KINE 2050 Lecture Notes - Lecture 2: Statistical Inference, Frequency Distribution, Dollar Sign
6 Mar 2018
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Document Summary
Independent variable is the variable that is manipulated by the researcher. Ideally we want to have complete control, with a rct, but in reality we can"t control everything, so we use randomization to hope that all other things that can a ect the dv are washed out across the randomization. This is done so that we can apply causation, and not just a correlational relationship between the variables. Statistical methods: help in describing data, making inferences from generalizations from the experimental data to larger groups, making causal relationships. When we collect data: rst we look at descriptive statistics , such as the mean median and mode, then we look at inferential statistics, that let us look at trends in the general population. Data steps: name variables, de ne what type of variable that you are inputting (numeric or text) Proc steps tells sas what procedures we want to perform on the data set that you have identi ed in the.
