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Running head: TESTING FOR BIVARIATE CATEGORICAL ANALYSIS 1

TESTING FOR BIVARIATE CATEGORICAL ANALYSIS 11

Testing for Bivariate Categorical Analysis

Sahens Mezidor

RSCH - 8210A

Walden University

February 7, 2021

Dr. Rohrer

Scenario 1

In the first scenario, the relationship between police trust by the citizens of African countries and the

presence of democracy was examined. Afrobarometer dataset was used to explore the connection by using the Chi-square test. Chi-square test was used since we are two categorical variables (Gaboardi & Rogers, 2018). The categorical variables used were 1) Q59h. Trust police and 2) Democracy (dichotomous).

Trust in the police had four levels, 1) Not at all, 2) Just a little, 3) Somewhat, and 4) A lot. Democracy

was dichotomous 1) Yes or 2) No. The mean of ages for the participants was 37.39, as shown in Table 1. Table 1: Mean of ages Descriptive Statistics

N Mean Std. Deviation

Q1. Age 10232 37.39 14.863

Valid N (listwise) 10232

A cross-tabulation was formed, and Table 2 shows the results. Table 2: Cross tabulation Q59h. Trust

police * Democracy (dichotomous) Crosstabulation

Count

Democracy (dichotomous) Total

Not a Democracy Democracy

Q59h. Trust police Not at all 421 1705 2126

Just a little 297 2066 2363

Somewhat 234 2281 2515

A lot 136 2310 2446

Total 1088 8362 9450

According to the analysis, the cross-tabulation shows participants in each group. The total number of those who reported their countries are not democratic was 1088, while for democratic, the number was 8362. The cross table also said the total amount of participants grouped according to their responses to police trust. Chi-square was used to test whether there was a statistically significant relationship between

trust in police and democracy. Table 3 shows the results of the analysis. Table 3: Chi-square test Chi-

Square Tests

Value df Asymptotic Significance (2-sided)

Pearson Chi-Square 243.109a 3 .000

Likelihood Ratio 239.354 3 .000

Linear-by-Linear Association 233.990 1 .000

N of Valid Cases 9450

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INCLUDED SOURCES

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a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 244.77.

The analysis shows that the relationship is statistically significant where χ2 (3, N = 9450) = 243.11, p <

.05, η2 = 0.16 (Warner, 2020), which implies we reject the null hypothesis and conclude that there is a stat- istically significant relationship between trust in police and democracy. The effect size was large, meaning that there was meaningfulness. A visual presentation of the data is shown in figure 1. The bar graph shows that the people who have trust in police also reported their government as democratic and vice versa.

Figure 1: Visual presentation

The study shows that trust in police is related to democracy. Countries that are democratic have citizens who trust the police more compared to countries that are not democratic. The governments of the respect- ive countries should practice democracy, which ensures that citizens trust and work with the police.

Scenario 2

The second scenario examines whether there is a relationship between citizens' trust in police and

whether they reside in rural, urban, or semi-urban areas. The Afrobarometer dataset was utilized for this study to draw conclusions based on the research question. Chi-square test was used since we were com- paring two categorical variables with two or more levels. The variables used are 1) Urban or Rural

Primary Sampling Unit and 2) Q59h. Trust police. Urban or Rural Primary Sampling Unit had three levels, namely 1) Urban, 2) Rural and 3) Semi-Urban. The research was started as; Is there a relationship

between citizen trust in police and whether respondents reside in rural, urban, or semi-urban settings? The null hypothesis can be given as: H0: There is no statistically significant relationship between

citizen trust in police and whether respondents reside in rural, urban, or semi-urban settings. The cross- tabulation was as given in Table 4. Table 4: Cross tabulation 2 Q59h. Trust police * Urban or Rural

Primary Sampling Unit Crosstabulation

Count

Urban or Rural Primary Sampling Unit Total

Urban Rural Semi-Urban

Q59h. Trust police Not at all 1044 1193 26 2263

Just a little 1053 1409 40 2502

Somewhat 1039 1609 41 2689

A lot 730 1855 59 2644

Total 3866 6066 166 10098

The analysis shows that the total of respondents residing in urban areas was 3866. Many respondents were from the rural areas (6066), while the least number of people reside in the semi-urban areas. Chi-square analysis was carried out to examine the significance of the relationship. Table 5 shows the results of the study.

