**Understanding Hypothesis Testing: Key Concepts****1. Interpreting the Null Hypothesis (H0)**When analyzing hypothesis tests, interpreting the results often involves understanding whether to reject or fail to reject the null hypothesis. Here are key conclusions when the null hypothesis is rejected:- **A. Alternative Hypothesis Validity:** - If the null hypothesis is rejected, there is sufficient statistical evidence to infer that the alternative hypothesis is true.- **B. Insufficient Evidence for Alternative:** - This conclusion states there is not enough statistical evidence to infer the alternative hypothesis is true, but is incorrect if the null hypothesis is rejected.- **C. Statistical Significance:** - Incorrect in this context, as rejecting H0 indicates statistical significance.- **D. Evidence for Null Hypothesis:** - Incorrect conclusion if H0 is rejected, indicating a lack of support for the null hypothesis being true.**2. p-value Interpretation in Hypothesis Testing**The p-value assists in determining the strength of evidence against the null hypothesis. In a given hypothesis test scenario:- The null hypothesis can be rejected at the 0.10 and 0.05 levels of significance but not at the 0.01 level. Therefore, the most accurate statement about the p-value is: - **A. 0.01 < p-value < 0.05:** - Indicates the rejection of H0 at 0.05 but not at the more stringent 0.01 level.- Other Options: - **B. 0.05 < p-value < 0.10** - **C. p-value = 0.01** - **D. p-value = 0.10**These concepts are crucial in understanding how statistical evidence influences the acceptance or rejection of hypotheses in data analysis and research.

The null hypothesis is rejected.

Answered: IT we reject the huil hypothesis, we c…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Determine the critical value, zo, to test the claim about the population proportion p20.132 given n= 48 and p 0.110. Use a=0.05. O A. - 1.645 OB. -1.96 C. - 2.575 O D. -2.33 Click to select your answer. Dec 04, 2009 Compute the value of the test statistic? | Yahoo Answers 0 0 9 G Type here to search
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-Find the correct null hypothesis and for each correct alternative hypothesis 3. Suppose you hear a claim that the average score on a national exam is 78. You think the average is higher than that. Set up your null and alternative hypotheses.
If we reject the null hypothesis when testing to see if a certain treatment has an effect, it means the treatment does have an effect. True False
A college professor states that this year's entering students appear to be smarter than entering students from previous years. The college's records indicate that the mean IQ for entering students from earlier years is 110.4. Suppose that we want to sample a small number of this year's entering students and carry out a hypothesis test to see if the professor's statement can be supported. State the null hypothesis H0 and the alternative hypothesis H1 that we would use for this test. H0= H1=
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Select the appropriate null and alternative hypothesis for the following research question: People who see therapists have lower depression scores than people who do not see therapists? xbar1 = the average depression score for people who see a therapist xbar2 = the average depression score for people who do not see a therapist O Null Hypothesis: People who see a therapist have depression scores lower than or equal to people who do not see a therapist i.e. xbar1 xbar2 O Null Hypothesis: People who see a therapist have depression scores higher than or equal to people who do not see a therapist i.e. xbar1 >= xbar2 Alternative Hypothesis: People who see a therapist have depression scores lower than people who do not see a therapist i.e. xbar1 < xbar2
We are comparing two samples during a hypothesis test. Sample A has a z-test statistic of 1.58 and sample B has a z-test statistic of -0.34. We can say then that... If H-naught is true, then Sample B has a higher probability of occurring while Sample A has a lower probability of occurring. If H-naught is true, then Sample A has a higher probability of occurring while Sample B has a lower probability of occurring. We reject the null hypothesis. If H-naught is rejected, then Sample A has a higher probability of occurring while Sample B has a lower probability of occurring.
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