Greg Martin Statistics Overview

https://www.youtube.com/watch?v=I10q6fjPxJ0&t=437s    

Variables can be Categorical summarize in table or bar chart Numeric  distribution- range, interquartile range, mean median box plot histogram H1 is hypothesis  H0 is null hypothesis  Probability of relationship testing- p value.  Alpha valiue is cut off pt to reject the null. if p is less than alpha, we reject the null Chi-squared test (x^2) determines if there is significant difference between expected and observed frequencies in one or more categories  looks at how likely the observed frequencies would be if null hypothesis is true if more than two categories in one of the variables, do ANOVA instead of t test correlation test- get correlation coefficient (between-1 and 1) and p value  perfectly negative correlation is -1 no cor is 0 perfectly pos is 1