A quality control manager thinks that there is a higher defective rate on the production line than theadvertised value of p = 0.025. She does a hypothesis test with a significance level of 0.05. Symbolically,the null and alternative hypothesis are as follows: H0: p = 0.025 and Ha: p > 0.025. She calculates ap-value for the hypothesis test of defective light bulbs to be approximately 0.067. Choose the correctinterpretation for the p-value.A) The p-value tells us that the true population rate of defective light bulbs is approximately 0.067.B) The p-value tells us that if the defect rate is 0.025, then the probability that she would observe thepercentage she actually observed or higher is 0.067. At a significance level of 0.05, this would notbe an unusual outcome.C) The p-value tells us that the result is significantly higher than the advertised value using asignificance level of 0.05.D) The p-value tells us that the probability of concluding that the defect rate is equal to 0.025, when infact it is greater than 0.025, is approximately 0.067

A quality control manager believes that there are too many defective light bulbs being produced, higherthan the advertised rate. The manager's null hypothesis is that the production line of light bulbs has adefect rate of p = 0.025 (the light bulb's stated defect rate). He does a hypothesis test with a significancelevel of 0.05. Symbolically, the null and alternative hypothesis are as follows: H0: p = 0.025 and Ha: p >0.025. Choose the statement that best describes the significance level in the context of the hypothesistest.A) The significance level of 0.05 is the defect rate we believe is the true defect rate.B) The significance level of 0.05 is the probability of concluding that the defect rate is equal to 0.025 whenin fact it is greater than 0.025.C) The significance level of 0.05 is the probability of concluding that the defect rate is higher than 0.025when in fact the defect rate is equal to 0.025.D) The significance level of 0.05 is the test statistic that we will use to compare the observed outcome tothe null hypothesis.

Suppose that a major polling organization wanted to test the hypothesis that there was a change in the president’s “approval rating” since last month. Last month, 35% of the representative sample of registered voters approved of the president. For this month, the null hypothesis was that the approval rating equals 35% and the alternative hypothesis is that the approval rating does not equal 35%. The significance level for this test was 0.05.The results of the hypothesis test of the new survey showed a p-value of 0.008.Which of the following statements is correct? Check all that apply. The results were statistically significant. The results were not statistically significant. The null hypothesis should be rejected. The null hypothesis should be accepted. The null hypothesis cannot be rejected.

When the p-value is used for hypothesis testing , the null hypothesis is rejected if Group of answer choicesp value is less than or equal to alphapvalue is greater than alphap value is equal to alphaalpha less than the pvalue

The p-value in hypothesis testing represents which of the following: Group of answer choicesThe probability of failing to reject the null hypothesis, given the observed resultsThe probability that the null hypothesis is true, given the observed resultsThe probability that the observed results are statistically significant, given that the null hypothesis is trueThe probability of observing results as extreme or more extreme than currently observed, given that the null hypothesis is true

For a strong Null hypothesis, what should be the value of P-value?Select an option Clear ResponseP-value must be greater than 0.05P-value must be lesser than 0.05P-value must be equal to 0.05P-value cannot determine the null hypothesis