EC1011 Data Analysis 2 Investigating the Effects of Prosocial Spending on Happiness for Psychological Research

Coursework Aims

The second coursework assignment for this module is an individual project worth a cumulative 50% of the overall module mark. This is an individual coursework that you must complete on your own. You must carry out your analysis in Excel, and you must submit your work online as one Excel file on Moodle. Please make sure that each of the five questions is answered on a separate worksheet. For each question, please indicate clearly which sub-question you are answering.

Overall, the work should not be more than 1,500 words long. You are given indicative word limits for each question. However, except question 5, you should feel free to distribute the number of words across the questions as you see fit, as long as the overall number of words stays within the limit of 1,500 words. There is a 10% allowance on the word limit. Markers will read any submission only up to the allowed word limit. Any word over the word limit will not be read. Any comments and text should be written by using ‘text boxes’ in Excel. Formulae, functions, graphs and Excel-generated tables do not count towards the word limit.

The Data Analysis Toolpack should NOT be used to calculate summary statistics, confidence intervals and carry out hypothesis testing. The appropriate Excel functions and statistical formulae should be used in the calculations.

Marking Criteria

When marking your work, we will look at the following features:

• Full marks will be awarded for accurate, detailed and informative answers and analysis. The correct formulae, functions, graphs and tables should be used. Good and relevant comments are added to the technical analysis.
• Solutions are computed by using the appropriate functions or formulae. Solutions whose derivation cannot be determined will receive a mark of zero. Simply producing values that are not generated by a formula or a function is not acceptable.
• Some marks will still be awarded even if the solutions or comments are not fully accurate or correct, provided that there is evidence of some positive approach to each answer.

For questions 1 – 4, the following criteria are applied:

For question 5, the marking will be based on the following criteria:

Grade A: The report is well written, focused and organised without spelling mistakes or inaccuracies; it provides an informative, correct, clear and interesting summary of the research and the findings from questions 1 to 4; overall, there is clear evidence of understanding, presented coherently and professionally.

Grade B: There is evidence that most of the criteria to achieve a grade A are met, but with some inaccuracies or shortcomings either in the overall writing or in the summary of the research and the coursework's main findings.

Grade C: The report is successful in providing a broad overview of the research and of the evidence emerging from the coursework. However, either a lack of clarity or organisation or style in the writing makes it difficult for the reader to understand the work carried out. Confusion and inaccuracy in the presentation of the findings also contribute to reducing the quality of the report.

Grade D: The report shows that there is some, but limited, understanding of the research and of the coursework findings. Ideas, evidence and findings are not presented in a coherent and structured way.

Grade F: The report fails to provide a concise, clear and informative summary of the research and of the findings. The structure and organisation of thoughts and understanding are not clear and raise doubts about the actual understanding of the overall coursework.

Academic Integrity, Misconduct Policy and Use of Artificial Intelligence

The Department expects you to uphold academic integrity and good academic practice by demonstrating behaviour that is honest and ethical in all of your academic work. You can get an understanding of what is meant by good academic practice and honest and ethical academic behaviour by consulting the University’s Academic Integrity & Misconduct Policy and Guidance.

Permitted use of Generative AI

Generative AI tools can be used only according to the following guidelines.

You are permitted to use Generative AI within the context outlined below.

• Ideas and understanding: You may use generative AI to aid and expand your understanding: to explain, connect, or generate ideas, to brainstorm and explore potential initial ideas you may want to cover in your submission. Anything you include in your submission needs to be described and structured in your own words.
• Output: anything you produce in Excel, whether formulae or functions or text or anything else, needs to be your product and should be the outcome of your efforts. The support of generative AI is acceptable as long as it is limited to supporting you with your work and not produce output used in the submission.
• Writing and production: You can use word processors, spell or grammar checkers, but not tools that rewrite or paraphrase more than individual words or phrases. All writing must be in your own words. You must not include any material that is directly copied from the output of a generative AI system in your submission.

If you use generative AI, you are required to do the following: add Excel worksheet to your submission file in which you:

• Include a list of the generative AI software that you used.
• Produce a list of the prompts that you used to interrogate the generative AI software.

