Do shoppers at the mall spend more money on average the day after Thanksgiving compared to the day after Christmas? The 52 randomly surveyed shoppers on the day after Thanksgiving spent an average of $122. Their standard deviation was $29. The 59 randomly surveyed shoppers on the day after Christmas spent an average of $117. Their standard deviation was $35. What can be concluded at the αα = 0.05 level of significance? Based on this, we should the null hypothesis. Thus, the final conclusion is that ... The results are statistically significant at αα = 0.05, so there is sufficient evidence to conclude that the population mean amount of money that day after Thanksgiving shoppers spend is more than the population mean amount of money that day after Christmas shoppers spend. The results are statistically insignificant at αα = 0.05, so there is insufficient evidence to conclude that the population mean amount of money that day after Thanksgiving shoppers spend is more than the population mean amount of money that day after Christmas shoppers spend. The results are statistically significant at αα = 0.05, so there is sufficient evidence to conclude that the mean expenditure for the 52 day after Thanksgiving shoppers that were observed is more than the mean expenditure for the 59 day after Christmas shoppers that were observed. The results are statistically insignificant at αα = 0.05, so there is statistically significant evidence to conclude that the population mean amount of money that day after Thanksgiving shoppers spend is equal to the population mean amount of money that day after Christmas shoppers spend.

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Description: Do shoppers at the mall spend more money on average the day after Thanksgiving compared to the day after Christmas? The 52 randomly surveyed shoppers on the day after Thanksgiving spent an average of $122. Their standard deviation was $29. The 59 ran

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

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Do shoppers at the mall spend more money on average the day after Thanksgiving compared to the day after Christmas? The 52 randomly surveyed shoppers on the day after Thanksgiving spent an average of $122. Their standard deviation was $29. The 59 randomly surveyed shoppers on the day after Christmas spent an average of $117. Their standard deviation was $35. What can be concluded at the αα = 0.05 level of significance?

Based on this, we should the null hypothesis.
Thus, the final conclusion is that ...
- The results are statistically significant at αα = 0.05, so there is sufficient evidence to conclude that the population mean amount of money that day after Thanksgiving shoppers spend is more than the population mean amount of money that day after Christmas shoppers spend.
- The results are statistically insignificant at αα = 0.05, so there is insufficient evidence to conclude that the population mean amount of money that day after Thanksgiving shoppers spend is more than the population mean amount of money that day after Christmas shoppers spend.
- The results are statistically significant at αα = 0.05, so there is sufficient evidence to conclude that the mean expenditure for the 52 day after Thanksgiving shoppers that were observed is more than the mean expenditure for the 59 day after Christmas shoppers that were observed.
- The results are statistically insignificant at αα = 0.05, so there is statistically significant evidence to conclude that the population mean amount of money that day after Thanksgiving shoppers spend is equal to the population mean amount of money that day after Christmas shoppers spend.

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 + ...

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