Before the furniture store began its ad campaign, it averaged 144 customers per day. The manager is investigating if the average has changed since the ad came out. The data for the 14 randomly selected days since the ad campaign began is shown below: 150, 112, 156, 124, 133, 113, 146, 149, 139, 134, 155, 114, 111, 118 Assuming that the distribution is normal, what can be concluded at the αα = 0.01 level of significance? For this study, we should use Select an answer t-test for a population mean z-test for a population proportion The null and alternative hypotheses would be: H0:H0: ? μ p Select an answer ≠ = > < H1:H1: ? p μ Select an answer = < ≠ > The test statistic ? t z = (please show your answer to 3 decimal places.) The p-value = (Please show your answer to 4 decimal places.) The p-value is ? ≤ > αα Based on this, we should Select an answer fail to reject accept reject the null hypothesis. Thus, the final conclusion is that ... The data suggest the populaton mean is significantly different from 144 at αα = 0.01, so there is sufficient evidence to conclude that the population mean number of customers since the ad campaign began is different from 144. The data suggest that the population mean number of customers since the ad campaign began is not significantlydifferent from 144 at αα = 0.01, so there is insufficient evidence to conclude that the population mean number of customers since the ad campaign began is different from 144. The data suggest the population mean is not significantly different from 144 at αα = 0.01, so there is sufficient evidence to conclude that the population mean number of customers since the ad campaign began is equal to 144. Interpret the p-value in the context of the study. There is a 2.42506628% chance of a Type I error. There is a 2.42506628% chance that the population mean number of customers since the ad campaign began is not equal to 144. If the population mean number of customers since the ad campaign began is 144 and if you collect data for another 14 days since the ad campaign began, then there would be a 2.42506628% chance that the population mean would either be less than 132.4 or greater than 155.6. If the population mean number of customers since the ad campaign began is 144 and if you collect data for another 14 days since the ad campaign began, then there would be a 2.42506628% chance that the sample mean for these 14 days would either be less than 132.4 or greater than 155.6. Interpret the level of significance in the context of the study. If the population mean number of customers since the ad campaign began is 144 and if you collect data for another 14 days since the ad campaign began, then there would be a 1% chance that we would end up falsely concuding that the population mean number of customers since the ad campaign began is different from 144. There is a 1% chance that the population mean number of customers since the ad campaign began is different from 144. There is a 1% chance that there will be no customers since everyone shops online nowadays. If the population mean number of customers since the ad campaign began is different from 144 and if you collect data for another 14 days since the ad campaign began, then there would be a 1% chance that we would end up falsely concuding that the population mean number of customers since the ad campaign is equal to 144.

