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Descriptive Statistics
The table above shows that the number of male students who took part in the study was 65 while the number of female students who took part in the study was 67. Male students, therefore, represented 49.14 percent while female students represented 50.76 percent.
The table above shows that: the number of students who said they were not afraid of crime on campus was 46, representing 34.65 percent of the total number of students who participated in the study. The number of students who said they were a little bit afraid was 25, representing 16.94 percent of the total student participants. The number of students who said they were neutral about fear of crime on campus was 24, representing 16.16 percent of the total student participants. Likewise, 24 students said they were kind of afraid, also representing 16.16 percent of the participants. 12 students said they were very afraid, representing 9.09 percent of the total student participants. There was only 1 missing response.
Coding of the Data
The study involved analyzing the correlation between two variables, namely: fear and gender. Gender can be either male or female. The Male was coded 1 while the female was coded 2. On the other hand, the variable “fear” had several options: “not afraid” was coded as 1, “little bit afraid” was coded as 2, “neutral” was coded as 3, “kind of afraid” was coded as 4, “very afraid” was coded as 5, and any missing value was coded as 97.
Correlation Analysis
Correlation measures the relationship between two or more variables. The Pearson correlation coefficient ranges from -1 to +1. A negative Pearson correlation coefficient indicates a negative relationship between variables while a positive Pearson correlation coefficient indicates a positive relationship between variables. Two variables are said to be strongly correlated if the correlation coefficient is close to 1 (or -1). Variables are said to be weakly correlated if the correlation coefficient is close to 0. If the correlation coefficient is 1 (or -1), the variables are said to be perfectly correlated. On the other hand, if the correlation coefficient is 0, the variables are said to not correlate at all.
From the correlation analysis results presented in the table above, the Pearson correlation coefficient is 0.0133. This coefficient tells us two things about the nature of the relationship between gender and fear of crime on campus: the magnitude and the direction of the relationship. The magnitude of the relationship is the size of the correlation coefficient, which in this case is 0.0133. This magnitude is small and is closer to zero than it is to one. As a result, we can conclude that there is a weak relationship between gender and fear of crime on campus. The second information provided by the correlation coefficient is the direction of the relationship. In this case, the correlation coefficient is positive, implying that there is a positive relationship between gender and fear of crime on campus. The meaning of this is that fear of crime on campus is higher among female students than among male students.
The figure given below the correlation coefficient is the probability value and helps to determine the statistical significance of the correlation test. In this case, the p-value is 0.8794. Comparing it with the level of significance of 5% (0.05), the p-value is greater than 0.05 and therefore we fail to reject the null hypothesis of no correlation between the two variables. The conclusion is that there is no correlation between gender and the fear of crime on campus.
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