data project (must use jamovi)

https://video.ucdavis.edu/media/Soc+46B+Data+Analy…

here is a video tutorial on the assignment

Overview

The data projects give you a research question to answer with real data. You’ll apply relevant core concepts to an important sociological problem, analyze data using skills from the weekly activities, and interpret the real-world importance results.

For Data Project 3, you’ll apply skills covered in weeks 7-9. Based on the research question given below, you’ll formulate and test hypotheses using data from the American Community Survey (ACS). You’ll submit a document resembling a very short sociological study (around 3-5 pages, including tables and charts). This document will describe the project’s research question and hypotheses, data and analyses, and the results.

Research Questions

In addition to common knowledge, we’ve examined gender pay gaps a couple times in this course (chapters 5 and 10 of the textbook). We’ve also seen that gender inequalities in the workforce can vary by field of study or job type (reading by Dr. Quadlin in week 8).

For this project, you’ll test hypotheses for whether there is a gender pay gap in three different occupations (food service, mail carriers, psychologists). Within each occupation, you’ll answer the question, “Are typical full-time working women paid less than typical full-time working men?” You’ll develop the appropriate null and alternative hypotheses for this question.

In addition to addressing the gender pay gap within each of these three occupations, you’ll also address the question, “Does any gender pay gap differ between low-, middle-, and high-wage occupations?” (You don’t need to formulate hypotheses for this question. You can simply describe why you think there might be an association and whether the data support that.)

Data

You’ll test your hypotheses with data from the 2018 American Community Survey (ACS). Click here for a document summarizing the ACS sampling design, response rates, and strategies for handling item non-response.

Click here to download the ACS data in jamovi format

The main variables for this project are:

• sex
• annual earnings
• occupation

Hints:

• To conduct a test with the mean of a quantitative variable with a skewed distribution, you may need to transform the variable to reduce/eliminate the skew (see the weeks 7 and 8 tutorials).
• Use “filters” to test hypotheses about the gender pay gap within each occupation separately (see the week 9 tutorial for a very similar process).
• To determine which occupations are high/middle/low-wage occupations, you can calculate typical annual earnings for each occupation (see the week 4 tutorial).

Click here for a detailed recommended outline/checklist for your submission

The Data Analysis tutorial for week 8 is generally similar to Data Project 3. You’ll simply repeat the hypothesis test for earnings three times (once in each occupation). The week 9 tutorial demonstrates how to use the filters to easily repeat the tests for different groups.

Academic Integrity

The TAs and I can answer general questions about the project and specific questions about project instructions (i.e., “Where do I put the captions for my figures?”). However, we cannot answer specific questions that would give you the project’s solutions (i.e., “is this percentage correct?” “do these results support the alternative hypothesis?”).

You may work with other students to figure out how to do the project. However, your written submission must be your own work. You may not copy text, tables, or charts from another student. In short–it’s fine to talk things through with each other, but every student should complete the analysis and writing for their own submission.

Rubric

Data Project 3 Rubric