents the first question, “ Do you plan to buy a laptop in the next 12 months?” The variable name tends to be very short. Since variable names are very short, it is also a good idea to add slightly longer labels to all variables. Making the variable understandable but not too long allows you to remember its meaning without having togo back to the

questionnaire. In this case “Plan to buy in 12 months” makes sense and is easily read in the window without having to scroll the whole question.

The Name and the Label of a variable in each column also have Values. Values assign numbers to the  respondent’s answers, that we also call coding answers. The main reason we code answers (by giving them numbers), is that most statistical packages like SPSS will only do mathematical analysis with

numbers, not words. One very useful property of SPSS is that it allows you to assign a description for each numeric value a variable can take. This makes it easier to work with the data without having to  go back and check what the value of each variable represents. Most of the answers in our data set

are already coded. However, the last 3 variables still need coding. To code the last 3 variables, carry out the following actions:

Coding Instructions

1.    Go to the Variable View and click on the cell defined by the row “ (Q12) Gender” . Under the “Value” column add the following Value Labels: 0 = Females; 1 = Males.

2.    Next, give labels to the levels of “Age Group”, using the labels given below:

1 = 18-29 2 = 30-39 3 = 40-49 4 = 50-59

5 = 60 and above

3.     Give names to the levels of “ Ethnic background”, using the terms below.

1 = Asian

2 = NZ European or European 3 = Māori

4 = Other Ethnicity

Do you see what happens if you goto the Data View tab and then to the View menu (top-left) and uncheck “Value Labels”? What happens if you check it again?

At this stage, it is useful to again save your data to your H-drive/One Drive. Please do sousing the file name Eurocom Survey Data.sav. In general, it is a good habit to save the data frequently, to

avoid re-doing work in case of a computer problem.

Measurement levels

In the Variable View tab, you can see a few remaining columns we have not explained. Most of these are easily interpreted, but there are two that need some extra attention.

Type: This gives the type of the variable; in our case, these should all be numeric.

Measure: Gives the scale level of the variable, Nominal (i.e., the number is just a label), Ordinal (i.e., the number is more than just a label and implies a certain order, such as higher means more), and Scale (i.e., the number implies a certain order and the difference between values is meaningful). SPSS does not distinguish between Ratio or Interval scales and labels them both as Scale.

Often SPSS does the thinking for you, but with “Type” and “Measure”, it is wise to double check as SPSS does make some mistakes here. Now all variables in your data set are Nominal. Do you think all those levels are correct? What scale level should each variable be? Check out every variable and correct the scale level if it is wrong? (Hint: 25 variables have the wrong scale level defined).

Workshop 2- Descriptive Statistics

Descriptive Statistics:

So now we have checked and entered, if necessary, all the data. Next, we want to analyse what the data means. One way of analysing data is to obtain descriptive statistics.

For assessment 3 (final report), you will be able to use the results of your descriptive statistics to

describe your sample.

First, we want to describe the sample. Have a look in the drop-down menus in your SPSS for

"Analyse", "Descriptive Statistics", and next, “ Frequencies". Describe (i.e., profile) respondents by  running “ Frequencies” on Q8 and Q11-Q14 in the data set. You can make pie chartsandbar charts by clicking on “Charts” followed by “Bar Chart” or “Pie Chart” .

If you did it correctly, SPSS has now added these tables and graphs to your output file, Output1.spo. Please save this file to your H-drive/One Drive using the name, Eurocom Results.spo. By saving this

file after every new output is added, all output of this session should be stored in this file. Go back to your output file. Look at your bar graphs. For the appropriate variables (keep the scale level in mind), order the answer categories in the graph from high to low. To do this, double click on the graph and   within the Chart Editor, select X. You can now sort the categories by a statistic.

Look at all the tables and graphs in the output. What do the tables and graphs tell you? Who is in

your sample? With the outputs of this analysis, you can describe your sample. However, keep in

mind that the scale level determines how you should summarise and present each variable (e.g., the use of a table, pie chart, or bar chart depends on the scale level - nominal, ordinal, scale). Pick the

tables and graphs that are the most appropriate way to summarise each variable. If you can’t remember, go back to the lecture material - Descriptive Statistics).

