Since the population value of σ is unknown, we want to use the confidence interval for σ unknown. Thus the 1 − α confidence interval is
x ˉ − t α / 2 s n < μ < x ˉ + t α / 2 s n \bar{x}-t_{\alpha/2}\cfrac{s}{\sqrt{n}}<\mu<\bar{x}+t_{\alpha/2}\cfrac{s}{\sqrt{n}} x ˉ − t α /2 n s < μ < x ˉ + t α /2 n s
x ˉ − t α / 2 s n < μ < x ˉ + t α / 2 s n \bar{x}-t_{\alpha/2}\cfrac{s}{\sqrt{n}}<\mu<\bar{x}+t_{\alpha/2}\cfrac{s}{\sqrt{n}} x ˉ − t α /2 n s < μ < x ˉ + t α /2 n s x ˉ − t α / 2 s n < μ < x ˉ + t α / 2 s n \bar{x}-t_{\alpha/2}\cfrac{s}{\sqrt{n}}<\mu<\bar{x}+t_{\alpha/2}\cfrac{s}{\sqrt{n}} x ˉ − t α /2 n s < μ < x ˉ + t α /2 n s
where t α / 2 t_{\alpha/2} t α /2 is the value from the t-distribution table for
P ( T > t α / 2 ) = α / 2. P(T>t_{\alpha/2})=\alpha/2. P ( T > t α /2 ) = α /2.
For a 98% confidence interval we have α = 0.02 and α /2 = 0.01.
Using the table for df = n - 1 = 9 - 1 = 8 (degrees of freedom, n = 9 - the sample size):
t 0.01 ; 8 = 2.896. t_{0.01;8}=2.896. t 0.01 ; 8 = 2.896.
The population sample mean:
x ˉ = ( 1.01 + 0.97 + 1.03 + 1.04 + 0.99 + 0.98 + + 0.99 + 1.01 + 1.03 ) / 9 = 1.0056. \bar{x}=(1.01+0.97+1.03+1.04+0.99+0.98+\\+0.99+1.01+1.03)/9=1.0056. x ˉ = ( 1.01 + 0.97 + 1.03 + 1.04 + 0.99 + 0.98 + + 0.99 + 1.01 + 1.03 ) /9 = 1.0056.
The population variance:
s 2 = ∑ ( x i − x ˉ ) 2 n − 1 = = ( ( 1.01 − 1.0056 ) 2 + ( 0.97 − 1.0056 ) 2 + + ( 1.03 − 1.0056 ) 2 + ( 1.04 − 1.0056 ) 2 + + ( 0.99 − 1.0056 ) 2 + ( 0.98 − 1.0056 ) 2 + + ( 0.99 − 1.0056 ) 2 + ( 1.01 − 1.0056 ) 2 + + ( 1.03 − 1.0056 ) 2 ) / 8 = 0.00060278. s^2=\cfrac{\sum(x_i-\bar x)^2}{n-1}=\\
=((1.01-1.0056)^2+(0.97-1.0056)^2+\\
+(1.03-1.0056)^2+(1.04-1.0056)^2+\\
+(0.99-1.0056)^2+(0.98-1.0056)^2+\\
+(0.99-1.0056)^2+(1.01-1.0056)^2+\\
+(1.03-1.0056)^2)/8=0.00060278. s 2 = n − 1 ∑ ( x i − x ˉ ) 2 = = (( 1.01 − 1.0056 ) 2 + ( 0.97 − 1.0056 ) 2 + + ( 1.03 − 1.0056 ) 2 + ( 1.04 − 1.0056 ) 2 + + ( 0.99 − 1.0056 ) 2 + ( 0.98 − 1.0056 ) 2 + + ( 0.99 − 1.0056 ) 2 + ( 1.01 − 1.0056 ) 2 + + ( 1.03 − 1.0056 ) 2 ) /8 = 0.00060278.
The population standard deviation:
s = 0 , 00060278 = 0.0246. s=\sqrt{0,00060278}=0.0246. s = 0 , 00060278 = 0.0246.
s = 0 , 00060278 = 0.0246. s=\sqrt{0,00060278}=0.0246. s = 0 , 00060278 = 0.0246.
Thus the 98% CI is
1.0056 − 2.896 ⋅ 0.0246 9 < μ < 1.0056 + 2.896 ⋅ 0.0246 9 0.9819 < μ < 1.0293. 1.0056-2.896\cdot\cfrac{0.0246}{\sqrt{9}}<\mu<1.0056+2.896\cdot\cfrac{0.0246}{\sqrt{9}}\\
0.9819<\mu<1.0293. 1.0056 − 2.896 ⋅ 9 0.0246 < μ < 1.0056 + 2.896 ⋅ 9 0.0246 0.9819 < μ < 1.0293.
1.0056 − 2.896 ⋅ 0.0246 9 < μ < 1.0056 + 2.896 ⋅ 0.0246 9 0.9819 < μ < 1.0293. 1.0056-2.896\cdot\cfrac{0.0246}{\sqrt{9}}<\mu<1.0056+2.896\cdot\cfrac{0.0246}{\sqrt{9}}\\
0.9819<\mu<1.0293. 1.0056 − 2.896 ⋅ 9 0.0246 < μ < 1.0056 + 2.896 ⋅ 9 0.0246 0.9819 < μ < 1.0293. 1.0056 − 2.896 ⋅ 0.0246 9 < μ < 1.0056 + 2.896 ⋅ 0.0246 9 0.9819 < μ < 1.0293. 1.0056-2.896\cdot\cfrac{0.0246}{\sqrt{9}}<\mu<1.0056+2.896\cdot\cfrac{0.0246}{\sqrt{9}}\\
0.9819<\mu<1.0293. 1.0056 − 2.896 ⋅ 9 0.0246 < μ < 1.0056 + 2.896 ⋅ 9 0.0246 0.9819 < μ < 1.0293.
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