Created by Lindsay Dade
over 4 years ago
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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
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