When one changes the significance level ofa hypothesis test from 0.10 to 0.05, which of thefollowing will happen? Check all that apply.A. The test becomes less stringent to reject the nullhypothesis (i.e. it becomes easier to reject the nullhypothesis).B. The chance that the null hypothesis is truechanges from 0.10 to 0.05.C. It becomes harder to prove that the nullhypothesis is true.D. The chance of committing a Type II errorchanges from 0.10 to 0.05.E. The chance of committing a Type I error changesfrom 0.10 to 0.05.F. It becomes easier to prove that the nullhypothesis is true.G. The test becomes more stringent to reject thenull hypothesis (i.e., it becomes harder to reject thenull hypothesis).

Here as level of significance is probability of type I error and sample should have p value less…

Answered: When one changes the significance level…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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If a significance test gives p-value 0.005... A.. the effect of interest is practically significant B...We do have good evidence against the null hypothesis C...we do not have good evidence against the null hypothesis D...the null hypothesis is very likely to be true E.. The margin of error is 0.005
Test the claim that the mean GPA of night students is smaller than 2.2 at the 0.025 significance level. The null and alternative hypothesis would be: Ho: 2.2 Ho:p ≤ 0.55 Ho:p≥ 0.55 Ho:p = 0.55 Ho:μ = 2.2 Ho:μ ≤ 2.2 H₁: 0.55 H₁:p 2.2 The test is: two-tailed left-tailed right-tailed Based on a sample of 35 people, the sample mean GPA was 2.15 with a standard deviation of 0.04 The p-value is: Based on this we: O Fail to reject the null hypothesis O Reject the null hypothesis (to 2 decimals)
Which of the following statements below is incorrect about Type II error? The larger the effect size, the smaller the power of the test will be. For a given probability of type I error, the probability of type II error can be reduced by increasing the sample size. The power of a test is equal to 1-3, where represents the probability that a hypothesis test does not reject a false null hypothesis. The effect size measures the distance between the true population proportion and the value assumed for it in the null hypothesis.
Which of the following statements is true regarding the influence of a small alpha level in the context of hypothesis testing? a. A small alpha level reduces the likelihood of a Type I error. b. A small alpha level reduces the effect size. c. A small alpha level increases statistical power. d. A small alpha level increases the likelihood of detecting statistical significance.
Which of the following would be an appropriate null hypothesis? A. The mean age of a sample is equal to 30. B. The mean age of a population is greater than 30. C. The mean age of a population is equal to 30. D. The mean age of a sample is greater than or equal to 30.
Test the claim that the mean GPA of night students is significantly different than 2.6 at the 0.05 significance level. The null and alternative hypothesis would be: Но: д — 2.6 Нo:р 3 0.65 Но: р %—D 0.65 Но:н H:р > 2.6 Н:p#0.65 Hi:p > 0.65 Н:д < 2.6 H:д 2 2.6 H:р<0.65 - 2.6 Ho:µ 2.6 Но:р 0.65 = = The test is: right-tailed left-tailed two-tailed Based on a sample of 65 people, the sample mean GPA was 2.63 with a standard deviation of 0.05 The test statistic i: (to 2 decimals) The positive critical value is: (to 2 decimals) Based on this we: O Fail to reject the null hypothesis O Reject the null hypothesis
It has been reported in the past that the probability that an individual will develop schizophrenia over their lifetime is 0.004. A researcher believes that this proportion has increases since then. She found out that in a random sample of 2500 individuals, 16 developed schizophrenia. Is there evidence to support the claim that the true proportion of people who will develop schizophrenia is greater 0.004? Use hypothesis testing at a = 0.10 level of significance to answer this question. a. State the null and alternative hypotheses. b. What is the probability model (underlying distribution of the sample proportion p)? c. Compute p. d. Compute the test statistic. e. Find the P-value. f. Make the decision whether to reject Ho or not. g. State a conclusion answering the question above. 1
A fellow student tells you the P-value is the probability that the null hypothesis is true, so when the P-value is small, you reject the null hypothesis. Explain why the student is not correct. What would you tell the student about the P-value to help them out? What exactly is the relationship between the P-value and the hypotheses?
Need ASAP. Tyia:) 46. The following describes an alternative hypothesis except?A. It contradicts the null hypothesis.B. It is accepted once the null hypothesis is rejected.C. It states a specific difference between the variables.D. It states that the difference between two variables is not significant.47. Using 0.05 level of significance in testing hypothesis, what is the probability of accepting to commit an error in rejecting the null hypothesis? A. 1%B. 5%C. 95%D. 99% 48. What does level of significance mean in hypothesis testing?A. probability of calculating the hypothesized meanB. probability of not calculating the hypothesized meanC. probability of rejecting the null hypothesis when it is trueD. probability of not rejecting the null hypothesis when it is false
Which one of the following statements is incorrect: A. A type I error consists of rejecting the null hypothesis when it is true B. A type II error consists of accepting the null hypothesis when it is false C. You can control simultaneously both the Type I and Type II error probabilities when the sample size is fixed D. Hypothesis testing and confidence intervals are related concepts
In hypothesis testing, O if the P-value is 0.01, we should conclude there is a 1% chance the null hypothesis is false. O neither the test statistic nor the P-value can ever be negative. O we always begin the hypothesis test by assuming the null hypothesis is true. O if the P-value is 0.99, we should conclude that the null hypothesis is true. O results that are statistically significant will always be practically important (or practically significant).
B. What is the test statistic? z=___ C. What is the P-value? P-value=___ D. What is the null hypothesis, and what do you conclude about it? H0: p≠0.09or H0: p<0.09 or H0: p=0.09 or H0: p >0.09 E. Reject the null hypothesis or Fail to reject the null hypothesis? Why? F. What is the final conclusion?

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