Assignment WK 11

 

Assignment: Testing for Bivariate Categorical Analysis

You have had plenty of practice with data analysis in the Discussions and hopefully you have received helpful and encouraging feedback from your colleagues. Now, for the last time in the course, it is time once again to put all of that good practice to use and answer a social research question using categorical statistical tools. As you begin the Assignment, be sure and pay close attention to the assumptions of the test. Specifically, make sure the variables are categorical level variables.

For this Assignment, you will consider three different scenarios. Each of these scenarios include a research question. You will examine each scenario, choose a categorical data analysis and run a sample test.

To prepare for this Assignment:

• Review Chapters 10 and 11 of the Frankfort-Nachmias & Leon-Guerrero course text and the media program found in this week’s Learning Resources related to bivariate categorical tests.
• Using the SPSS software, open the Afrobarometer dataset found in this week’s Learning Resources.
• Next, review the Chi Square Scenarios found in this week’s Learning Resources and consider each research scenario for this Assignment.
• Based on the dataset you chose and for each research scenario provided, using the SPSS software, choose a categorical data analysis and run a sample test.
• Once you perform your categorical data analysis, review Chapter 11 of the Wagner text to understand how to copy and paste your output into your Word document.

For this Assignment:

Write a 1- to 2-paragraph analysis of your categorical data results for each research scenario. If you are using the Afrobarometer Dataset, report the mean of Q1 (Age). In your analysis, display the data for the output. Based on your results, provide an explanation of what the implications of social change might be.

Use proper APA format, citations, and referencing for your analysis, research question, and display of output.

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Week 11

Scenarios

1. Results of your literature review conclude that trust in the police is an integral

part of any democracy. You wish to test whether a relationship between trust in
the police and presence of democracy (measured with dichotomous variable)
exists in Africa. Using Afrobarometer 2015, please provide: a 1–2 APA style
paragraph statement that furnishes an answer to this question, note the relevant
statistics, comment on meaningfulness, and include your relevant SPSS output.

2. Following up on your previous analysis, you now wish to determine whether a
relationship exists between citizen trust in police and whether respondents reside
in rural, urban or semi-urban settings? Using Afrobarometer 2015, please
provide: a 1–2 APA style paragraph statement that furnishes an answer to this
question, note the relevant statistics, comment on meaningfulness, and include
your relevant SPSS output. In addition, please comment on what could be
influencing the results you obtained.

3. Is there a relationship between perceptions of current economic conditions and
extent of a democracy? Using Afrobarometer 2015, please provide: a 1–2 APA
style paragraph statement that furnishes an answer to this question, note the
relevant statistics, comment on meaningfulness, and include your relevant SPSS
output. In addition, please comment on what could be influencing the results you
obtained.

Learning Resources

Required Readings

Frankfort-Nachmias, C., & Leon-Guerrero, A. (2020). Social statistics for a diverse society (9th ed.). Sage Publications.

· Chapter 9, “Bivariate Tables” (pp. 281-325)

· Chapter 10, “The Chi-Square Test and Measures of Association” (pp. 327-373)

Required Media

· Laureate Education (Producer). (2016a). Bivariate categorical tests [Video file]. Baltimore, MD: Author.

 

· Note: The approximate length of this media piece is 5 minutes.

 

· In this media program, Dr. Matt Jones demonstrates bivariate categorical tests using the SPSS software.

   

 

     

     
   

 
 

   

 

                   
                 

     

                       

                 

   

   

     

                   
                 

             

                           
                                   
             
                         

   

               

             
                       

                   
           

             
                   

                   

                       
                       

         

                       
                         

             
                       

                   
           

                         
   

   

                     
                   

                       

Bivariate Categorical Tests

Bivariate Categorical Tests
Program Transcript

[MUSIC PLAYING]

MATT JONES: Up to this  point, we’ve been focusing on statistical tests  that
require metric  or  variables-­-­ that is, variables  measured at the interval or  ratio
level. But there are a lot of categorical variables  that are of use to the social
scientist. We’re going to cover  the chi-­square test for  independence and
associated measures  of effect of Cramer’s  V in SPSS.

Let’s go to SPSS. We can test for  the relationship between two variables  by  
using the chi-­square test for  independence. Let’s go ahead and test the
relationship between gender  and views  on marijuana legalization.

To do this, we go to Analyze, Descriptive Statistics, and Crosstabs. Here, you will
see a place to put a variable in a row and a column. I’m going to scroll down and
find my  SHOULD MARIJUANA  BE MADE  LEGAL variable and enter  that into my  
row, and I will scroll down to find the respondent’s gender  and place that into my  
column.

I’m going to go ahead and hit OK  to show you the output that we receive. And
here, you will see some output that are basic  Descriptive Statistics. These are
counts  of the number  of males  and the number  of females  who felt that marijuana
should be either  LEGAL or  NOT LEGAL.

However, this  does  not statistically  test for  a relationship between these
variables. We can request the chi-­square statistic  by, again, going back  into our  
Crosstabs  box. So I perform  the same procedure of going to Descriptive
Statistics, Crosstabs, and all of my  information is  still there, so I can select
Statistics. You’ll see that the Chi-­square statistic  comes  first, but I have to go
ahead and activate that.

I’m also going to go into the section Nominal to ask  for  Phi and Cramer’s  V. This  
will tell me something about the strength of the relationship between the two
variables. As  you know from  your  reading, the chi-­square tells  us  whether  there
is  a relationship, but it doesn’t tell us  anything about the strength of that
relationship. Find Cramer’s  V help us  with that follow-­up should we have a
significant relationship with a chi-­square. Continue.

OK. So I’m going to hit Cells. Just for  ease of interpretation, I’m going to request
Percentages  for  Columns.

I’ll hit Continue and OK. Here, you see, I receive some Case Processing
Summary. This  tells  me that there are 920 valid cases  in this  analysis. 580 cases  
are missing. So out of the 1,500 cases  or  respondents  of the survey, we have

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Bivariate Categorical Tests

quite a few of them  that either  didn’t answer, refused to answer, or  just left that
blank.

The next piece of output is  the Crosstabulation table. You can see this  looks  
similar  to the Crosstabs  I asked for  in Descriptive Statistics  with just the raw
counts, but now, I also requested for  the percent within respondent’s sex. This  
tells  me 55% of the males  believe that marijuana should be made LEGAL and
44.6% of the males believe that marijuana should be NOT LEGAL for  a
cumulative percentage of 100%. I can interpret the female column as  the same
way. 41% of females  believe that marijuana should be LEGAL while 59% believe
that it should be NOT LEGAL. If there was  no relationship between these two
variables, we would see approximately  equal percentages.

To statistically  test for  this, we can look  to our  chi-­square statistic. Here, we see a
critical value of 18.993 with an associated p-­value of 0.001. This  test is  significant
at the 0.01 level and certainly  well below the common 0.05 threshold. Therefore,
we can reject the null hypothesis  that there is  no relationship between the two
variables  assuming that there is  some sort of relationship between gender  and
position on marijuana legalization.

But once again, we don’t know the strength of that relationship. We can scroll
down to our  Cramer’s  V correlation, which tells  us  about the strength of this  
relationship. A  value of 0 indicates  no relationship whatsoever, and a value of 1.0
indicates  a very  strong, perfect relationship.

We can see here, we have a value of 0.144. So while there is  a relationship, it’s
important to do the follow-­up test to determine the strength of that relationship. In
this  case, the relationship between these two variables, which is  statistically  
significant at the 0.01 level, is  rather  weak.

[MUSIC FADING]

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