Alanis Krikorian Analysis 3 11_29 (2)

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Statistics

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Jan 9, 2024

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1. Statistical significance is used to make conclusions about data (Urdan, 2022, 75) and is influenced by sample size (Urdan, 2022, 74). Statistical significance is the probability that a statistic from a sample is because of some random happening in the population where the sample was selected from. It’s important to measure to see if the sample is a good representation of the population or not (Urdan, 2022, 76). It is different from practical significance because practical significance is the subjective determining of the relevance of the statistic in real life. 2. Test statistics, also known as sample statistics, are the values that are calculated during our hypothesis testing. The p-value is the probability of our null hypothesis being true. The p-value is typically expected to be set at .05 to find statistical significance. The P-value is calculated depending on the type of test being done and using sampling distribution for the null hypothesis. 3. Type 1 errors are “false positives”, rejecting the null hypothesis when it’s actually true. Type 2 errors are “false negatives”, failing to reject the null hypothesis when it’s false. For example, when testing drugs, the null hypothesis would be that the drug has no effect, and the alternative would be that the drug is effective. Type 1 error in this case would be saying the drug is effective when it is not. Type 2 error would be saying the drug has no effect when it actually has a positive effect. 4a. This tells me that out of 3,940 total respondents, 1,736 or 44% were male, and 2,204, or 56% were female. There are more women than men in the survey. 4b. Independent: Sex of a person; dependent: Time online, Null Hypothesis: Women and men do not differ in time spent online 4c. We are 95% confident that men who were surveyed spent between 15 and 17 hours on the Internet per week and we are 95% confident that women who were surveyed spent between 13 and 15 hours online per week. We are 95% confident that ALL respondents spend about 15 hours per week online. I used a t-test and found the difference in means as 1.638085 and the p-value as . 0203, smaller than .05, meaning it is statistically significant and we reject the null hypothesis. A p-value smaller than the alpha suggests the observed frequencies are unlikely under the
assumption that the null hypothesis is true. 4d. We can conclude that there is a significant difference in the mean time spent online by women is different from the mean time spent online by men. Although there are more females than males in this survey, we are confident men spend more hours a week online than women. 5a. The percentage of White people who support defunding the police is 29%. The percentage of Black people who support defunding the police is 7%. The percentage of “Other” people who support defunding the police is about 5%. 5b. Independent- Race, Dependent- Rate of supporting defunding the police, Null Hypothesis- Support of defunding the police DOES NOT differ by race 5c. The chi test statistic reported is 78 and the p-value for the chi test is 0 (less than .05) meaning that we reject the null hypothesis. 5d. We can conclude that support support of defunding the police DOES IN FACT differ by race.
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