what is meany by type I error?
type 1 error:
means rejecting the null hypothesis(Ho) when it is actually true.
Determine whether the outcome is a Type I error, a Type II error, or a correct decision. A test is made of H0: μ = 67 versus H1: μ ≠ 67. The true value of μ is 68 and H0 is not rejected a)Type II error b)Type I error c)Correct decision
Determine whether the outcome is a Type I error, a Type II error, or a correct decision. A test is made of H0: μ = 40 versus H1: μ ≠ 40. The true value of μ is 40 and H0 is rejected. Group of answer choices Correct decision Type II error Type I error
The term "error" is used two different ways in hypothesis testing: 1) Type I error (or Type II) and 2) standard error. What can a researcher do to influence the size of the standard error? Does this action have any effect on the probability of a Type I error? What can a researcher do to influence the probability of a Type I error? (4 points)
True or False? The probability of a Type I error (a) and Type (II) error (B) are complementary and total to 1. a. True b. False
Q9: Answer the following: a. What is the difference between type I and type Il error? b. What is the deference between dependent and independent variables? C. When should we use ANOVA analysis?
Fill in the following table with the words CORRECT, TYPE I ERROR, and TYPE II ERROR. H0 true H0 false Reject H0 Fail to Reject H0
Which of the following is/are true? Type I and Type II error probabilities are complements Type I and Type II errors cannot both occur in one hypothesis test. Type I and Type II error probabilities are conditional probabilities. At least one of Type I or Type II errors must occur.
6. (5 points) a. What is a Type I error? How can you limit your risk of type Terror? b. What is a Type Il error?
Determine whether the outcome is a Type I error, a Type II error, or a correct decision. a. A test is made of : μ = 7 versus : ? ≥ 7 The true value of μ is 8 and is rejected b. A test is made of : μ = 18 versus : μ ≠ 18. The true value of μ is 18 and is rejected.
statistics 10 (a). Explain type I error and type II error in hypothesis. b) Test the hypothesis using If n=300; x = 75; α= 0.01 left to right problem