Data Analysis Assignment
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Data Analysis Assignment
What and Why?
The goal of this assignment is to provide you the opportunity to work with a real dataset. This assignment will have you apply what you have been learning about statistics to a dataset. This will give you experience with using statistical software so that you better understand the process of analysing data and interpretating the results, which is what you will be doing if you go on to conduct research!
For this project, you will be given a simulated data-set. You will have to organize the data, select appropriate analyses, analyze the data, formally report the results in APA style, and reflect on your experience completing the project. Please note, you will need to make changes to the original data set to complete this assignment.
To complete the assignment, you will need the following files, in addition to the questions below (all of which can be found on Quercus):
1. Data Set (in csv format)
2. Data Dictionary – this defines each variable in the data-set (e.g., type of variable, scale it is on, when the variables were collected)
You will be using the statistical software jamovi to run your analyses. This is freely available online using the following link:
Notes on Analyses
Although in the ‘real world’ you might make choices about removing outliers or not doing an analysis because the assumption of homogeneity or normality is violated, for the purpose of this assignment please do not remove anyone from the data file and report all analyses even if assumptions are violated. You may still be asked to check the assumption (e.g., homogeneity of variance statistic provided with ANOVA) and report a corrected statistic – but I will specifically note this next to the test.
Basic Submission Details
All answers should be typed into a Word document and uploaded to Quercus by the due date (specified on the syllabus) in one of the following formats: .doc, .docx, .pdf. No other file formats will be accepted. It is your responsibility to make sure that your assignment has been uploaded and submitted correctly. You must also submit your final jamovi file with the updated variables.
Please take care to format your assignment (including typed responses, pasted figures and images) in an organized, easy-to-read manner.
For explanations and discussion questions, complete sentences are expected unless otherwise specified.
Assignment Instructions
PART 1: Data Organization
1. Before you begin working with your data, you should set up your file with descriptions and value labels. Value labels are used with categorical variables– these are labels to indicate what the numbers mean (e.g. – 1 is control condition) to make interpreting output and figures more straightforward.
2. In your dataset, there are items from two questionnaires that need to be averaged together to create a final score. Using the information from the Data Dictionary, compute all relevant scales for these measures. In addition, do a reliability analysis for each scale and indicate the quality of internal consistency for each (this will be discussed in correlations lecture); explain what this means for this measure, in words, and explain whether any items should be removed or maybe should have been reverse scored (you do not have to remove or reverse score, just interpret the reliability analysis).
a. Emotion inventory – negative emotions (sad, angry, anxious) a day before therapeutic intervention, a day after therapeutic intervention, and 3 weeks after therapeutic intervention (1 averaged score for each time point - 3 total!)
b. Ageism (4 items total).
A description of the variables, study design, and when measures were collected is provided in the data dictionary.
This assignment and the instructions above are based off an assignment shared with me by Dr. Molly
Metz.
26 marks total for updating data, creating appropriate variables, and providing reliability analyses and interpretation for the scales you created (the scales that required you to average items). Reliability analyses is explained in lecture 9, but I will make the video for this part of lecture available sooner so you can view it before starting the assignment.
3. For these scales and all other (already computed) scales the document (except “ID” and “Therapy”) compute and record (when appropriate – do not use a measure if it is not appropriate for that scale): minimum, maximum, mean, median, mode, and standard deviation. Which measure of central tendency is most appropriate for each variable? Why? Include all descriptive info in an APA style table in your final word document. When deciding which measuring is appropriate you should check the distributions of the variables – are they normally distributed? They do not have to be perfect. In jamovi, under exploration - descriptives, after adding your variables to the variables box you can go to statistics and select the skewness statistic. As long as this is under 1, your data are not skewed. You should also go to plots and get a histogram for each interval or ratio variables (regardless of whether they are discrete or continuous) and include the histograms with your table in your final report.
10 marks total for generating histograms, all appropriate measures of central tendency for each variable, and explaining why the measures of central tendency were appropriate (can group common variables together and create one explanation for them, so long as it applies to all the variables you are grouping).
