a. Explain a Type II error and power in context of choosing a smaller level of significance.
b. Explain a Type II error and power in context of a greater difference between the null hypothesis claim and the true value of the population parameter.
a. Explain a Type II error and power in context of choosing a smaller level of significance. b. Explain a Type II error...
Which of the following will increase the power of a significance test? (A) Increase the Type II Error probability (B) Increase the significance level alpha (C) Select a value for the alternative hypothesis closer to the value of the null hypothesis (D) Decrease the sample size. (E) Reject the null hypothesis only if the P-value is smaller than the level of significance.
α is the probability of a Type I error, which occurs when we accept the alternative H1 when the null hypothesis Ho is true. True False A Type II error occurs when when a false null hypothesis is rejected. True False If a null hypothesis is rejected at the 5% significance level but not at the 1% significance level, then the p-value of the test is less than 1%. True False The power of a test is the probability of...
State whether the following statements true or false, and Why? 1. The type I error and type II error are related. A decrease in the probability of one generally results in an increase in the probability of the other. 2. The size of the critical region, and therefore the probability of committing a type I error, can always be reduced by adjusting the critical value(s). 3. An increase in the sample size n will reduce α and β simultaneously. 4....
If you make the significance level smaller (a) the p-value gets smaller (b) the t critical value moves closer to zero (c) the probability of a Type I error increases (d) the probability of a Type II error increases
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. O true false (b) Decreasing the significance level (a) will increase the probability of making a Type 1 Error. false O true (c) Suppose the null hypothesis is u =...
1. Which of the following statements are not generally true? a. A type I error is usually more serious than a type II error. b. A type II error is usually more serious than a type I error. c. A test with significance level is one for which the type I error probability is controlled at the specified level. d. When an experiment and a sample size are fixed, then decreasing the size of the rejection region to obtain...
A type ll error is: O A. the error you make when choosing type Il or type I O B. typically smaller than the type l error. O C. the error you make when not rejecting the null hypothesis when it is false. O D. cannot be calculated when the alternative hypothesis contains an "-".
i need 9 though 15 please and thank you STAT 2480 Chapter 9: Significance Tests About Hypotheses Across 1. In a significance test, the null hypothesis is presumed to unless the data give strong evidence against it. Down 2. The hypothesis is usually a statement of no treatment effect the null hypothesis 3. A Type 1 Error is when we when it is true. 4. When the null hypothesis is rejected because the P- value is less than or equal...
Q6.) A null hypothesis is not rejected at a given level of significance. As the assumed value of the mean gets further away from the true population mean, the Type II error will _____________. A. Increase B. Decrease C. Stay the same D. Randomly fluctuate
12 (a). Explain type I error and type II error in hypothesis. b) Test the hypothesis using H0 : p=0.6 versus H1 : p is greater than 0.6 If n=300; x = 75; α= 0.01