19.How would you interpret a chi-square value that results in p being greater than 0.05? more than one of the statements is true deviations from the expected value are likely explained by chance and therefore the null hypothesis is accepted deviations from the expected value are likely explained by chance and therefore the null hypothesis is rejected deviations from the expected value are likely not explained by chance and therefore the null hypothesis is accepted

A Chi-square analysis is used to test whether the association between two categorical variables is…

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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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In a test of statistical hypotheses, the P-value tells us O the probability of observing a sample mean as we did or something more unusual if the null hypothesis is true. if the null hypothesis is true. if the alternative hypothesis is true. the largest level of significance at which the null hypothesis can be rejected.
The Consumers Risk (B) is defined as a Type II error and occurs when we accept the Null Hypothesis (Ho), when in fact it is false, i.e., we accept bad articles. True or False Plzz explain.
If the p-value is very large (say close to 1), then it is likely that we will reject the null hypothesis. True False
A gambler is trying to decide if a coin is weighted so he flips it 40 times and finds that only 24% turn up heads. From this data, it looks like the coin is weighted to turn up tails more often, but his sample could have been a random chance. Being well-initiated in the practice of statistics he decides to run a hypothesis test.(a) Complete the mathematical statement of the null hypothesis where we are taking to be the proportion of the 40 flips that turn up heads: H0 : p = _______ (b) Complete the mathematical statement of the alternative hypothesis:HA : p __________
1- Type II error occurs when a false null hypothesis is not rejected Select one: True False
In doing a test of statistical significance, you will have made a Type I error if you concludethat there is no difference between means in the population when in fact there is a difference the absence of a difference in the samples is due to chance any difference in the samples is due to chance there is a difference between means in the population when in fact there is no difference
6- The variance of the sum of the random variables equals the sum of the variances if the random variables are uncorrelated. True O False
State if you would retain or reject the null hypothesis 7. p>.05 8. p<.05 9. critical value = + and -1.96, test statistic = -1.98 10. critical value = + 1.65, test statistic = -1.90
2
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?
30. A researcher had originally planned to collect a sample of size 200, and conduct a hypothesis test with a 5% significance level. Now, she has decided instead to collect a sample of size 300, and conduct a hypothesis test with a 1% significance level. How will this change affect the A probabilities of type I and type 2 error? The probability of type 1 error will decrease, and the probability of type 2 error will increase. The probability of both type 1 and type 2 error will decrease. The probability of type 1 error will decrease, but it's impossible to determine whether the probability of type 2 error will increase or decrease. The probability of type 1 error will increase, and the probability of type 2 error will decrease. The probability of type 2 error will decrease, but it's impossible to determine whether the probability of type 1 error will increase or decrease.
If one rejects the null hypothesis at the 5% level, then there is a 5% chance that you made the wrong decision. True /False

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	more than one of the statements is true
	deviations from the expected value are likely explained by chance and therefore the null hypothesis is accepted
	deviations from the expected value are likely explained by chance and therefore the null hypothesis is rejected
	deviations from the expected value are likely not explained by chance and therefore the null hypothesis is accepted