Political Inquiry

Front 1

Symmetric

Back 1

a word to describe correlation of DV and IV- if something is symmetric, it doesn't make a distinction between the IVs and DV

Front 2

What is to be considered a “strong” relationship and a “weak” relationship? When is this useful?

Back 2

Strong relationship is when the regression has substantive and statistical significance. A weak relationship is when it doesn't. This is useful when calculating the correlation of a DV and IV.

Front 3

Regression

Back 3

A procedure that derives statistics to evaluate the relationship between two interval variables.

Front 4

Least-squares line

Back 4

the single best fitting lines that explains the relationship of the variables (where the R squared is the highest)

Front 5

Slope

Back 5

Measured by coefficients, the angle at which the line rises or falls, the effect of the IV on the DV and it can tell us if the relationship is positive or negative (highly dependent on the units of mesurement)

Front 6

Pearsons's R

Back 6

Measures how closely points are around the regression line (fit)

Front 7

R-squared

Back 7

The percent in the variance of the DV explained by the IV (closer to 1 is best)

Front 8

F-test

Back 8

How many standard deviations the entire regression is away from the mean (same as T-stat = slope/standard error)

Front 9

Describe the principle behind regressions

Back 9

The key idea is that there is a line that best describes the relationship between the IV and DV

Front 10

Explain the function of Pearson’s r

Back 10

It tells us the strength of association and is a measure of how good a predictor one variable is of another

Front 11

List ways to calculate substantive significance

Back 11

-Coefficients (slope) for each IV
-R squared (fit) for overall regression

Front 12

List ways to calculate statistical significance

Back 12

- P-Value for each IV
- T-stat for each IV
- F-stat for overall regression
- Sig. F for overall regression

Front 13

Coefficients for regression essay

Back 13

Found not in brackets, 1 unit increase in x correlates with a ________ increase in Y

Front 14

R squared for regression essay

Back 14

Found at bottom of graph, % variance in DV explained by IV's, above .3 or closer to 1 for substantive

Front 15

P-value for regression essay

Back 15

Found at bottom indicated by stars, less than .05 to determine relationship

Front 16

T-stat for regression essay

Back 16

Found by dividing coeffient/standard error (found in brakets), ought to be more than absolute value of 2

Front 17

F-stat test for regression essay

Back 17

Found by dividing coeffient/standard error (found in brakets) for whole regression, more than 2

Front 18

Significant F for regression essay

Back 18

Found by stars, less than .05 to determine relationship of whole regression

Front 19

Three standard deviation numbers

Back 19

68, 95, 99.7

Front 20

Method problems for regression essay

Back 20

Multicollinearity, Amount of Cases, Endogeneity, Spurious Relationship, Auto-Correlation

Front 21

Spurious

Back 21

A relationship where the independent variable really does not affect the dependent.

Front 22

Intervening Variable

Back 22

When the independent variable goes in between the other two variables =b where a=b=c

Front 23

Beta Weights

Back 23

Also called standardized regression coefficients, they are standardized results of multiple regressen analyses. They show effect of each indpenednt variable on the dependent variable, controlling for all other independent variables, and they use the standard deviation of the variables to remove the effects of the particular units in which the variables are measured.

Front 24

Reciprocal

Back 24

In causation, for X to influence Y while Y influences X (causal relationships should only be one direction). Ex. ideology and partiy indentification.

Front 25

What is the most important principle to remember when dealing with control variables?

Back 25

not finished

Front 26

What are the criteria for inferring causality? Briefly explain each.

Back 26

not finished

Front 27

How should you interpret regression coefficients, or b's? Compare this to the interpretation of beta, or beta weights.

Back 27

not finished

Front 28

Difference between independent causation, spurious correlation, intervening variable, and complete causation.

Back 28

look at pictures on page 180 of monroe

Front 29

Causal Mechanisms

Back 29

The intervening connection between indepedent and dependent variables.

Front 30

Process Tracing

Back 30

Using time and sequence to test the causal story. (tracing sequence or history, and chart the events that happen between X and Y.)

Front 31

Causal Effect

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The change in the expecetd value of the outcome variable brought about by a specified change in the vaule of an independent variable.

Front 32

Why can a causal mechanism not be directly observed?

Back 32

"They are a component of the of a causal process that intervenes between agetns with causal capacities and outcomes." Or in laymen terms it is because they are like the plus sign between two numbers, without the numbers the plus sign cannot be observed to do anything.

Front 33

Which is more important: the causal mechanism or the causal effect? Why?

Back 33

They are equally necessary components of explaining causal theories. This is because they illustrate different but important connections between the independent and dependent variable.

Front 34

What are the advantages of process tracing in theory development and testing?

Back 34

Process tracing is the empircal tracing of the causal mechanisms. Theory development and testing: identify paths to an outcome, point out excluded variables, check for spuriousness, and permit causal inference on the basis of a few or even a single case.

Front 35

Goodluck on the test

Back 35

I'm sure you'll do awesome...this is kind of a cheesy thing to do, so sue me. -Nathan

Front 36

Knock Knock!
Who's there?
Wendy.
Wendy who?

Back 36

Wendy wind blows de cradle will rock (www.knock-knock-joke.com 2006).

Front 37

Cross-cutting cleveages

Back 37

Ask Allison about it...

Front 38

quantitative research

Back 38

uses numbers and statistical methods, based on numerical measurements of specific aspects of phenomena, seeks general discriptions, seeks measurements and analyses that are easily replicable by other researchers

Front 39

qualitative research

Back 39

focuses on one or a small number of cases, use intensive interviews or in depth analysis of history, discursive method, concerned with rounded or comprehensive account of some event.

Front 40

falsifiable

Back 40

capable of generating as many observable implications as possible, allows more tests of the theory with more data and a greater variety of data.

Front 41

parsimony

Back 41

a simple assumption about the nature of the world