A random sample of 25 office workers was selected to determine how much the average person spends weekly on groceries. The sample mean was equal to $260, with a sample standard deviation of $8. What is the 95 percent confidence interval of this sample? Round the answer to the nearest hundredth

1 answer

To calculate the 95% confidence interval for the mean spending on groceries, we can use the formula for the confidence interval based on the sample mean, sample standard deviation, and the t-distribution (since the sample size is small, n < 30).

The formula for the confidence interval is:

\[ CI = \bar{x} \pm t^* \left( \frac{s}{\sqrt{n}} \right) \]

Where:

  • \(\bar{x}\) = sample mean
  • \(t^*\) = t-value from the t-distribution table corresponding to the desired confidence level and degrees of freedom
  • \(s\) = sample standard deviation
  • \(n\) = sample size

Given values:

  • Sample mean (\(\bar{x}\)) = $260
  • Sample standard deviation (\(s\)) = $8
  • Sample size (\(n\)) = 25

Step 1: Calculate degrees of freedom

Degrees of freedom (df) = \(n - 1 = 25 - 1 = 24\)

Step 2: Find the t-value

For a 95% confidence interval and 24 degrees of freedom, the critical t-value (using a t-table or calculator) is approximately \(t^* \approx 2.064\).

Step 3: Calculate the standard error (SE)

\[ SE = \frac{s}{\sqrt{n}} = \frac{8}{\sqrt{25}} = \frac{8}{5} = 1.6 \]

Step 4: Calculate the margin of error (ME)

\[ ME = t^* \times SE = 2.064 \times 1.6 \approx 3.3024 \]

Step 5: Calculate the confidence interval

\[ CI = \bar{x} \pm ME = 260 \pm 3.3024 \]

Calculating the lower and upper bounds:

  • Lower bound: \(260 - 3.3024 \approx 256.70\)
  • Upper bound: \(260 + 3.3024 \approx 263.30\)

Final Result

The 95% confidence interval for the average amount spent weekly on groceries is approximately:

\[ \boxed{(256.70, 263.30)} \]