Copy the appropriate tables and graphs into your PowerPoint (which starts the document for your     final report). The lecture material on Data Analysis - Descriptive Statistics will show examples of how you can present your graphs and tables.

Workshop 3

Cross-tabs using Chi-Square analysis:

We are now ready to embark on slightly more advanced analyses. The first research question aims at profiling the target market (i.e., the laptop buyers) in terms of their demographics. To answer

this research question, we conduct and interpret some Chi-square analyses. Please goto "Analyze",    "Descriptive Statistics", and "Crosstabs". Create 4 cross-tables by putting Q1 in the row box and Q11- Q14 in the columns box. Click ok. Go back to your output file. Do you see any associations?

Now go back to crosstabs ("Analyse" "Descriptive Statistics" "Crosstabs") and click on

"Statistics,” check the "Chi-Square" box, and click "Continue". Also, click on "Cells" and check both

the "Counts Observed", and the "Counts Expected" box. Also, under Percentage, click “Column” . Run the cross tables again. When you look at the output, how would you interpret it? Please keep in

mind that we should only interpret outputs that show significant associations! Think about why Chi- square is an appropriate method to analyse the associations for these variables. You should include  the rationale for using Chi-Square in your appendix.

Copy the tables/graphs that show significant associations into your PowerPoint document (the

document you will submit as assignment 3). Keep in mind that this table belongs to the first research question. Start answering research question two based on your tables. The lecture material on Data   Analysis -Inference Statistics will show examples of how you can present your results.

Workshop 4

The second research question assesses the level of interest in laptops in the New Zealand market. To answer this research question, we first want to look at some descriptive statistics (If you forgot

how to do descriptive statistics, go back to workshop 1 that explains how to make frequency tables    and charts). For this analysis, make a frequency table and a pie chart of consumers who plan to buy a laptop and those who do not plan to buy a laptop (Q1) and run another frequency table and bar

chart on Q4 (likelihood to buy a customised laptop made by a new brand). Look at all the tables and graphs in the output. What do the tables and graphs tell you? How would you answer research

question two based on the tables and/or graphs?  Since we want to make sure that we can infer that our results are also true for the population of interest (and not just our sample), in the nextstep, we calculate a one sample t-test that will tellus whether our results are significant or not.

One sample t-test

In the first step, we look at the value for the likelihood to buy a customised laptop made by a new    brand (Q4). Goto question 4 and check the values. What value represents at least some likelihood?

Now try to formally test whether respondents are interested in a new customised laptop via a one-    sample t-test. Goto "Analyse", "Compare means", "One Sample T-test", and select the variables. Put "3" as the test value. Think about why 3? Is that an appropriate value to test against? What does the output tell you?

You need the output of this analysis for your report to answer research objective two. Copy and

paste the graphs/tables into your PowerPoint document. Try to answer this research objective using  the result of the analysis. The lecture material in the week on Data Analysis -Testing for Differences 1 will provide examples of how you can present your results.

The third research question assesses the importance of selection criteria in choosing a laptop. To

answer this research question, we first look at the values for the importance scale for the selection

criteria (Q6a-Q6i). What value represents no importance, and what value represents at least some

importance? Remember, you can see the values under ‘Variable View’ . Next, to get an initial feel for the answer, we first create an Error Bar for the selection criteria. Goto "Graphs," "Legacy Dialogs,"

"Error Bar," and select "Summaries of separate variables". Click on "Define", select all the selection     criteria (Q6a-Q6i), and click OK. In the output, double-click on the error bar graph and transpose it by clicking “Options” followed by “Transpose Chart”, i.e., this ensures that the variable names are on

they-axis. Next, we want to order the mean values from high to low. We do this by clicking on they- axis. If you did this successfully, another window will open. You can now sort the variables by

selecting ‘statistic’ . Leave the direction as “ascending” . Click ‘Apply’ . Have a look at your output. What do you see? What are the most important selection criteria? What are the least important selection criteria?

