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A random sample of 43 observations is used to estimate the population variance. The sample mean and sample standard deviation

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Answer #1

ANSWER:

Given that,

Sample size = n = 43

Sample mean = \bar{x} = 68.5

Sample standard deviation = s = 3.1

(a) Construct the 95% interval estimate for the population variance

Degree of freedom = df = n-1 = 43-1 = 42

c = 95% = 95/100 = 0.95

\alpha = 1-c = 1-0.95= 0.05

\alpha/2 = 0.05/2 = 0.025

1 - \alpha /2 = 1 - 0.05/2 = 0.975

Critical values,

>> X1-a/2,df = \chi _{0.975,42}^{2} = 25.99866 and

2 Xa/2,df = \chi _{0.025,42}^{2} = 61.77675

Confidence interval

(n-1)s^{2} / 2 Xa/2,df < \sigma ^{2} < (n-1)s^{2} / >> X1-a/2,df

(43-1)3.1^2 / 61.77675 < \sigma ^{2} < (43-1)3.1^2 / 25.99866 ​

6.5335259624373247 < \sigma ^{2} < 15.5246462702308504

6.5335 < \sigma ^{2} < 15.5246 (Rounded to four decimal place)

Confidence innterval 6.5335 to  15.5246

(b) Construct the 99% interval estimate for the population variance

Degree of freedom = df = n-1 = 43-1 = 42

c = 99% = 99/100 = 0.99

\alpha = 1-c = 1-0.99= 0.01

\alpha/2 = 0.01/2 = 0.005

1 - \alpha /2 = 1 - 0.01/2 = 0.995

Critical values,

>> X1-a/2,df = \chi _{0.995,42}^{2} = 22.13846 and

2 Xa/2,df = \chi _{0.005,42}^{2} = 69.33599

Confidence interval

(n-1)s^{2} / 2 Xa/2,df < \sigma ^{2} < (n-1)s^{2} / >> X1-a/2,df

(43-1)3.1^2 / 69.33599 < \sigma ^{2} < (43-1)3.1^2 / 22.13846 ​

5.8212192542429985 < \sigma ^{2} < 18.2316204469506912

5.8212 < \sigma ^{2} < 18.2316 (Rounded to four decimal place)

Confidence innterval 5.8212   to  18.2316

(c) The width of the interval increases with the confidence interval.

----------------------------------------------------------------------The End ------------------------------------------------------------------------

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