Before the furniture store began its ad campaign, it averaged 146 customers per day. The manager is investigating if the average is larger since the ad came out. The data for the 16 randomly selected days since the ad campaign began is shown below: 172, 147, 168, 163, 166, 139, 158, 151, 137, 140, 138, 137, 158, 133, 144, 144 Assuming that the distribution is normal, what can be concluded at the αα = 0.10 level of significance? H0: μ =146 H1 μ > 146 The test statistic t = 1.158 The p-value = 0.1325(Please show your answer to 4 decimal places.) The p-value is > αα Based on this, we should fail to reject accept reject the null hypothesis. (((((This is my question:)))) 3 questions sorry theres some reading Thus, the final conclusion is that ... The data suggest the populaton mean is significantly more than 146 at αα = 0.10, so there is sufficient evidence to conclude that the population mean number of customers since the ad campaign began is more than 146. or The data suggest that the population mean number of customers since the ad campaign began is not significantly more than 146 at αα = 0.10, so there is insufficient evidence to conclude that the population mean number of customers since the ad campaign began is more than 146. or The data suggest the population mean is not significantly more than 146 at αα = 0.10, so there is sufficient evidence to conclude that the population mean number of customers since the ad campaign began is equal to 146. Interpret the p-value in the context of the study: If the population mean number of customers since the ad campaign began is 146 and if you collect data for another 16 days since the ad campaign began then there would be a 13.24750974% chance that the population mean number of customers since the ad campaign began would be greater than 146. or There is a 13.24750974% chance of a Type I error. or There is a 13.24750974% chance that the population mean number of customers since the ad campaign began is greater than 146. or If the population mean number of customers since the ad campaign began is 146 and if you collect data for another 16 days since the ad campaign began then there would be a 13.24750974% chance that the sample mean for these 16 days would be greater than 149.7. or Interpret the level of significance in the context of the study: If the population mean number of customers since the ad campaign began is 146 and if you collect data for another 16 days since the ad campaign began, then there would be a 10% chance that we would end up falsely concuding that the population mean number of customers since the ad campaign began is more than 146. or There is a 10% chance that the population mean number of customers since the ad campaign began is more than 146. There is a 10% chance that there will be no customers since everyone shops online nowadays. or If the population mean number of customers since the ad campaign began is more than 146 and if you collect data for another 16 days since the ad campaign began, then there would be a 10% chance that we would end up falsely concuding that the population mean number of customers since the ad campaign is equal to 146.

Before the furniture store began its ad campaign, it averaged 146 customers per day. The manager is investigating if the average is larger since the ad came out. The data for the 16 randomly selected days since the ad campaign began is shown below: 172, 147, 168, 163, 166, 139, 158, 151, 137, 140, 138, 137, 158, 133, 144, 144 Assuming that the distribution is normal, what can be concluded at the αα = 0.10 level of significance? H0: μ =146 H1 μ > 146 The test statistic t = 1.158 The p-value = 0.1325(Please show your answer to 4 decimal places.) The p-value is > αα Based on this, we should fail to reject accept reject the null hypothesis. (((((This is my question:)))) 3 questions sorry theres some reading Thus, the final conclusion is that ... The data suggest the populaton mean is significantly more than 146 at αα = 0.10, so there is sufficient evidence to conclude that the population mean number of customers since the ad campaign began is more than 146. or The data suggest that the population mean number of customers since the ad campaign began is not significantly more than 146 at αα = 0.10, so there is insufficient evidence to conclude that the population mean number of customers since the ad campaign began is more than 146. or The data suggest the population mean is not significantly more than 146 at αα = 0.10, so there is sufficient evidence to conclude that the population mean number of customers since the ad campaign began is equal to 146. Interpret the p-value in the context of the study: If the population mean number of customers since the ad campaign began is 146 and if you collect data for another 16 days since the ad campaign began then there would be a 13.24750974% chance that the population mean number of customers since the ad campaign began would be greater than 146. or There is a 13.24750974% chance of a Type I error. or There is a 13.24750974% chance that the population mean number of customers since the ad campaign began is greater than 146. or If the population mean number of customers since the ad campaign began is 146 and if you collect data for another 16 days since the ad campaign began then there would be a 13.24750974% chance that the sample mean for these 16 days would be greater than 149.7. or Interpret the level of significance in the context of the study: If the population mean number of customers since the ad campaign began is 146 and if you collect data for another 16 days since the ad campaign began, then there would be a 10% chance that we would end up falsely concuding that the population mean number of customers since the ad campaign began is more than 146. or There is a 10% chance that the population mean number of customers since the ad campaign began is more than 146. There is a 10% chance that there will be no customers since everyone shops online nowadays. or If the population mean number of customers since the ad campaign began is more than 146 and if you collect data for another 16 days since the ad campaign began, then there would be a 10% chance that we would end up falsely concuding that the population mean number of customers since the ad campaign is equal to 146.