Coursework Information

Does spending money on others (prosocial spending) lead to greater happiness than spending money on oneself?

The project asks you to investigate this question by replicating the research and the findings published in the article “Does Spending Money on Others Promote Happiness?: A Registered Replication Report” (the article is available on Moodle). The researchers carry out three experiments aimed at testing whether spending money on others (what is also called prosocial spending) leads to greater happiness than spending money on oneself. The experiments are explained in the article, and all the material and datasets used in the research are available on Moodle.

In this coursework, we will be focusing on two of the three experiments and, in particular, on experiment 1 and experiment 2. You will be assigned to investigate only one of the two experiments, and details of which experiment has been assigned to you can be found on Moodle in the file “EC1011 Project Experiment Allocation.pdf”.

Dataset Preparation

Before you answer the coursework questions, you should prepare the dataset for the analysis.

From qualitative to quantitative data

In preparation for the analysis, you should transform all qualitative answers in the datasets into quantitative ones according to the Likert scale below:

There are only two exceptions to the setup described above:

Question 1 in Part 1, “Do you feel alert in general”, T1_Alert, is a 5-Likert scale question, but the qualitative options are:

The last question in the Part 1 questionnaire labelled “T1-In general, I consider myself” is a 7-Likert scale question:1 (Not a very happy person) to 7 (A very happy person)In this case, you need to scale the question from 1 to 7. The coursework questions will ask you to manipulate this data to complete many tasks.

Compute the Happiness Indexes

In both experiments, each participant’s post-intervention happiness is measured by computing two indexes.

The first index is computed as the average of eleven items that include the positive feelings that make up the Positive and Negative Affect Schedule (PANAS). The PANAS positive feelings are: interested, happy, excited, strong, enthusiastic, proud, alert, inspired, determined, attentive and active. Let’s call this index PAS (Positive Affect Schedule).

The second index is computed as the sum of the 6 positive emotions that make up the Scale of Positive and Negative Experience (SPANE). The 6 positive emotions are: positive, good, pleasant, happy, joyful, and contented. Let’s call this index SPE (Scale of Positive Experience).

The Report

Use the data in your allocated dataset to investigate the relationship between personal spending, prosocial spending and happiness by completing the following questions.

Question 1

The research reports the participants’ baseline happiness level on a state “Do you feel happy right now” and trait “In general, I consider myself…” measures (see page e19 in the article).

• Do you think these two measures would be correlated? Why? Compute the correlation coefficient and comment on it. (100 words, 5 marks)
• Like in the actual research paper (see page e19), compute a baseline happiness measure for each participant by standardising each respondent’s score to the two questions and by averaging the two standardised values. Explain what standardising the scores means and produce some summary statistics of the baseline happiness measure (mean, median, standard deviation, minimum, maximum) and comment on your findings. (50 words, 8 marks)
• Produce and plot two density histograms of the baseline happiness measure: one for men and one for women. Compare and comment on the two density histograms and compute the probabilities that the happiness index is between 0.5 and 1.5. Comment on your findings. (50 words, 7 marks)

Question 2

The researchers are interested in investigating whether the prosocial behaviour (i.e. giving to others) leads to greater happiness than spending on oneself. To investigate this issue, you are asked to complete the following tasks.

• Researcher suggest using the PAS index (i.e. the average of the positive feelings) to estimate the participant’s average happiness level. Comment on whether this is a good index to measure happiness and, if not, what other index you would suggest using (Hint: this question does not ask you to discuss whether some other indicators of feelings of happiness should be used to compute the happiness index but, rather, whether a simple average is a good estimator or, instead, whether a different estimator should be used). (100 words, 5 marks)
• Compute and plot in the same graph two confidence intervals that have a high probability of capturing the personal and prosocial spending participants’ PAS index. Comment on your findings. (50 words, 5 marks)
• Only answer the question that is relevant to you:
• c.1) Answer this question only if you have been allocated to experiment 1 – Some researchers believe that individuals in the prosocial spending group tend, on average, to be less than ‘moderately’ (PAS < 3) happy. Test this hypothesis by also computing the p-value and commenting on your findings. (100 words, 5 marks)
• c.2) Answer this question only if you have been allocated to experiment 2 – Some researchers believe that individuals in the prosocial spending group tend, on average, to be more than ‘moderately’ (PAS > 3) happy. Test this hypothesis by also computing the p-value and commenting on your findings. (100 words, 5 marks)
• Researchers state that a more accurate way to test whether prosocial spending leads to greater happiness than personal spending would be to carry out a two-population mean test of the PAS index. Carry out such a test by making sure to also compute the p-value and comment on your findings. (50 words, 5 marks)
• Researchers believe that the impact of prosocial spending on happiness is different between men and women. Test this hypothesis by producing the appropriate confidence intervals and hypothesis testing. Make sure to plot the confidence intervals and to compute the p-values. Comment on your findings. (100 words, 10 marks)

