The p-value is greater than the significance level. (a) We can have a Type I error (b) The absolute value of the test st

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The P Value Is Greater Than The Significance Level A We Can Have A Type I Error B The Absolute Value Of The Test St 1 (73.73 KiB) Viewed 30 times

The p-value is greater than the significance level. (a) We can have a Type I error (b) The absolute value of the test statistic is less than the absolute value of the t critical value (c) if we had used a larger value for alpha the p-value would have been smaller (d) We must have had a two tail test Assume the true population mean is 46.8, the t critical value is 1.76, the test statistic is 1.82, and we have HAL > 47. (a) We have a Type II error since we rejected the null hypothesis and it is false (b) We have a correct decision since we rejected the null hypothesis and it is false (c) We have a Type I error since we rejected the null hypothesis and it is true (d) We have a correct decision since we did not reject the null hypothesis and it is true We have a one sample test for the population mean. The significance level is a fixed value. Suppose we increase the sample size. Assume the true mean equals the null mean. (a) The t critical value moves closer to zero. (b) The size of the rejection region decreases (c) The probability of a Type I error decreases (d) The probability of a Type I error increases Suppose the alternative hypothesis is true. (a) The probability the test statistic is in the rejection region is less than alpha. (b) The probability the test statistic is in the rejection region equals alpha. (c) The probability the test statistic is in the rejection region is greater than alpha. (d) None of the above