Assignment:
This is a redo assignment for my social science class. My professor comments are below. Evidently, I needed a forum post with a brief into before I got into the findings. Please also see attached word that was done and help me with this.
"To note, you'll need to include an independent variable in your research question. If you are interested in religion, it could be: "Does a person's religion influence their opinion on committing suicide if a person has a terminal illness?" See how that makes a difference? Then, you would run your crosstabs with your IV on the column and DV (suicide for terminal illness) on the rows."
Please repost......Professor Glenn
Provide a brief introduction to your study to remind your classmates what we are reading about here. You will also title your thread accordingly (do not include the week # or your name). This week we talk about the uses of a crosstabulation (crosstab) and the benefits of creating this "snapshot" of your data. Create a crosstab for your data and include in the post. Be sure to explain your findings.
You will also identify the following times about your study:
1. Your overall research question;
2. The research hypothesis and null hypothesis
Special note:
When a variable is continuous (interval/ratio level of measurement), for example, age of respondent, we do not run crosstab directly b/c it will result in a really spread-out table with lot of 0s and low frequency cells. Such crosstab does not help us understand the data.
The correct way is to reduce the level of measurement to either ordinal level or nominal level and then run the cross table. The way to fix is to reduce I/R level of measurement to a lower level by lumping columns in into just a few categories. For example, you can group age 19 to 22 as one category, 23 to 30 as one category, and so on. In this way, your crosstab will help us better understand data. Here is an example of recoding: https://www.youtube.com/watch?v=uzQ_522F2SM
Interpreting crosstab output
When you interpret the result, please include the discussion of epsilons and the 10% rule. The epsilons in short is the differences between the highest and lowest column % in any given row. As long as one epsilon makes the 10% threshold, we'll deem two variables have "enough" going on to with each other to warrant further statistical analysis.