In this paper, I used two-way ANOVA (analysis of variance) to explore whether gender and race would influence student’s academic performance in some special majors. To be more specific, I would like to know how students perform when they are studying computer science. I used two-way ANOVA to test the null hypothesis and use the F value to find the answer to the question. Data was collected based on the survey sent out by me.

When I was reading articles related to Statistics, I found a really interesting one. Randy Olson is an author who wrote several controversial gender-related articles. In his article, “Average IQ of Students by College Major and Gender ratio”, he gave a really interesting plot. What the plot demonstrates is that if one major has lower female student ratio, the average IQ of students will be higher. Those so-called male-dominated majors (for instance, physics, astronomy, computer science) tend to have higher average IQ. However, the estimate of IQ was based on SAT scores, which, in my point of view, was not representative and even misleading. I was really curious about the relationship between the academic performance and gender. In addition to gender, I was also interested in knowing how the races influenced the academic performance. It is widely accepted that in the field of computer science, many minority groups are underrepresented. How does the combination of gender and race influence students’ performance when studying computer science? In this paper, I want to explore how the gender and race factors influence students’ academic performance in the field of Computer Science.

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