We saw that if the true population mean is 9.6 points and the sample standard deviation is 3.4 points, then the likelihood of sampling 25 students and getting a sample mean as far away as 10.5 or farther is approximately 20%. Suppose instead that you had sampled 50 students and got the same sample mean and sd. Would you still fail to reject the null hypothesis that the true mean is 9.6 (using a 5% significance level and two-tail hypothesis test)? Complete each step of your hypothesis test in your do file (i.e. don’t use any built-in t-test commands) and enter the answers below.
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The t-stat = abs(`sample_mean’ – `pop_mean’)/`sample_mean_se’. Plugging in values, we get that t = 1.87.
The p-value for a two-sided hypothesis test is 2*(1 – t(`df’, `t_stat’)). Plugging in values, we get p = 0.067.
Since p = 0.067 > 0.05, we fail to reject the null hypothesis that the true population mean is 9.6 using a 5% significance level.
1. What is the t-stat, rounded to the nearest hundredth?
2. What is the p-value, rounded to the nearest thousandth?
3. Which of the following statements is true about this hypothesis test? (Choose all that apply)
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