1. Create Your Dataset:
o Select a Population of Interest: The possibilities are endless. You could study sports teams, countries/states/counties, musical artists/albums, political figures, celebrities, CEOs, streaming services, national parks, etc. So long as you can find a variety of information about each observation using the Internet, you can study it.
o If Needed, Choose a Sampling Method and Select a Sample: Be specific about your population and decide whether you can study the whole population or if you’ll need to draw a sample. For example, if you are only interested in studying NFL quarterbacks who played in a regular-season game during the 2021 season, you might be able to create a dataset with of the whole population. If however, you are interested in all NFL quarterbacks who have ever played, you’ll need a way of selecting a sample (e.g., random sampling).
o Choose Variables to Collect: Whatever you choose to study, you’ll collect a variety of pieces of data about each. For example, if you were composing a dataset of NFL quarterbacks, you could record a variety of continuous (e.g., annual salary, average passing yards) and categorical (e.g., whether they are right- or left-handed) variables about each quarterback. Think ahead about what type of analyses you’d like to be able to perform. For example, if you want to look for correlations, you’ll need continuous variables. If you want to compare groups, you’ll need categorical variables that can be used for grouping. Locate the data using the Internet and organize it into a dataset using Microsoft Excel.
o Create a Codebook: Following the instructions in the tutorial and using appropriate statistical vocabulary, create a codebook describing each variable in your dataset. Include this as an appendix in your final deliverable for reference.
o Save your Dataset: Remember, you can’t save multiple worksheets using the comma separated values (.csv) file format. As such, save your dataset as a .csv file and also save your codebook in a separate, Excel workbook. Include your dataset as an appendix in your final deliverable.
2. Perform the Analysis using JASP: You’ll need to include your full set of JASP outputs as an appendix for your final deliverable. Be sure to save all JASP outputs as you perform them.
o Descriptive Statistics: Fully analyze the descriptive properties of your dataset. Produce frequency/descriptive statistics for each variable and look at the shape/spread/skew of the data. Investigate possible outliers.
o Inferential Statistics: Chapter 16 of your textbook reviews how to select analyses appropriate to the variables and describe the results of those findings. Use that chapter to select analyses appropriate to your research questions and variables. Perform inferential analyses using JASP and interpret the p-values in light of your research question and/or predictions.
3. Prepare Your Report: Using Microsoft Word, create a report of your project that includes the following sections.
1. Introduction: Summarizes the scope and purpose of your project. Explain why you chose the project and what you hope to learn from the data you compiled. Be sure to specify your main research questions. Summarize and cite the article you selected for the Week 5 Deliverable and use it to contextualize your topic.
2. Description of Sample & Data: Describe the sample and/or population studied. In detail, explain the rationale and sampling method used to obtain the data. Using accurate statistical vocabulary, describe each variable studied and a rationale for why it was included. Include an APA-formatted in-text citation and reference for each source (e.g., website, agency) from which data was obtained.
3. Descriptive Analysis: Include a descriptive statistics section similar to the descriptive statistics report you prepared during Week 3 but also integrating more recent concepts (e.g., confidence intervals, boxplots/outliers). Provide both detailed verbal interpretations and data visualizations to familiarize your reader with the dataset.
4. Inferential Analysis: Include an inferential statistics section reporting interesting and/or significant findings from your data. For each inferential analysis you perform, include the following: your predictions/hypotheses and rationale for your predictions, a justification of the appropriateness of the statistical test based on the characteristics of the variables analyzed and research question being tested, specifics of the analysis performed and variables involved (e.g., which variables were treated as outcomes/predictors), and verbal interpretation of results including applicable statistics. If possible, also include a data visualization of your findings (e.g., bar graph, scatterplot).
5. Discussion: Conclude with a one- to two-paragraph summary of your project with a focus on the findings and their application. Consider possible implications (e.g., for personal decision making or policy) of your project. Remember, your job, as the statistician, is not just to state the statistical findings but to interpret them for your reader. Think critically, as a statistician, when offering interpretations for trends in your data.
6. References & Appendices: At the end of your deliverable, include APA-formatted references to all websites and other resources from which data were obtained as well as any articles referenced. Also, include an appendix section and include your codebook, dataset, and full JASP Outputs. Note, the instructor needs these materials to assess the accuracy of your statistical decision making and verbal interpretations.
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