Before the furniture store began its ad campaign, it averaged 144 customers per day. The manager is investigating if the average has changed since the ad came out. The data for the 14 randomly selected days since the ad campaign began is shown below: 150, 112, 156, 124, 133, 113, 146, 149, 139, 134, 155, 114, 111, 118 Assuming that the distribution is normal, what can be concluded at the αα = 0.01 level of significance? For this study, we should use Select an answer t-test for a population mean z-test for a population proportion The null and alternative hypotheses would be: H0:H0: ? μ p Select an answer ≠ = > < H1:H1: ? p μ Select an answer = < ≠ > The test statistic ? t z = (please show your answer to 3 decimal places.) The p-value = (Please show your answer to 4 decimal places.) The p-value is ? ≤ > αα Based on this, we should Select an answer fail to reject accept reject the null hypothesis. Thus, the final conclusion is that ... The data suggest the populaton mean is significantly different from 144 at αα = 0.01, so there is sufficient evidence to conclude that the population mean number of customers since the ad campaign began is different from 144. The data suggest that the population mean number of customers since the ad campaign began is not significantlydifferent from 144 at αα = 0.01, so there is insufficient evidence to conclude that the population mean number of customers since the ad campaign began is different from 144. The data suggest the population mean is not significantly different from 144 at αα = 0.01, so there is sufficient evidence to conclude that the population mean number of customers since the ad campaign began is equal to 144. Interpret the p-value in the context of the study. There is a 2.42506628% chance of a Type I error. There is a 2.42506628% chance that the population mean number of customers since the ad campaign began is not equal to 144. If the population mean number of customers since the ad campaign began is 144 and if you collect data for another 14 days since the ad campaign began, then there would be a 2.42506628% chance that the population mean would either be less than 132.4 or greater than 155.6. If the population mean number of customers since the ad campaign began is 144 and if you collect data for another 14 days since the ad campaign began, then there would be a 2.42506628% chance that the sample mean for these 14 days would either be less than 132.4 or greater than 155.6. Interpret the level of significance in the context of the study. If the population mean number of customers since the ad campaign began is 144 and if you collect data for another 14 days since the ad campaign began, then there would be a 1% chance that we would end up falsely concuding that the population mean number of customers since the ad campaign began is different from 144. There is a 1% chance that the population mean number of customers since the ad campaign began is different from 144. There is a 1% chance that there will be no customers since everyone shops online nowadays. If the population mean number of customers since the ad campaign began is different from 144 and if you collect data for another 14 days since the ad campaign began, then there would be a 1% chance that we would end up falsely concuding that the population mean number of customers since the ad campaign is equal to 144.

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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150, 112, 156, 124, 133, 113, 146, 149, 139, 134, 155, 114, 111, 118

Assuming that the distribution is normal, what can be concluded at the αα = 0.01 level of significance?

For this study, we should use Select an answer t-test for a population mean z-test for a population proportion
The null and alternative hypotheses would be:

H0:H0: ? μ p Select an answer ≠ = > <

H1:H1: ? p μ Select an answer = < ≠ >

The test statistic ? t z = (please show your answer to 3 decimal places.)
The p-value = (Please show your answer to 4 decimal places.)
The p-value is ? ≤ > αα
Based on this, we should Select an answer fail to reject accept reject the null hypothesis.
Thus, the final conclusion is that ...
- The data suggest the populaton mean is significantly different from 144 at αα = 0.01, so there is sufficient evidence to conclude that the population mean number of customers since the ad campaign began is different from 144.
- The data suggest that the population mean number of customers since the ad campaign began is not significantlydifferent from 144 at αα = 0.01, so there is insufficient evidence to conclude that the population mean number of customers since the ad campaign began is different from 144.
- The data suggest the population mean is not significantly different from 144 at αα = 0.01, so there is sufficient evidence to conclude that the population mean number of customers since the ad campaign began is equal to 144.
Interpret the p-value in the context of the study.
- There is a 2.42506628% chance of a Type I error.
- There is a 2.42506628% chance that the population mean number of customers since the ad campaign began is not equal to 144.
- If the population mean number of customers since the ad campaign began is 144 and if you collect data for another 14 days since the ad campaign began, then there would be a 2.42506628% chance that the population mean would either be less than 132.4 or greater than 155.6.
- If the population mean number of customers since the ad campaign began is 144 and if you collect data for another 14 days since the ad campaign began, then there would be a 2.42506628% chance that the sample mean for these 14 days would either be less than 132.4 or greater than 155.6.
Interpret the level of significance in the context of the study.
- If the population mean number of customers since the ad campaign began is 144 and if you collect data for another 14 days since the ad campaign began, then there would be a 1% chance that we would end up falsely concuding that the population mean number of customers since the ad campaign began is different from 144.
- There is a 1% chance that the population mean number of customers since the ad campaign began is different from 144.
- There is a 1% chance that there will be no customers since everyone shops online nowadays.
- If the population mean number of customers since the ad campaign began is different from 144 and if you collect data for another 14 days since the ad campaign began, then there would be a 1% chance that we would end up falsely concuding that the population mean number of customers since the ad campaign is equal to 144.

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