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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Question

172, 147, 168, 163, 166, 139, 158, 151, 137, 140, 138, 137, 158, 133, 144, 144

Assuming that the distribution is normal, what can be concluded at the αα = 0.10 level of significance?

H0: μ =146

H1 μ > 146

The test statistic t = 1.158
The p-value = 0.1325(Please show your answer to 4 decimal places.)
The p-value is > αα
Based on this, we should fail to reject accept reject the null hypothesis.

(((((This is my question:)))) 3 questions sorry theres some reading

Thus, the final conclusion is that ...
- The data suggest the populaton mean is significantly more than 146 at αα = 0.10, so there is sufficient evidence to conclude that the population mean number of customers since the ad campaign began is more than 146.
- or
- The data suggest that the population mean number of customers since the ad campaign began is not significantly more than 146 at αα = 0.10, so there is insufficient evidence to conclude that the population mean number of customers since the ad campaign began is more than 146.
- or
- The data suggest the population mean is not significantly more than 146 at αα = 0.10, so there is sufficient evidence to conclude that the population mean number of customers since the ad campaign began is equal to 146.
Interpret the p-value in the context of the study:
- If the population mean number of customers since the ad campaign began is 146 and if you collect data for another 16 days since the ad campaign began then there would be a 13.24750974% chance that the population mean number of customers since the ad campaign began would be greater than 146.
- or
- There is a 13.24750974% chance of a Type I error.
- or
- There is a 13.24750974% chance that the population mean number of customers since the ad campaign began is greater than 146.
- or
- If the population mean number of customers since the ad campaign began is 146 and if you collect data for another 16 days since the ad campaign began then there would be a 13.24750974% chance that the sample mean for these 16 days would be greater than 149.7.
- or
Interpret the level of significance in the context of the study:
- If the population mean number of customers since the ad campaign began is 146 and if you collect data for another 16 days since the ad campaign began, then there would be a 10% chance that we would end up falsely concuding that the population mean number of customers since the ad campaign began is more than 146.
- or
- There is a 10% chance that the population mean number of customers since the ad campaign began is more than 146.
- There is a 10% chance that there will be no customers since everyone shops online nowadays.
- or
- If the population mean number of customers since the ad campaign began is more than 146 and if you collect data for another 16 days since the ad campaign began, then there would be a 10% chance that we would end up falsely concuding that the population mean number of customers since the ad campaign is equal to 146.

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

Expert Solution

Step 1

I checked your work and your calculated test statistic , t , P-value and decision are absolutely correct , Good work!

Conclusion Interpretation :

Here you've decided that fail to reject the null hypotheses it simply means that we are in favor of accepting the null hypotheses.

And in this case our null hypotheses , the population mean number of customers since the ad campaign began is not more than 146.

That is ,the data suggest that the population mean number of customers since the ad campaign began is not significantly more than 146 at α= 0.10, so there is insufficient evidence to conclude that the population mean number of customers since the ad campaign began is more than 146.

Thus , the correct choice is B.

Step 2

Interpret the p-value :

Notice , if the P-value ≤ α , then the null hypothesis is rejected.

And, if the P-value > α , then the null hypothesis is not rejected.

In this case , P-value (0.1325) > α (0.1) so we fail to reject the null hypotheses.

Hence we can say that ,if the population mean number of customers since the ad campaign began is 146 and if you collect data for another 16 days since the ad campaign began then there would be a 13.24750974% chance that the sample mean for these 16 days would be greater than 149.7.

Thus , the correct choice is D.

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