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HenryJY

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  1. Sure I can expound more. However, the paper includes tables and special symbols that can not be displayed in the post. So I will just add my conclusion for people who are interested . Sorry for the inconvenience! According to the P value, we have the following conclusion: P(gender) is greater than a(alpha), so we fail to reject the null hypothesis that the population means of each gender group are equal. There is no significant difference between the mean female score and the mean male score. P(race) is less than a , so we reject the null hypothesis that the population means of each rac
  2. 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 articl
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