Question 3

Researchers claim that the relationship between prosocial spending and happiness can also be investigated by comparing the proportion of participants that report a positive experience, i.e. a high SPE index (SPE ≥ 24).

• What estimator would you recommend the researchers use to estimate the population proportion of participants displaying a positive experience? Explain. (100 words, 5 marks)
• Compute and plot in the same graph two confidence intervals that have a high probability of capturing the personal and prosocial spending proportions of participants who display a high SPE index (SPE ≥ 24). (50 words, 5 marks)
• Policymakers believe that at least 50% of prosocial spending participants show a high SPE index (SPE ≥ 24). Researchers believe that this is an optimistic estimate and that the correct proportion is lower. Test this hypothesis by also making sure to compute the p-value. Comment on your results. (100 words, 5 marks)
• Researchers claim that a more accurate way to test whether the proportion of prosocial spending participants displaying a high SPE (SPE ≥ 24) is greater than that of personal spending participants would be to carry out a two-population proportion test of the SPE index. Carry out such a test by making sure to also compute the p-value and comment on your findings. (100 words, 5 marks)

Question 4

Some researchers claim that baseline happiness (the index you computed in question 1 above) can explain differences in happiness between the personal spending and prosocial participants.

• Test this claim by plotting two scatterplots showing the relationship between baseline happiness and the PAS index for the personal and prosocial spending participants. Also, compute the correlation coefficients and comment on the evidence. (100 words, 5 marks)
• The researchers believe that the personal and prosocial spending participants’ overall happiness index can be modelled, respectively, according to the following two equations: Overall Happinesspersonal spending = 3Baseline Happiness + 2PASOverall Happinessprosocial spending = 2Baseline Happiness + 5PASUse the rules of the functions of random variables to compute the expected values and the standard deviations of the two overall happiness indexes. (50 words, 10 marks)

Question 5

Write a short report that summarises the article and reports on your research findings. Your report should be organised as follows:

• Introduce the research question and the overall research aims and objectives.
• Briefly discuss the methodologies used to address the research question (briefly write about all three experiment setups);
• Provide a summary of the data collected to carry out the analysis (you should limit this summary to the data related to the experiment that you have been allocated to).
• Discuss your findings from questions 1 to 4. You do not need to repeat what you do in each question, but rather, provide a summary of your main findings and how they contribute to providing an answer to the research question.
• Briefly conclude by summarising your main findings and discussing their main implications.

Format:

• avoid the use of bullet points;
• You can consider organising the report in sections that focus on different aspects of the report, i.e. introduction, methodology, data, findings etc..
• Make sure that the various parts of your report are nicely linked up and that analysis is fluent and thought in your writing.
• avoid the use of the “I” pronoun and avoid using statements such as “as you can see…”;
• report numbers or statistics only when they are strictly necessary;
• Use the report to convey the main findings of your work in words rather than in numbers or tables, or graphs;
• If you are making use of graphs or tables or equations, make sure that they are properly numbered and labelled.
• make sure to be clear about the ‘technical’ aspect of your work without, however, missing out on explaining the importance and the main implications for policy, strategy or behaviour emerging from your analysis;
• Write your report in a ‘text-box’ in Excel and place it in a separate worksheet.
• The word limit for the report is 400 words but you are allowed to use up to 100 additional words provided that you are using 100 fewer words across the other questions.

(400 words, 15 marks)</p

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