A retailer wants to see if a red "Sale" sign brings in the same amount of revenue than the same "Sale" sign inblue. The data below shows the revenue in thousands of dollars that was achieved for various days whenthe retailer decided to put the red "Sale" sign up and days when the retailer decided to put the blue "Sale"sign up.Red: 2.6, 2.3, 2.9, 2.9, 1.9, 1.8, 3.8,3.7, 1.6, 3Blue: 2.6, 4, 4.8, 3.8, 2.9, 4.8, 3.7, 5.2, 3.9Assume that both populations follow a normal distribution. What can be concluded at the a = 0.10 levelof significance level of significance?For this study, we should use Select an answera. The null and alternative hypotheses would be:Ho: Select an answerH₁:Select an answer ✓Select an answer ✓Select an answer ✓Select an answer ✓(please enter a decimal)Select an answer (Please enter a decimal)b. The test statistic ? ✓ =c. The p-value =d. The p-value is ? ✓ ae. Based on this, we should | Select an answer the null hypothesis.f. Thus, the final conclusion is that ...(please show your answer to 3 decimal places.)(Please show your answer to 4 decimal places.)The results are statistically significant at a = 0.10, so there is sufficient evidence to concludethat the mean revenue for the ten days with a red "Sale" sign is not the same as the meanrevenue for the nine days with a blue "Sale" sign.The results are statistically significant at a = 0.10, so there is sufficient evidence to concludethat the population mean revenue on days with a red "Sale" sign is not the same as thepopulation mean revenue on days with a blue "Sale" sign.O The results are statistically insignificant at a = 0.10, so there is statistically significantevidence to conclude that the population mean revenue on days with a red "Sale" sign is equalto the population mean revenue on days with a blue "Sale" sign.O The results are statistically insignificant at a = 0.10, so there is insufficient evidence toconclude that the population mean revenue on days with a red "Sale" sign is not the same asthe population mean revenue on days with a blue "Sale" sign. g. Interpret the p-value in the context of the study.O If the sample mean revenue for the 10 days with a red "Sale" sign is the same as the samplemean revenue for the 9 days with a blue "Sale" sign and if another 10 days with a red "Sale"sign and 9 days with a blue "Sale" sign are observed then there would be a 0.3% chance ofconcluding that the mean revenue for the 10 days with a red "Sale" sign differs at least 1.3thousand dollars compared to the mean revenue for the 9 days with a blue "Sale" signO If the population mean revenue on days with a red "Sale" sign is the same as the populationmean revenue on days with a blue "Sale" sign and if another 10 days with a red "Sale" sign and 9days with a blue "Sale" sign are observed then there would be a 0.3% chance that the meanrevenue for the 10 days with a red "Sale" sign would differ by at least 1.3 thousand dollars fromthe mean revenue for the 9 days with a blue "Sale" sign.There is a 0.3% chance that the mean revenue for the 10 days with a red "Sale" sign differs byleast 1.3 thousand dollars compared to the mean revenue for the 9 days with a blue "Sale" sign.O There is a 0.3% chance of a Type I error.h. Interpret the level of significance in the context of the study.There is a 10% chance that there is a difference in the population mean revenue on days with ared "Sale" sign and on days with a blue "Sale" sign.O If the population mean revenue on days with a red "Sale" sign is the same as the populationmean revenue on days with a blue "Sale" sign and if another 10 days with a red "Sale" sign and 9days with a blue "Sale" sign are observed then there would be a 10% chance that we would endup falsely concluding that the population mean revenue for the days with a red "Sale" sign isnot the same as the population mean revenue on days with a blue "Sale" signO There is a 10% chance that green is your favorite color, so why woud you even consider red orblue?O If the population mean revenue on days with a red "Sale" sign is the same as the populationmean revenue on days with a blue "Sale" sign and if another 10 days with a red "Sale" sign and 9days with a blue "Sale" sign are observed, then there would be a 10% chance that we would endup falsely concluding that the sample mean revenue for these 10 days with a red "Sale" signand 9 days with a blue "Sale" sign differ from each other.