PART 2: Planning Analyses
1. For each of the following tests, (a) choose the specific variables that can be analyzed using this test, (b) identify which is the predictor (or independent variable) and which is the outcome (ifrelevant), (c) and describe in words the research question you propose to test. There are many correct answers!
You will receive 3 marks for each response for a total of 21 marks.
a) One-way ANOVA
b) Repeated measures ANOVA
c) Two-way ANOVA (can be only between subject factors or between and repeated factors)
d) Correlation
e) Regression
f) Chi-Square Test of Goodness of Fit
g) Chi-Square Test of Independence
Example: (you may not use this in your assignment):
Regression
(a) Ageism and Agreeableness
(b) Agreeableness is the predictor Ageism is the outcome.
(c) Are people that are low in agreeableness higher in ageism?
PART 3: Analyzing and Reporting Results
Looking back at part 2, choose 4 of your proposed analyses to do:
(1) ANOVA – this can be one way between or within subjects – so a regular one-way ANOVA or repeated measures ANOVA (check homogeneity assumption, report on whether it was met, and report corrected stat if required). For either, you must conduct follow up multiple comparison tests and report these – even if your original F value is not significant (I want you to demonstrate you understand how to do this). (16 marks)
(2) factorial ANOVA– can be only between subjects or between and within (check homogeneity assumption, report on whether it was met, and report corrected stat if required. (18 marks)
**Please note – for (1) or (2) above, you must use a within variable for one of the analysis, so you may a just run a repeated measures ANOVA for (1) or use a repeated measures variable as one of your IVs for the factorial ANOVA (2).
(3) simple linear regression (13 marks)
(4) one type of chi-square analysis (hint – in interpreting where a difference lies - in particular for chi square test of independence - look at percentage or proportion of observations across cells. - 13 marks)
(4 total analyses).
For each analysis, paste the output into the document, and report your results in APA format. Your report should include both the APA-style statistical report as well as a description of the findings in plain language. Include each report of the results in its own paragraph with the plain language description of what was found at the end. Include measures of effect size for all analyses where possible. In addition, for 2 of the analysis create a data visualization that clearly displays your results (clearly labelled, easy to interpret). Paste the figures into the document and explain in words what exactly this figure communicates . For the other 2 analyses (different from the two you create figures for) create a table that clearly communicates descriptive information relevant to this analysis (e.g., means of each group for ANOVA, percentages or counts for frequency data) .
Note: the test does not have to be significant to run and report the test for the assignment; you will get credit for reporting the result accurately - significant or not
Also, that I acknowledge that if you pick inappropriate variables for an analysis in section 2, then run that analysis here in section 3, you might be concerned about losing marks for the same error twice. However, this should be a self-correcting process such that if you chose inappropriate variables for an analysis, you will likely get an error trying to run it and this should help you correct that mistake in part 2. However, if you are able to run and interpret and analysis even after selecting an inappropriate variable type, while some marks will be docked you can still get full marks for interpreting, reporting, and providing a table or figure for that analyses so long as you do this correctly.
PART 4: Reflect
Finally, include a 1-page reflection on what you learned or what skills you developed while completing this assignment and how you believe this will be useful to you either in a future career or your further education. This should be thoughtful and will be evaluated based on the quality (e.g., do you connect this to a specific education or career path, does the connection make sense – is it thoughtful and specific versus very general and vague.). (15 marks).
To get a good-exceptional (12- 15 marks) grade, you must demonstrate awareness of your strengths and limitations while completing the assignment and integrate examples into your analysis (e.g., do not make general statements but be specific about some of the tasks you completed and how these will help you in the future (e.g., education or career goal). This should be thoughtful and show engagement with the assignment.
Jamovi output needs to be submitted as well and should be organized such that it follows the order of the assignment instructions, with value labels appropriately set-up for all categorical (nominal) variables – 8 marks
Total Assignment /140 Marks
2022-07-25