Posted: February 27th, 2021

Statistics assignment (cross-tabulations) urgent work (10 hours)


Topic: Suicide

My professor says my work is fuzzy so please keep this in mind when helping me with suicide please. I want to get it rght this week so i can get full credit

You cannot pursue your research question as it is stated.  We can only measure public opinion on suicide.  

Thus, you’ll need to use two variables from the GSS, and you should only be using the 2012 data set that you download from the first week’s lesson in the required readings page. Unfortunately, there are very few individuals who are in the military in our sample.  You will likely want to choose a different independent variable – characteristic – that will influence a person’s opinion on suicide if the person is tired of living (your dependent variable).So, decide your independent variable, then run just the frequencies for each and create charts for each of your variables with just the 2012 data provided…..this was my professors message to me.

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

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:

When you interpret the result, please include the discussion of epsilons (p. 170) and the 10% rule (p. 165). 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.

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