μ = 9.96 σ = 0.05 n = 5 μ = 9.96 \\
σ = 0.05 \\
n = 5 μ = 9.96 σ = 0.05 n = 5
Assumption: the acceptable range of the sample is within +/-1 of the standard deviation.
P ( μ − σ < X < μ + σ ) = P ( ( μ − σ ) − μ σ / n < X − μ σ / n < ( μ − σ ) − μ σ / n ) P(μ - σ < X <μ + σ ) = P( \frac{(μ - σ) - μ }{σ/ \sqrt{n}} < \frac{X - μ }{σ/ \sqrt{n}}< \frac{(μ - σ) - μ }{σ/ \sqrt{n}} ) P ( μ − σ < X < μ + σ ) = P ( σ / n ( μ − σ ) − μ < σ / n X − μ < σ / n ( μ − σ ) − μ )
P ( 9.96 − 0.05 < X < 9.96 + 0.05 ) = P ( ( 9.96 − 0.05 ) − 9.96 0.05 / 5 < X − 9.96 0.05 / 5 < ( 9.96 + 0.05 ) − 9.96 0.05 / 5 ) P ( 9.995 < X < 9.965 ) = P ( − 0.05 0.05 / 5 < X − 9.96 0.05 / 5 < 0.05 0.05 / 5 ) P ( 9.995 < X < 9.965 ) = P ( − 0.4472 < t < 0.4472 ) d f = n − 1 = 5 − 1 = 4 P ( 9.995 < X < 9.965 ) = 2 × P ( 0 < t < 0.4472 ) P ( 9.995 < X < 9.965 ) = 2 × 0.1632 P ( 9.995 < X < 9.965 ) = 0.3264 P( 9.96 - 0.05 < X < 9.96 + 0.05) = P( \frac{( 9.96 - 0.05 ) - 9.96 }{0.05/ \sqrt{5}} < \frac{X - 9.96 }{0.05/ \sqrt{5}} < \frac {( 9.96 + 0.05 ) - 9.96 }{0.05/ \sqrt{5}}) \\
P( 9.995 < X < 9.965 ) = P( \frac{-0.05}{0.05/ \sqrt{5}} < \frac{X - 9.96 }{0.05/ \sqrt{5}} < \frac{0.05 }{0.05/ \sqrt{5}} ) \\
P( 9.995 < X < 9.965 ) = P( -0.4472 < t < 0.4472 ) \\
df = n-1 = 5-1 = 4 \\
P( 9.995 < X < 9.965 ) = 2 \times P( 0 < t < 0.4472 ) \\
P( 9.995 < X < 9.965 ) = 2 \times 0.1632 \\
P( 9.995 < X < 9.965 ) = 0.3264 P ( 9.96 − 0.05 < X < 9.96 + 0.05 ) = P ( 0.05/ 5 ( 9.96 − 0.05 ) − 9.96 < 0.05/ 5 X − 9.96 < 0.05/ 5 ( 9.96 + 0.05 ) − 9.96 ) P ( 9.995 < X < 9.965 ) = P ( 0.05/ 5 − 0.05 < 0.05/ 5 X − 9.96 < 0.05/ 5 0.05 ) P ( 9.995 < X < 9.965 ) = P ( − 0.4472 < t < 0.4472 ) df = n − 1 = 5 − 1 = 4 P ( 9.995 < X < 9.965 ) = 2 × P ( 0 < t < 0.4472 ) P ( 9.995 < X < 9.965 ) = 2 × 0.1632 P ( 9.995 < X < 9.965 ) = 0.3264
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