Construct the indicated confidence interval for the population mean u using the t-distribution. Assume the population is normally distributed. c = 0.95, x= 12.6, s=3.0, n= 10 (1) (Round to one decimal place as needed.)

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**Confidence Interval Construction Using the t-Distribution**

**Problem Statement:**

Construct the indicated confidence interval for the population mean (μ) using the t-distribution. Assume the population is normally distributed.

- Confidence level (c) = 0.95
- Sample mean (\( \bar{x} \)) = 12.6
- Sample standard deviation (s) = 3.0
- Sample size (n) = 10

**Confidence Interval:**

\[ (\_, \_) \]

**Instructions:**

Round to one decimal place as needed. 

**Understanding Confidence Intervals:**

A confidence interval provides a range of values that is likely to contain the population mean (μ) with a certain level of confidence. When the population standard deviation is unknown and the sample size is small (typically n < 30), the t-distribution is more appropriate than the normal distribution for constructing the interval. Here, we use a 95% confidence level, which means we are 95% confident that the interval calculated from the sample data contains the true population mean. 

To calculate the confidence interval, you would generally follow these steps:

1. Determine the t-score for your confidence level and degrees of freedom (df = n - 1).
2. Calculate the standard error (SE) of the mean: SE = s / √n.
3. Calculate the margin of error (ME): ME = t-score * SE.
4. Determine the confidence interval: ( \( \bar{x} \) - ME, \( \bar{x} \) + ME ).

**Note:** Provide actual values in place of placeholders after computation.
Transcribed Image Text:**Confidence Interval Construction Using the t-Distribution** **Problem Statement:** Construct the indicated confidence interval for the population mean (μ) using the t-distribution. Assume the population is normally distributed. - Confidence level (c) = 0.95 - Sample mean (\( \bar{x} \)) = 12.6 - Sample standard deviation (s) = 3.0 - Sample size (n) = 10 **Confidence Interval:** \[ (\_, \_) \] **Instructions:** Round to one decimal place as needed. **Understanding Confidence Intervals:** A confidence interval provides a range of values that is likely to contain the population mean (μ) with a certain level of confidence. When the population standard deviation is unknown and the sample size is small (typically n < 30), the t-distribution is more appropriate than the normal distribution for constructing the interval. Here, we use a 95% confidence level, which means we are 95% confident that the interval calculated from the sample data contains the true population mean. To calculate the confidence interval, you would generally follow these steps: 1. Determine the t-score for your confidence level and degrees of freedom (df = n - 1). 2. Calculate the standard error (SE) of the mean: SE = s / √n. 3. Calculate the margin of error (ME): ME = t-score * SE. 4. Determine the confidence interval: ( \( \bar{x} \) - ME, \( \bar{x} \) + ME ). **Note:** Provide actual values in place of placeholders after computation.
Expert Solution
Step 1

Since population standard deviation is unknown, Use t-distribution to find t-critical value.

Find the t-critical value:

Refer t-distribution table and look for t value corresponding to degrees of freedom=9 & confidence level of 95%.

Therefore,

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