A sales manager for a large department store believes that customer spending per visit with a sale is lower than customer spending without a sale, and would like to test that claim. A simple random sample of customer spen taken from without a sale and with a sale. The results are shown below. Without sale With sale
A sales manager for a large department store believes that customer spending per visit with a sale is lower than customer spending without a sale, and would like to test that claim. A simple random sample of customer spen taken from without a sale and with a sale. The results are shown below. Without sale With sale
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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Transcribed Image Text:### Investigating Customer Spending with and without a Sale
A sales manager for a large department store believes that customer spending per visit with a sale is lower than customer spending without a sale and would like to test that claim. A simple random sample of customer spending is taken from without a sale and with a sale. The results are shown below.
#### Statistical Summary:
| Statistic Description | Without Sale | With Sale |
|-------------------------------------------------|--------------|-----------|
| Mean | 82.904 | 71.316 |
| Variance | 1984.96 | 1826.41 |
| Observations | 200 | 150 |
| Hypothesized Mean Difference | 0 | |
| Degrees of Freedom (df) | 328 | |
| t Stat | -2.465 | |
| P(T <= t) one-tail | 0.0071 | |
| t Critical one-tail | -1.65 | |
| P(T <= t) two-tail | 0.0142 | |
| t Critical two-tail | -1.967 | |
| Confidence Level | 99% | |
#### Explanation of the Data:
- **Mean**: Average customer spending.
- **Variance**: Measure of the spread between numbers in the data set.
- **Observations**: Number of customers sampled.
- **Hypothesized Mean Difference**: The expected difference in means under the null hypothesis.
- **Degrees of Freedom (df)**: The number of independent values that can vary in the calculation.
- **t Stat**: The calculated t-statistic value.
- **P(T <= t) one-tail**: The p-value for the one-tail hypothesis.
- **t Critical one-tail**: The threshold t-value for a one-tail test at the 99% confidence level.
- **P(T <= t) two-tail**: The p-value for the two-tail hypothesis.
- **t Critical two-tail**: The threshold t-value for a two-tail test at the 99% confidence level.
#### Graphical Representation:
- The graph displayed is a standard normal distribution curve with labeled t-score axis ranging from -3 to 3.
- The p-value (probability value) and the t-value (t-statistic) are to be inserted into separate fields indicated next
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