To solve the given problem, we will follow these steps:
(a) Calculate the sample mean and sample standard deviation for the given data set.
(b) Adjust the data set by adding $4000$ to each salary, then calculate the new sample mean and sample standard deviation.
(c) Adjust the data set by subtracting $4000$ from each salary, then calculate the new sample mean and sample standard deviation.
(d) Analyze the results from (a), (b), and (c) to draw a conclusion about the effect of adding or subtracting a constant on the sample mean and standard deviation.
Given the sample salaries:
\[ \{46, 47, 48, 52, 33, 33, 46, 47, 48, 27, 52, 46, 41\} \]
The sample mean (\(\bar{x}\)) is calculated as:
\[ \bar{x} = \frac{\sum x_i}{n} = \frac{566}{13} \approx 43.5385 \]
The sample standard deviation (\(s\)) is calculated as:
\[ s = \sqrt{\frac{\sum (x_i - \bar{x})^2}{n-1}} \approx 7.7848 \]
Each salary is increased by $4000, resulting in the new data set:
\[ \{50, 51, 52, 56, 37, 37, 50, 51, 52, 31, 56, 50, 45\} \]
The new sample mean (\(\bar{x}_{\text{raise}}\)) is:
\[ \bar{x}_{\text{raise}} = \bar{x} + 4 \approx 47.5385 \]
The new sample standard deviation (\(s_{\text{raise}}\)) remains the same:
\[ s_{\text{raise}} = s \approx 7.7848 \]
Each salary is decreased by $4000, resulting in the new data set:
\[ \{42, 43, 44, 48, 29, 29, 42, 43, 44, 23, 48, 42, 37\} \]
The new sample mean (\(\bar{x}_{\text{cut}}\)) is:
\[ \bar{x}_{\text{cut}} = \bar{x} - 4 \approx 39.5385 \]
The new sample standard deviation (\(s_{\text{cut}}\)) remains the same:
\[ s_{\text{cut}} = s \approx 7.7848 \]