# Lec6 - Quantitative observations Things get a little bit...

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Quantitative observations Things get a little bit more complicated when we move from dichotomous variables to quantitative variables Dichotomous Quantitative p p μ y σ s ˆ Question : “how close to μ is Y likely to be?” where Y is a random variable representing the sample mean. To answer this question we consider the sampling distribution of Y .

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Population Sample 1 Sample 2 Sample 3 Y Y Y Population distribution Sampling distribution Sampling Population Y Y Y Y Y Y Y Y Y Y Y Y Y μ Y σ Y
σ Y = n = 120 4 = 120 2 = 60 Example Sampling common bean ( Phaseolus vulgaris ) seeds. The weights follow a normal distribution with mean μ = 500 mg and standard deviation = 120 mg. A. 480 mg B. 120 mg C. 60 mg D. 30 mg ? 2. have mean Y = = 500 mg 3. have standard deviation Y = ? Suppose we choose four seeds at random, weigh them, and then calculate the mean of the four weights. The distribution of outcomes for this sampling process will: 1. be normal

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Example Sampling common bean ( Phaseolus vulgaris ) seeds. The weights follow a normal distribution with mean μ = 500 mg and standard deviation σ = 120 mg. 2. have mean Y = = 500 mg 3. have standard deviation Y = 60 mg Suppose we choose four seeds at random, weigh them, and then calculate the mean of the four weights.
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## This note was uploaded on 11/04/2009 for the course BIO 50935 taught by Professor Bryant during the Fall '09 term at University of Texas.

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Lec6 - Quantitative observations Things get a little bit...

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