Pol 51 lecture 9

# Pol 51 lecture 9 - random event Given the relationship...

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Pol 51, Lecture 9 Bivariate Hypothesis Testing We want to be able to identify a relationship as “statistically significant” (which means we might’ve cross 3 hurdles. We’re confident that there’s a relationship, but it may not be a big significance). Not used as a final analyses because of Z’s. only time to not worry about Z’s is experiments. Limited utility. Categorical , categorical– tabular analysis (chi squared text) Categorical, continuous – difference of means (T test) any experiment with control and uncontrolled group ex: the effect of gender on income Continuous, categorical – probit/logit Continuous, continuous – correlation coefficient; bivariate regression P-value : probability value. Ranges from 0-1, closest thing we have to ‘bottom line’. Probability that you’re making a mistake when making inference. Probability that relationship between X and Y are just a
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Unformatted text preview: random event. Given the relationship, what’s the probability that there is no relationship? If there’s no relationship, what’s the probability of the sample? Lower the p-value, greater confidence we have there is a relationship between X and Y. however, it is not true that if p-value is 0 that relationship is stronger. P-value of .05 or less is considered to be statistically significant. Even if it’s “stastically significant” relationship DOES NOT mean that relationship between X and Y is strong or relationship is causal. Null-hypothesis is that there is no covariation. If there isn’t a relationship, then there is a relationship (reject the null hypothesis) We start with assumption that X and Y DO NOT covariate, then we see a relationship between X and Y (use statistical data). So never say that THERE IS a relationship, but rather there PROBABLY is a relationship....
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## This note was uploaded on 08/30/2011 for the course POL 51 taught by Professor Ryan,john during the Summer '08 term at UC Davis.

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