A machine produces cylindrical metal pieces. A sample of pieces is taken, and the diameter are found to be 1.01, 0.97, 1.03, 1.04, 0.99, 0.98, 0.99, 1.01 and 1.03 cm. Find the t-value for a 98% confidence interval for the diameters of the cylindrical metal pieces. Assume that the diameters are approximately normally distributed.
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
"\\bar{x}-t_{\\alpha\/2}\\cfrac{s}{\\sqrt{n}}<\\mu<\\bar{x}+t_{\\alpha\/2}\\cfrac{s}{\\sqrt{n}}"
"\\bar{x}-t_{\\alpha\/2}\\cfrac{s}{\\sqrt{n}}<\\mu<\\bar{x}+t_{\\alpha\/2}\\cfrac{s}{\\sqrt{n}}""\\bar{x}-t_{\\alpha\/2}\\cfrac{s}{\\sqrt{n}}<\\mu<\\bar{x}+t_{\\alpha\/2}\\cfrac{s}{\\sqrt{n}}"
where "t_{\\alpha\/2}" is the value from the t-distribution table for
"P(T>t_{\\alpha\/2})=\\alpha\/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."
The population sample mean:
"\\bar{x}=(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=\\cfrac{\\sum(x_i-\\bar x)^2}{n-1}=\\\\\n=((1.01-1.0056)^2+(0.97-1.0056)^2+\\\\\n+(1.03-1.0056)^2+(1.04-1.0056)^2+\\\\\n+(0.99-1.0056)^2+(0.98-1.0056)^2+\\\\\n+(0.99-1.0056)^2+(1.01-1.0056)^2+\\\\\n+(1.03-1.0056)^2)\/8=0.00060278."
The population standard deviation:
"s=\\sqrt{0,00060278}=0.0246."
"s=\\sqrt{0,00060278}=0.0246."
Thus the 98% CI is
"1.0056-2.896\\cdot\\cfrac{0.0246}{\\sqrt{9}}<\\mu<1.0056+2.896\\cdot\\cfrac{0.0246}{\\sqrt{9}}\\\\\n0.9819<\\mu<1.0293."
"1.0056-2.896\\cdot\\cfrac{0.0246}{\\sqrt{9}}<\\mu<1.0056+2.896\\cdot\\cfrac{0.0246}{\\sqrt{9}}\\\\\n0.9819<\\mu<1.0293.""1.0056-2.896\\cdot\\cfrac{0.0246}{\\sqrt{9}}<\\mu<1.0056+2.896\\cdot\\cfrac{0.0246}{\\sqrt{9}}\\\\\n0.9819<\\mu<1.0293."
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