Explain “Type II Error” (β) in hypothesis testing.
A type II error refers to non-rejection of false null hypothesis i.e, does not reject null hypothesis, even though alternative hypothesis is true state of nature. Or we accept the null hypothesis even when it is false i.e., this error produces a false positive and false finding is accepted true. This error rejects alternative hypothesis, even when it does not occur out of chance. This confirms idea which should be rejected, claiming two observances are same, even when they are different.
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
A Type II error occurs in hypothesis testing when we _____________________________. fail to reject the null hypothesis and the null hypothesis is not true reject the null hypothesis and the null hypothesis is true fail to reject the alternative hypothesis and the alternative hypothesis is not true reject the alternative hypothesis and the alternative hypothesis is true
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
1. True or False? In hypothesis testing analysis, a type II error occurs if the null hypothesis H0 is accepted when it is true. 2. True or False? When population is not normal, sampling distribution of ¯x , for a large sample size is normally distributed, irrespective of the shape of the population.
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)
Question 1 1 pts In classical hypothesis testing, what happens to the probability of Type II Error as we increase the significance level of the test (a)? P(Type II Error) Decreases P(Type II Error) Increases P(Type II Error) Stays the Same
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.
6. Which of the following statements about hypothesis testing are true? • A type I error occurs if H, is rejected when it is true. • A type II error occurs if He is rejected when it is true. • The power of a test is the probability of failing to reject H, when it is false.
6. Which of the following statements about hypothesis testing are true? • A type I error occurs if His rejected when it is true. • A type II error occurs if H, is reject ed when it is true, • The power of a test is the probability of failing to reject H, when it is false,
Discuss what is meant by Type I and Type II errors in hypothesis testing.