Pols 306 Exam 2

Question 1

What is correlation?

Answer 1

A relationship between two variables.

Question 2

What is a spurious correlation?

Answer 2

Relationships that are not genuine. When two measures of two or more variables are not in fact directly related.

Question 3

What is a lurking variable?

Answer 3

A third variable that influences the correlation between two other variables. This is why we control for other factors.

Question 4

What are the 5 R’s?

Answer 4

Refining, replicating, reducing, revealing, and reversing.

Question 5

What are the seven elements of a good table?

Answer 5

A clear title.
Figures are in browns instead of columns.
IV is on the top and DV is on the left.
Percentages over Absolute Numbers
Write totals at the bottom of the column.
Round numbers when you can.
Footnotes for sources and important information.

Question 6

In social science, how do you define significance?

Answer 6

It means that it is probably true.

Question 7

What is the p-value?

Answer 7

Probability that the sample selected is false

Question 8

How do you deductively determine the significance of the findings?

Answer 8

Testing important and substantive findings may suggest ways to modify the theory or seriously undermine the theory.

Question 9

r

Answer 9

Correlation coefficient, the strength of the relationship between two variables
(1.0 = perfect positive relationship -1.0 perfect negative relationship)
Sensitive to outliers and extreme values

Question 10

Marginals

Answer 10

The totals along the columns and rows

Question 11

Expected Frequencies

Answer 11

The expected frequency is the null hypothesis. The Chi square is comparing observed observations with null hypothesis

Question 12

Control Variable

Answer 12

The variable that has not changed

Question 13

Substantive Significance

Answer 13

The substance of a finding takes on importance only to the extent that it contributes to information valuable for the understanding of political behavior or business or public policy.

Question 14

p<.05

Answer 14

p<0.5 means that such an error would occur less than five times in 100 samples. *

Question 15

Slope

Answer 15

How much your dependent value changes based off of one unit of the independent variable

Question 16

Quartiles

Answer 16

4 parts of data
If you have 100 people 25 people would be in each quartile 2 inner quartile are closest to the mean and the 2 outer quartiles are farther from the mean because the graph flattens out

Question 17

Observed Frequencies

Answer 17

the number of times a specific event or outcome actually occurs in an experiment or real-life situation

Question 18

Revealing Effect

Answer 18

The original relationship changes are strengthened under certain conditions.

Question 19

Outlier

Answer 19

Does not follow the pattern of data

Question 20

M

Answer 20

Median

Question 21

Correlation Coefficient

Answer 21

A measure of the degree to which two variables are linearly related

Question 22

r2

Answer 22

the proportion of the variation in the dependent variable that is predictable from the independent variable

How close the data fits the line of best fit

Question 23

Y intercept

Answer 23

X=0

Question 24

Ecological Fallacy

Answer 24

When the researcher makes claims
about one lower-level unit of analysis that is based on data from some higher-level unit of analysis. Aggregate data to individualized assumption

Question 25

Reversing Effect

Answer 25

Original relationship changes from positive or negative.

Question 26

Type 1 Error

Answer 26

False Positive: Mistakenly claiming there is a relationship when there isn’t one (p-value of .05 indicates you are willing to accept a 5% chance of being wrong)

Question 27

Panel Study

Answer 27

Asking the same people the same questions as they change over time

Question 28

Type 2 Error

Answer 28

False Negative: When analysis concludes there is no relationship between the independent and dependent variables when in fact there is a relationship (particularly problematic in disease control)

Question 29

Replicating Effects

Answer 29

Control variable has no effect on the original relationship.

Question 30

Reducing Effect

Answer 30

Original relationship diminishes or disappears

Question 31

S

Answer 31

Standard deviation

Question 32

Cohort Study

Answer 32

Examines specific subpopulations, or cohorts, as they change over time. Typically, it is where demographers select a particular group (generation) and follow the changes that occur to those born at a certain year.

Question 33

Chi Square

Answer 33

Level of significance for the relationship between variables measured at a nominal and ordinal level; compares actual observed values to expected values; compares observed frequencies with the null hypothesis

Question 34

Z score

Answer 34

The number of standard deviations the value is away from the mean. It standardizes data so you can compare apples to oranges.

Question 35

Refining Effects

Answer 35

The original relationship between the dependent and independent variables only holds up under certain conditions.

Question 36

Spurius Relation

Answer 36

Relationships that are not genuine. When two measures of two or more variables are not in fact directly related.

Question 37

t value

Answer 37

the ratio of the departure of the estimated value of a parameter from its hypothesized value to its standard error.

Question 38

Lurking Variables

Answer 38

A third variable that influences the correlation between two other variables. This is why we control for other factors.

Question 39

Reductionism

Answer 39

When claims about some higher-level unit of analysis are made based on data at some lower-level unit of analysis.
Small to big