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

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### 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
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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