You randomly select 16 coffee shops and measure the temperature of the coffee sold at each. The sample mean temperature is 170.0 degrees with a sample standard deviation of 10 degrees. Construct a 99% confidence interval for the population mean temperature. Assume the temperatures are approximately normally distributed. x-bar std dev Confidence Level Margin of Error Point Estimate |round off to 1 decimal place round off to 1 decimal place Lower Limit Upper Limit Interpret the confidence interval in context of the problem

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### Confidence Interval Calculation for Coffee Temperature

#### Problem Statement
You randomly select 16 coffee shops and measure the temperature of the coffee sold at each. The sample mean temperature is 170.0 degrees with a sample standard deviation of 10 degrees. Construct a 99% confidence interval for the population mean temperature. Assume the temperatures are approximately normally distributed.

#### Parameters Given:
- **Sample mean (x-bar):** 170.0 degrees
- **Sample standard deviation (std dev):** 10 degrees
- **Sample size (n):** 16
- **Confidence Level:** 99%

#### Steps to Calculate the Confidence Interval

1. **Point Estimate:**
   The point estimate for the population mean is the sample mean.
   \[ \text{Point Estimate} = \bar{x} = 170.0 \]

2. **Margin of Error:**
   The margin of error (E) is calculated using the formula:
   \[ E = t_{\alpha/2} \cdot \frac{s}{\sqrt{n}} \]
   Where:
   - \( t_{\alpha/2} \) is the t-score corresponding to the 99% confidence level for degrees of freedom (df = n - 1).
   - \( s \) is the sample standard deviation.
   - \( n \) is the sample size.
   
3. **Lower and Upper Limits:**
   \[ \text{Lower Limit} = \bar{x} - E \]
   \[ \text{Upper Limit} = \bar{x} + E \]

#### Calculations:
(includes standard t-table lookup or software tools to get \( t_{\alpha/2} \))

Assuming \( t_{\alpha/2} \approx 2.947 \) for a 99% confidence interval with 15 degrees of freedom,

\[ E = 2.947 \cdot \frac{10}{\sqrt{16}} \approx 2.947 \cdot 2.5 = 7.3675 \]

Thus,

\[ \text{Lower Limit} = 170.0 - 7.4 \approx 162.6 \]
\[ \text{Upper Limit} = 170.0 + 7.4 \approx 177.4 \]

#### Summary:
The 99% confidence interval for the population mean temperature is \([162.6, 177.4]\
Transcribed Image Text:### Confidence Interval Calculation for Coffee Temperature #### Problem Statement You randomly select 16 coffee shops and measure the temperature of the coffee sold at each. The sample mean temperature is 170.0 degrees with a sample standard deviation of 10 degrees. Construct a 99% confidence interval for the population mean temperature. Assume the temperatures are approximately normally distributed. #### Parameters Given: - **Sample mean (x-bar):** 170.0 degrees - **Sample standard deviation (std dev):** 10 degrees - **Sample size (n):** 16 - **Confidence Level:** 99% #### Steps to Calculate the Confidence Interval 1. **Point Estimate:** The point estimate for the population mean is the sample mean. \[ \text{Point Estimate} = \bar{x} = 170.0 \] 2. **Margin of Error:** The margin of error (E) is calculated using the formula: \[ E = t_{\alpha/2} \cdot \frac{s}{\sqrt{n}} \] Where: - \( t_{\alpha/2} \) is the t-score corresponding to the 99% confidence level for degrees of freedom (df = n - 1). - \( s \) is the sample standard deviation. - \( n \) is the sample size. 3. **Lower and Upper Limits:** \[ \text{Lower Limit} = \bar{x} - E \] \[ \text{Upper Limit} = \bar{x} + E \] #### Calculations: (includes standard t-table lookup or software tools to get \( t_{\alpha/2} \)) Assuming \( t_{\alpha/2} \approx 2.947 \) for a 99% confidence interval with 15 degrees of freedom, \[ E = 2.947 \cdot \frac{10}{\sqrt{16}} \approx 2.947 \cdot 2.5 = 7.3675 \] Thus, \[ \text{Lower Limit} = 170.0 - 7.4 \approx 162.6 \] \[ \text{Upper Limit} = 170.0 + 7.4 \approx 177.4 \] #### Summary: The 99% confidence interval for the population mean temperature is \([162.6, 177.4]\
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