Class Notes (807,343)
Canada (492,710)
POL242Y1 (17)

Week 10 Lecture

4 Pages
Unlock Document

University of Toronto St. George
Political Science
Anthony Sealey

Week 10 Taking up the Quiz#4  We need a point estimate plus or minus our margin of error. 5.33 + or minus 0.25. (5.33 + 0.25)  Alternative hypothesis is related to region of rejection. Assignment #4-  Say/relate confidence to what you were analyzing  Explanation Section 2: Calculate confidence interval: you can say and relate it to what you were analyzing. E.g. Mean of the post communist data, therefore we can say with 95% of confidence that population parameter is the mean of the score of citizens of communist states is somewhere between…. And …. Testing Hypotheses: An alternative Approach Unstandardized Value  Probability value into standardized value called a T score. Stick it into Chi- function etc…Fifth step, you take your unstandardized test statistic into a standardized value.  X bar, subtract off the hypothesized value.  Universal standardized score (mean of standardized score): Mew= 0. o If we have a standardized score of 0.5, how much area is there?  If you get prob. Value and get it there, therefore, the form of the hypothesized test is: we do not reject null hypothesis.  B/c we know our alpha score is 0.5 We are looking for probability score of less than 0.5.  Left tailed test is -1.96. 2 is close to 0.5. If you calculate probability, the guess is 4.8 which is slightly behind 5%  Rather than using the tin, norminv and chiinv function in R to transform prob. Alues from level of significance into critical values, we transform from standardized to probabibility values. Example: Suppose that you want to test the hypothesis that the proportion of the public who favors some public policy is less than 50%. You draw a sample of 1200 canadians and find that 53.2% are in favor. Please test this hypothesis.  No need to find the critical numbers, b/c the alpha is already a prob. Score not standardized score AN introduction to Regression Analysis  Bi variate Linear Regression  Regression analysis s introduced to analyze relationships between linear variables.  Far more powerful tool used to analyze ANY type of variable.  Standard linear bivariate regression model (two variables)- in a relationshipthen presumably, there are 1 independent variable and 1 dependent variable o Independent affects dependent variable  Generally speaking, simple linear relationships among interval variables are rare.  Analyze data that is best modeled in a different way. o At eh macro level, how does political ideology of a palce affect public policy? o Measuring political ideologu on left right spectrum and public support as “decent standard of living”  Drawing a scatterplot  What type of relationship is this? o Negative relationship  Generally speaking, as we increase the alue of the independent variable, values of dependent decreases.  There are three relationships o Positive o Negative o No relationship  Generally for
More Less

Related notes for POL242Y1

Log In


Don't have an account?

Join OneClass

Access over 10 million pages of study
documents for 1.3 million courses.

Sign up

Join to view


By registering, I agree to the Terms and Privacy Policies
Already have an account?
Just a few more details

So we can recommend you notes for your school.

Reset Password

Please enter below the email address you registered with and we will send you a link to reset your password.

Add your courses

Get notes from the top students in your class.