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A sample of size [tex]n=14[/tex] has a sample mean [tex]\bar{x}=8.5[/tex] and sample standard deviation [tex]s=2.6[/tex]. Construct a [tex]95\%[/tex] confidence interval for the population mean [tex]\mu[/tex].

A. [tex]8.1 \ \textless \ \mu \ \textless \ 8.9[/tex]
B. [tex]7.6 \ \textless \ \mu \ \textless \ 9.4[/tex]
C. [tex]7.3 \ \textless \ \mu \ \textless \ 9.7[/tex]
D. [tex]7.0 \ \textless \ \mu \ \textless \ 10.0[/tex]


Sagot :

To construct a 95% confidence interval for the population mean [tex]\(\mu\)[/tex] given a sample, we need to follow these steps:

1. Identify Given Information:
- Sample size ([tex]\(n\)[/tex]) = 14
- Sample mean ([tex]\(\bar{x}\)[/tex]) = 8.5
- Sample standard deviation ([tex]\(s\)[/tex]) = 2.6
- Confidence level = 95%

2. Determine the t-critical value:
- Since the sample size is small (less than 30), we use the t-distribution.
- Degrees of freedom ([tex]\(df\)[/tex]) = [tex]\(n - 1 = 14 - 1 = 13\)[/tex].
- For a 95% confidence level, we look up the t-critical value ([tex]\(t^*\)[/tex]) corresponding to [tex]\(\frac{0.95 + 1}{2} = 0.975\)[/tex] in the t-distribution table for [tex]\(df = 13\)[/tex].
- This value is approximately 2.160.

3. Calculate the Standard Error of the Mean (SEM):
[tex]\[ \text{SEM} = \frac{s}{\sqrt{n}} = \frac{2.6}{\sqrt{14}} \approx 0.695 \][/tex]

4. Calculate the Margin of Error (ME):
[tex]\[ \text{ME} = t^* \times \text{SEM} = 2.160 \times 0.695 \approx 1.501 \][/tex]

5. Construct the Confidence Interval:
- Lower limit:
[tex]\[ \bar{x} - \text{ME} = 8.5 - 1.501 \approx 6.999 \][/tex]
- Upper limit:
[tex]\[ \bar{x} + \text{ME} = 8.5 + 1.501 \approx 10.001 \][/tex]

Therefore, the 95% confidence interval for the population mean [tex]\(\mu\)[/tex] is approximately:
[tex]\[ 6.9988 < \mu < 10.0012 \][/tex]

Comparing with the options provided, the closest interval is:
[tex]\[ \boxed{7.0 < \mu < 10.0} \][/tex]