1. Consider testing the hypotheses Ho: p= 0.43 versus Ha: p>0.43. Four possible samplestatistics, along with four possible p-values, are given. Match the statistics to their p-values.A||||p-value = 0.872p-value = 0.586p-value = 0.276p-value = 0.038BA 0.02452. Match each p-value to the most appropriate conclusion.B 0.0036p-value = 0.042p-value = 0.006p-value = 0.084p-value = 0.118CC 0.068210%"The evidence against the null and in favor of the alternative is very strong.""The result is significant at the 5% level but not at the 1% level.""There is really no evidence supporting the alternative hypothesis.""The evidence against the null is significant, but only at the 10% level.'DD 0.36193. For each p-value given, indicate the level(s) at which it would be significant. For each cell ofthe table put either S for "significant" or NS for "not significant".5%991%5. For each p-value, indicate the correct conclusion of the test (either R for "Reject H," or DNRfor "Do not reject H") based on this p-value if we use a 5% significance level.(a) p-value = 0.008(b) p-value = 0.083

Hi there! Thanks for posting the question. As we are entitled to solve one question at a time, I will answer 2nd question, as some information is missing in the first question (sample statistics are missing), please submit other questions one at a time to get them answered. 2) The objective is to match each p-value to the most appropriate conclusion. P-value is the probability of obtaining the test statistic value or a value even more extreme, assuming the null hypothesis H0 is true. If the p-value is less than or equal to the significance level, we reject the null hypothesis and hence we have strong evidence to support the alternative hypothesis. If the p-value is greater than the significance level, we do not reject the null hypothesis and hence there would not be strong evidence to support the alternative hypothesis. A) The p-value is 0.0245 Since this p-value is less than the significance level (0.05) but greater than significance level (0.01), we reject the null hypothesis at 5% significance but cannot reject the null hypothesis at 1% significance. Conclusion: The result is significant at the 5% significance level but not at the 1% significance level. B) The p-value is 0.0036 Since this p-value is too small i.e., less than significance levels (0.05, 0.01, 0.10), we reject the null hypothesis at all three levels of significant. Hence, there would be strong evidence against the null hypothesis and in favor of the alternative hypothesis. Conclusion: The evidence against the null and in favor of the alternative is very strong. C) The p-value is 0.0682 Since this p-value is less than the significance level (0.10) but greater than significance levels (0.01 and 0.05), we reject the null hypothesis at 10% significance only. Conclusion: The evidence against the null is significant, but only at the 10% level. D) The p-value is 0.3619 Since this p-value is greater than all three significance levels (0.01, 0.05, 0.10), we fail to reject the null hypothesis and so there is no evidence to support the alternative hypothesis. Conclusion: There is really no evidence supporting the alternative hypothesis.