Leyla

Social Studies

16 October, 09:43

True or false. Determine if the following statements are true or false, and explain your reasoning. If false, state how it could be corrected. (a) If a given value (for example, the null hypothesized value of a parameter) is within a 95% confidence interval, it will also be within a 99% confidence interval. (b) Decreasing the significance level (↵) will increase the probability of making a Type 1 Error. (c) Suppose the null hypothesis is μ = 5 and we fail to reject H0. Under this scenario, the true population mean is 5. (d) If the alternative hypothesis is true, then the probability of making a Type 2 Error and the power of a test add up to 1. (e) With large sample sizes, even small di↵erences between the null value and the true value of the parameter, a di↵erence often called the e↵ect size, will be identified as statistically significant.