Question

A retailer wants to see if a red &#34;Sale&#34; sign brings in the same amount of revenue than the same &#34;Sale&#34; sign inblue. The data below shows the revenue in thousands of dollars that was achieved for various days whenthe retailer decided to put the red &#34;Sale&#34; sign up and days when the retailer decided to put the blue &#34;Sale&#34;sign up.Red: 2.6, 2.3, 2.9, 2.9, 1.9, 1.8, 3.8,3.7, 1.6, 3Blue: 2.6, 4, 4.8, 3.8, 2.9, 4.8, 3.7, 5.2, 3.9Assume that both populations follow a normal distribution. What can be concluded at the a = 0.10 levelof significance level of significance?For this study, we should use Select an answera. The null and alternative hypotheses would be:Ho: Select an answerH₁:Select an answer ✓Select an answer ✓Select an answer ✓Select an answer ✓(please enter a decimal)Select an answer (Please enter a decimal)b. The test statistic ? ✓ =c. The p-value =d. The p-value is ? ✓ ae. Based on this, we should | Select an answer the null hypothesis.f. Thus, the final conclusion is that ...(please show your answer to 3 decimal places.)(Please show your answer to 4 decimal places.)The results are statistically significant at a = 0.10, so there is sufficient evidence to concludethat the mean revenue for the ten days with a red &#34;Sale&#34; sign is not the same as the meanrevenue for the nine days with a blue &#34;Sale&#34; sign.The results are statistically significant at a = 0.10, so there is sufficient evidence to concludethat the population mean revenue on days with a red &#34;Sale&#34; sign is not the same as thepopulation mean revenue on days with a blue &#34;Sale&#34; sign.O The results are statistically insignificant at a = 0.10, so there is statistically significantevidence to conclude that the population mean revenue on days with a red &#34;Sale&#34; sign is equalto the population mean revenue on days with a blue &#34;Sale&#34; sign.O The results are statistically insignificant at a = 0.10, so there is insufficient evidence toconclude that the population mean revenue on days with a red &#34;Sale&#34; sign is not the same asthe population mean revenue on days with a blue &#34;Sale&#34; sign. g. Interpret the p-value in the context of the study.O If the sample mean revenue for the 10 days with a red &#34;Sale&#34; sign is the same as the samplemean revenue for the 9 days with a blue &#34;Sale&#34; sign and if another 10 days with a red &#34;Sale&#34;sign and 9 days with a blue &#34;Sale&#34; sign are observed then there would be a 0.3% chance ofconcluding that the mean revenue for the 10 days with a red &#34;Sale&#34; sign differs at least 1.3thousand dollars compared to the mean revenue for the 9 days with a blue &#34;Sale&#34; signO If the population mean revenue on days with a red &#34;Sale&#34; sign is the same as the populationmean revenue on days with a blue &#34;Sale&#34; sign and if another 10 days with a red &#34;Sale&#34; sign and 9days with a blue &#34;Sale&#34; sign are observed then there would be a 0.3% chance that the meanrevenue for the 10 days with a red &#34;Sale&#34; sign would differ by at least 1.3 thousand dollars fromthe mean revenue for the 9 days with a blue &#34;Sale&#34; sign.There is a 0.3% chance that the mean revenue for the 10 days with a red &#34;Sale&#34; sign differs byleast 1.3 thousand dollars compared to the mean revenue for the 9 days with a blue &#34;Sale&#34; sign.O There is a 0.3% chance of a Type I error.h. Interpret the level of significance in the context of the study.There is a 10% chance that there is a difference in the population mean revenue on days with ared &#34;Sale&#34; sign and on days with a blue &#34;Sale&#34; sign.O If the population mean revenue on days with a red &#34;Sale&#34; sign is the same as the populationmean revenue on days with a blue &#34;Sale&#34; sign and if another 10 days with a red &#34;Sale&#34; sign and 9days with a blue &#34;Sale&#34; sign are observed then there would be a 10% chance that we would endup falsely concluding that the population mean revenue for the days with a red &#34;Sale&#34; sign isnot the same as the population mean revenue on days with a blue &#34;Sale&#34; signO There is a 10% chance that green is your favorite color, so why woud you even consider red orblue?O If the population mean revenue on days with a red &#34;Sale&#34; sign is the same as the populationmean revenue on days with a blue &#34;Sale&#34; sign and if another 10 days with a red &#34;Sale&#34; sign and 9days with a blue &#34;Sale&#34; sign are observed, then there would be a 10% chance that we would endup falsely concluding that the sample mean revenue for these 10 days with a red &#34;Sale&#34; signand 9 days with a blue &#34;Sale&#34; sign differ from each other.

Accepted Answer

by bartleby policy i can gives only 3 subparts answer at a time