Now try to formally test which one of the selection criteria are very important. We can do this again by doing a one sample t-test. Go again to "Analyze", "Compare means", "One Sample T test", and

select the variables (Q6a- Q6i). Put "3" as the test value. What do you see? Which of the selection criteria are very important?

Copy the error bar and the tables from the analysis into your PowerPoint document. Start answering research objective 3 using the graphs and tables. The lecture material in the week on Data Analysis -  Testing for Differences 1 will provide examples on how you can present your results.

Paired Sample t-test:

The fourth research question assesses whether magazines or the Internet are more important as information sources when students want to know about laptops.

Now, we try to formally test whether the newspaper/magazines or the Internet as information

sources are more important. We do this using a paired sample t-test. Goto "Analyze", "Compare    means", "Paired-Samples T-test", select the selection criteria variables (Q7aand Q7b) you want to test against each other, and click OK. What does the output tell you?

Copy the tables from the analysis into your PowerPoint document. Start answering research question 4 using the tables. The lecture material in the week on Data Analysis -Testing for

Differences 1 will provide examples of how you can present your results.

Workshop 5

Independentsamplest-test:

The fifth research question assesses what information sources are important to which target market group (males versus females). To give answers to this question, we calculate an

independent sample t-test.

To know whether males and females differ significantly in terms of the importance they give to

different information sources (Q7a-Q7f), goto "Analyse", "Compare means", and "Independent

sample T-test". The test variables are Q7ato Q7f, and the grouping variable is Gender. Click also on    "Define Groups", and type for group 1 = "0" and for group 2 = "1" (why?). What do we learn from the output?

Copy the results of this analysis into your PowerPoint under the fourth research objective. Start writing answers to research question 5. The lecture material on the Data Analysis -Testing for

Differences 2 will provide examples of how you can present your results.

One-way ANOVA

In order to give answers to the last research question (Q6), Assess what selection criteria are

important to which target market group (i.e., different ethnicities), we calculate an ANOVA. Why would we use ANOVA for this?

To know how people from a different ethnic background differ in terms of the selection criteria, go   to "Analyse", "Compare means", and "One-Way ANOVA". The dependent variables are the selection criteria (Q6a-Q6i), and the "Factor" is the variable for ethnicity. Click also on "Post-hoc multiple

comparisons" and select the Scheffetest (click continue). Next, click on "Options" and select

"Descriptive Statistics", and "Means plot". In the output, double-click on the Means plots (at the

end) and make they-axes comparable across the plots by choosing the range from 1 (minimum) to 4 (maximum). You can achieve that by double clicking on each graph/means plot. A separate window   will open. Click on the Y-Axis. Select minimum 1 and maximum 4.  Click “Apply” . Repeat this for each means plot graph.

Go back and have a look at your ANOVA output. What do we learn from the output?

Copy the results of this analysis into your PowerPoint under research question six. Start writing

answers to the last research question. The lecture material in the week on Data Analysis -Testing for Differences 2) will provide examples of how you can present your results.

Workshop 6- Report Writing

Finalising the Report

Be sure to present your results/analysis in amanagerially friendly way. Also, discuss the practical

implications of your analysis for the Eurocom marketing strategy (segment, target and/or positioning aspects) and make recommendations.

Use the structure outlined at the beginning of this document as the framework for your report. For every research question, provide answers based on the analysis of the SPSS workshops. Make sure  to present the results in a manager friendly form. Use the graphs and tables SPSS generated as a

base, but use Excel or PowerPoint to improve the look of the graphs and tables.

Avoid using statistical language in the main body of your report. Give a brief, clear explanation

related to your research questions. To each brief result/graph, add a sentence such as, “please see

Appendix xx for more information” . In the Appendix, you can add the SPSS created graphs and tables and further elaborate on the statistical details of the analysis. You should also add why you have

chosen each method of analysis. For example, explain why you are using a certain test and what the  p-value and mean value means. The lecture material on the week Report Writing will show examples of how you can present your results and how to finalise your report.

All files uploaded will be submitted to the text matching detection service Turnitin.com The valid format for the report is MS PowerPoint.