lecture 17

# lecture 17 - Hypothesis Testing Lecture 17 Hypothesis...

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1 Lecture 17 Hypothesis Testing and Statistical Significance Inferential Statistics { Allow for making predictions, estimations or inferences about what has not been observed based on what has (from a sample) through hypothesis testing Inferential Statistics { Requires testing a hypothesis z H o : null hypothesis { No effect or no difference z H a : research (alternative) hypothesis { There is an effect or difference Hypothesis Testing { I believe that Treatment A is better than Treatment B. Why not test my research hypothesis? Why test the null hypothesis? H 0 : Treatment A = Treatment B z The research hypothesis requires an infinite number of statistical tests z If we test the null hypothesis, we only have to perform one test, that of no difference Hypothesis Testing { The statistical association tells you the likelihood the result you obtained happened by chance alone { A strong statistical association does not show cause! { Every time we reject the null hypothesis we risk being wrong { Every time we fail to reject the null hypothesis we risk being wrong Examples of Hypothesis Testing { You calculate age-adjusted rates for New Brunswick and South Brunswick and compare them z H o : AAR1 = AAR2 z H a : There is a statistically significant difference between the age-adjusted rates of New Brunswick and South Brunswick

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2 Hypothesis Testing (cont.) { You calculate odds ratios and relative risks z H o : OR = 1 (or RR = 1) z H a : There is a statistically significant difference between cases and controls (or between the exposed and unexposed) Hypothesis Testing (cont.) { You calculate the SMR for workers z H o : SMR = 100% z H a : There is a statistically significant difference between the cohort and the control population Steps in Hypothesis Testing { Assume the null hypothesis is true { Collect data and test the difference between the two groups { Set your level of significance { Calculate your p-value (the probability that you would get these results by chance alone) { If the p-value is low (chance is an improbable explanation for the result), reject the null
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## This note was uploaded on 04/06/2008 for the course PUBLIC HEA 832:335 taught by Professor Schneider during the Spring '08 term at Rutgers.

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lecture 17 - Hypothesis Testing Lecture 17 Hypothesis...

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