Lecture_7_Conditions_for_Paramet.pptx - Conditions for Parametric Inference Estimation of Population Mean σ Known • σ can be computed from relevant

# Lecture_7_Conditions_for_Paramet.pptx - Conditions for...

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Conditions for Parametric Inference

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Estimation of Population Mean: σ Known σ can be computed from relevant historical data Practical advice: > plot histogram, normal probability plot > test for normality
Estimation of Population Mean: σ Known Case 1: n ≥ 30 can be safely used Case 2: 15 ≤ n < 30 > If histogram, normal probability plot and normality test show at least a roughly symmetric distribution, can be used for at least 15 data points.

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Estimation of Population Mean: σ Known Case 3: n < 15 > Data should strictly be near normal to use
Example: Healing of skin wounds Biologists studying the healing of skin wounds measured the rate at which new cells closed a razor cut made in the skin of an anesthetized newt. Here are data from 18 newts, measured in micrometers (millionths of a meter) per hour: 29 27 34 40 22 28 14 35 26 35 12 30 23 18 11 22 23 33 Suppose that from past experience with this species of newts we know that the standard deviation of healing rates is σ = 8 micrometers per hour. On the average, what is the healing rate of an anesthetized newt? Give a point estimate and a 95% interval estimate.

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