Review Sheet 2

# Review Sheet 2 - Pop mean = sample mean = x = x i n Pop...

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Pop mean = μ , sample mean = x = x i / n Pop variance = σ 2 , sample s 2 = ss/df df – number of independent pieces of info in a calculation (n-1) Var(x) = (x i -x ) 2 /(n-1), variance = σ 2 /n St. dev. = σ / n t-statistic = estimated – hypothesized parameter value/SE(estimate) SE(estimate) = s p (1/n 1 +1/n 2 ) CI: x±m*SE(x) or x±2*( σ / n) -2SE(e) < e < 2SE(e) Not skewed e -2SE(e) Negative skew e 2SE(e) Positive skew -2SE(u) < u < 2SE(u) Not kurtotic u -2SE(u) Negative kurtosis u 2SE(u) Positive kurtosis Quantitative – can be meaningfully subtracted - discrete – only whole numbers - continuous – interval, fractions Categorical – numbers are not meaningful - nominal - categorical and no meaningful order Bias how far the average of many measurements is from the true value Skewness – measure of asymmetry IQR – measure of spread (Q3- Q1), more robust than var or QN plot – if all points fall on or nearly on diagonal line, Normal distribution -allows detection of non-normality and diagnosis of skewness and kurtosis -values too high in high&low range – positive(right) skew - high end points too high&low end Probability mass function (pmf) – discrete/cat. Two-level cat. variable, quantitative outcome -> independent samples t-test or ANOVA t-statistic = difference between sample means divided by st. error of difference p-value = probability that any given experiment will produce value of chosen statistic equal to observed value in experiment or something more extreme, when null hypothesis is true and assumptions are met -reject null hypothesis when p-value is less than acceptable type 1 error rate ( ) α -if null hypothesis is really true, approximate p=value will be less than .05 exactly Measurement variability – differences in repeat measurement values (high precision) Environment variability – tradeoff – may reduce external validity Treatment application variability difference in quality/quantity of treatment among subjects assigned to same treatment Internal validity – degree to which we can appropriately conclude that changes in X caused changes in Y -random assignment of treatment – best way to assure that all potential confounding variables are equal on average among groups -block randomization – randomization is performed separately for each level of the critical

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## This document was uploaded on 06/28/2011.

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Review Sheet 2 - Pop mean = sample mean = x = x i n Pop...

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