topic4_associations_handout_2017.pptx

topic4_associations_handout_2017.pptx - PH 3200...

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PH 3200: Introduction to Biostatistics Describing Associations Robert H Podolsky
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Agenda & Learning Objectives Association Overview Explain what is meant by association between two variables Identify which of two variables is a response variable and which is an explanatory variable Association between two categorical variables Interpret a contingency table Compute and interpret marginal and conditional proportions Summarize association between two categorical variables using the difference in proportions, risk ratio, or the odds ratio Association between two quantitative variables Use scatterplots to describe the trend, direction, and strength of association Calculate and interpret the covariance and Pearson’s correlation Describe limitations of correlation
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ASSOCIATION OVERVIEW
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Scatter Plots & Types of Variables Contnuous Contnuous Categorical Categorical Y X
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Response and Explanatory Variables Response variable (Dependent variable) The outcome variable on which comparisons are made. Explanatory variable (Independent variable) Categorical explanatory variable: defines the groups to be compared with respect to the response variable. Quantitative explanatory variable: defines the change in different numerical values to be compared with respect to the values for the response variable. Example: Response/Explanatory
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  • Winter '18
  • podolsky
  • Statistics, Covariance and correlation, explanatory variables, scary movies

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