Student Learning Outcomes:
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How interesting and fun statistics can be
? How and why statistics has developed as a tool of the scientific process
? How data are collected and how observations are quantified during the scientific and research process
? How observations are represented and stored in a data file
? The uses and limitations of statistical software
? The scaling and coding of data
? Frequency distributions; how data can be represented visually, and the strengths and weaknesses of these representations
? Methods of appropriately describing the central tendencies of various distributions
? Variability and how to quantify variability
? The reasoning and assumptions underlying the inferential statistical process
? Probability, as it refers to inferential statistics
? Correlation and simple linear regression
? The appropriate application and interpretation of various inferential statistical procedures, including the t-test, the Chi-square test, inferential tests applied to correlation, and basic ANOVA
? How to write a simple description of methodology and results from analyses

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