SOC202H1 Lecture Notes - Linear Regression, Null Hypothesis, Statistic
Document Summary
Ch15 bivariate correlationship and regression: hypothesis testing. Larger slope and smaller standard error yield stronger evidence against the null hypothesis. Standard error of the slope ( ) Estimates the degree of sample-to-sample variation if regression slopes were calculated from many random samples of size n. A small standard error implies a higher likelihood that most of the sample slopes would be near the true population slope. Larger standard error implies that the regression coefficient estimate may not accurately reflect the true relationship between x and y in the population. Standard deviation of the residual ( ) Careful interpretations of correlation and regression statistics: correlation apply to a population not an individual, careful interpretation of the slope, b, distinguishing statistical significance from practical significance. 6 steps of statistical inference and 4 aspects of a relationship: requirements: There is one representative sample from a single population. There are no restrictions on sample size, but generally, the larger the n the better.
