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... standard deviation of 1.623 mg/100g. The normal probability plot for this data is shown to the right, indicating reasonable grounds ...
... standard deviation of 1.623 mg/100g. The normal probability plot for this data is shown to the right, indicating reasonable grounds ...
Concepts for Week 1
... deviations, you need to know the mean to estimate (x - x); if you have only one observation then x will equal x, so there can be no deviation from the mean - there are no degrees of freedom for variation; for two observation, (x1 - x) and (x2 - x) will be equal and opposite, so there is only one ind ...
... deviations, you need to know the mean to estimate (x - x); if you have only one observation then x will equal x, so there can be no deviation from the mean - there are no degrees of freedom for variation; for two observation, (x1 - x) and (x2 - x) will be equal and opposite, so there is only one ind ...
Sample Statistics
... Mean: a measure of central tendency Variance, Deviation: measures of dispersion about the mean The sample standard deviation has the same "units" as the data and the sample mean. For example, if the data has units of sec then so also does the sample mean and standard deviation. Although the sample v ...
... Mean: a measure of central tendency Variance, Deviation: measures of dispersion about the mean The sample standard deviation has the same "units" as the data and the sample mean. For example, if the data has units of sec then so also does the sample mean and standard deviation. Although the sample v ...
Example
... The assumption that we sample from a normal population is important for small n but not for large n. Properties of the t-distribution 1. continuous and symmetric about 0 2. more variable and slightly different shape than the standard normal 3. As n becomes large, the t distribution can be approxima ...
... The assumption that we sample from a normal population is important for small n but not for large n. Properties of the t-distribution 1. continuous and symmetric about 0 2. more variable and slightly different shape than the standard normal 3. As n becomes large, the t distribution can be approxima ...
H - Cengage Learning
... • For Ha: μ < μ0, the p-value is P(Z < z0). • For Ha: μ > μ0, the p-value is P(Z > z0). • For Ha: μ ≠ μ0, we must consider both tails of the standard normal distribution and the p-value is 2 • P(Z > |z0|). ...
... • For Ha: μ < μ0, the p-value is P(Z < z0). • For Ha: μ > μ0, the p-value is P(Z > z0). • For Ha: μ ≠ μ0, we must consider both tails of the standard normal distribution and the p-value is 2 • P(Z > |z0|). ...
Confidence Intervals for the Mean
... • Suppose we want to estimate the unknown mean height of male students at NC State with a confidence interval. • We want to be 95% confident that our estimate is within .5 inch of • How large does our sample size need to be? ...
... • Suppose we want to estimate the unknown mean height of male students at NC State with a confidence interval. • We want to be 95% confident that our estimate is within .5 inch of • How large does our sample size need to be? ...
Tests for Two Means in a Multicenter Randomized Design
... are independent. The authors make the simplifying assumption that the sample size from all centers are equal to 2n and that the number of subjects assign to each treatment is the same. Thus the total sample size N is 2Qn. Note that the authors conduct a number of simulation studies and conclude that ...
... are independent. The authors make the simplifying assumption that the sample size from all centers are equal to 2n and that the number of subjects assign to each treatment is the same. Thus the total sample size N is 2Qn. Note that the authors conduct a number of simulation studies and conclude that ...