Class Notes (809,047)
Canada (493,506)
Sociology (3,202)
SOC200H1 (95)


4 Pages
Unlock Document

University of Toronto St. George
Alexandra Marin

September 30 , 2013 Independent variable → the cause Dependent variable → the effect Cause has to come before the effect Spurious variable has to be the cause of both?? To control you must hold it constant → if relationship goes away then you can tell it is spurious WIKIPEDIA: In statistics, a spurious relationship (or, sometimes, spurious correlation) is a mathematical relationship in which two events or variables have no direct causal connection, yet it may be wrongly inferred that they do, due to either coincidence or the presence of a certain third, unseen factor (referred to as a "confounding factor" or "lurking variable"). Suppose there is found to be a correlation between A and B. Aside from coincidence, there are three possible relationships: A causes B, B causes A, OR C causes both A and B How does X cause Y? → called a mechanism Mechanism → an account of how (or the process by which) one thing causes another, it is basically a story WIKPEDIA: “To explain an event is to give an account of why it happened. Usually… this takes the form of citing an earlier event as the cause of the event we want to explain…. [But] to cite the cause is not enough: the causal mechanism must also be provided, or at least suggested.” Example: Education leads to more income People with more education → seen as more skilled → get higher status job → more pay money Orrr people with more education → more and better employment options → able to negotiate better salaries Another Causal relationship → working fewer hours for pay causes better grades  Mechanism: More time to study Causal relationship → living in a city causes better health  Easier access to hospitals  Walk more than in rural areas  More money so they choose to go in the city (spurious)  Chances of make more money in the city (mechanism) Casual relationship → having kids = less sleep  Crying babies When we see competing mechanism, how are we going to know which one?  Proposed mechanism is a theory of how X leads to Y  Credentialism: people with more education →  Have to find an intervening variable! o EDUCATION (independent variable) + → CREDENTIALS (intervening variable) +→ INCOME (dependent variable) o Education causes income (already supported) o Education causes credentials o Credentials causes income o Where education doesn’t lead to credentials, it doesn’t lead to higher income  Where education doesn’t lead to credentials o Hold constant the intervening variables (see graph comparing those with only one credential vs two credentials/ high school vs degree → those with just one credential doesn’t have a lot of income compared to the second → if you’re right, your graph should look like a flat line. Statistically the intervening variable and a spurious relation is statistically, mathematically the same.  Not only are variables affected by things, but the relationship between variables can be affected Math skills → grades BUT MAJOR! It depends on your major… being physics students with bad math skills = bad grades, an engl
More Less

Related notes for SOC200H1

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.