Table 5: Chi-square test Chi-Square Tests

Value df Asymptotic Significance (2-sided)

Pearson Chi-Square 204.896a 6 .000

Likelihood Ratio 209.423 6 .000

Linear-by-Linear Association 182.724 1 .000

N of Valid Cases 10098

a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 37.20.

The Pearson Chi-Square test shows that the relationship was statistically significant where χ2 (6, N =

10098) = 204.90, p < .05, η2 = 0.14. This implies that we reject the null hypothesis and conclude a stat-

istically significant relationship between citizen trust in police and whether respondents reside in rural, urban, or semi-urban settings.

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The effect size was large enough to imply meaningfulness. The visual representation was reported, as shown in figure 2. Figure 2: Visual representation

The analysis shows that people living in the rural have more trust in police than people living in urban and semi-urban areas. People living in rural areas interact well with the police increasing their trust compared to people in the urban. Again, a lot of people in the rural areas have faith in the police, while fewer people trust the police in the urban areas.

Scenario 3

This scenario examines whether there is a statistically significant relationship between perception of7

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This scenario examines whether there is a statistically significant relationship between perception of

current economic conditions and the extent of democracy. Afrobarometer dataset was used to explore the relationship of good decision making. The Chi-square test was the appropriate test statistic in this case since both variables were categorical. The variables used were 1) Q3a. Country's present economic

condition and 2) Q42. The extent of democracy. Both variables were categorical, with more than two

levels each. The study's research question was: Is there a relationship between perceptions of

current economic conditions and the extent of a democracy? The null hypothesis stated as shown: H0: There is no statistically significant relationship between perceptions of current economic conditions

and the extent of democracy. A cross-tabulation was determined to examine the relationship of the vari- ables used. Table 6 shows the results of the cross-tabulation. Table 6: Cross tabulation Q3a.

Country's present economic condition * Q42. Extent of democracy Crosstabulation

Count

Q42. Extent of democracy Total

Not a democracy A democracy, with major problems A democracy, but with minor problems A full demo- cracy

Q3a. Country's present economic condition Very Bad 436 987 739 343 2505

Fairly bad 341 968 943 434 2686

Neither good nor bad 137 449 682 296 1564

Fairly good 157 575 979 586 2297

Very good 23 95 157 157 432

Total 1094 3074 3500 1816 9484

According to the analysis, countries with no democracy reported high numbers in the bad economic conditions. Democratic countries corresponded to high responses to the right economic conditions (Bennett et al., 2017). A Chi-square test was conducted to aid in decision making on the subject. Table 7 shows the analysis of the variables. Table 7: Chi-square test Chi-Square Tests

Value df Asymptotic Significance (2-sided)

Pearson Chi-Square 500.943a 12 .000

Likelihood Ratio 492.594 12 .000

Linear-by-Linear Association 440.844 1 .000

N of Valid Cases 9484

a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 49.83.

Analysis shows that the relationship of the variables was statistically significant where χ2 (12, N = 9484) = 500.94, p < .05, η2 = 0.22. This implies that we reject the null hypothesis and conclude a statistically

significant relationship between perceptions of current economic conditions and the extent of democracy. The effect size was enormous, implying that the relationship was significant and meaningful. The visual rep- resentation of the variables was as shown in figure 3. Figure 3:

The analysis shows that the economic conditions of a country are related to the extent of democracy. Every country should practice democracy to increase the economic conditions.

Reference: Bennett, W. L., Borning, A., & Gruen, D. (2017). Solutions for environment, economy, and demo- cracy (SEED) a manifesto for prosperity. Interactions, 25(1), 74-76. Gaboardi, M., & Rogers, R. (2018, July). Local private hypothesis testing: Chi-square tests. In International Conference on Machine Learning

(pp. 1626-1635). PMLR. Warner, R. (2020). Applied Statistics: From Bivariate Through Multivariate

Techniques. SAGE Publications, Inc.

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Word Count: Submitted on: Submission UUID: Attachment UUID: 1,485 02/13/21 34045f6e-ce42-ad1b-885b-ba9c0284f391 66545c23-b99c-e9ec-6158-627b908d714f