research design quiz #12

Question 1

After we have gathered and cleaned our data, we can run different
statistical analyses to…

Answer 1

• Explore relationships between different variables
• Understand the distributions of our variables
• Test measures of central tendency and dispersion
• Answer research questions or hypotheses

Question 2

Different types of statistics are used to answer different types of
questions:

1)M of a
2) C s
3) I s

Answer 2

• Measures of association
• Comparative statistics
• Inferential statistics

Question 3

Measures of _________ determine the strengths of _________ among the variables that are being studied

Answer 3

association;

relationships

Question 4

two continuous measures (measures from -1 = perfect negative association to +1 = perfect positive association)

which of the seven (7) measures of association is this one?

Answer 4

Pearson’s R

Question 5

measures the association between two dichotomies

which of the seven (7) measures of association is this one?

Answer 5

Phi coefficient

Question 6

measures the association between two rank ordered
variables

which of the seven (7) measures of association is this one?

Answer 6

Spearman’s rank order correlation (Rho)

Question 7

measures the association between a continuous variable and a
dichotomous variable

which of the seven (7) measures of association is this one?

Answer 7

Point-biserial correlation

Question 8

measures the association between a continuous variable and a theoretically continuous-but-polytomized variable categorized into 3+ levels (think Likert scale scores)

which of the seven (7) measures of association is this one?

Answer 8

Polyserial correlation

Question 9

measures the association between two dichotomous variables and
estimates what the association would be had both variables been continuous

which of the seven (7) measures of association is this one?

Answer 9

Tetrachoric correlation

Question 10

measures the association between ordinal variables with two or
more levels

which of the seven (7) measures of association is this one?

Answer 10

Polychoric correlation coefficient

Question 11

_______ ________ involves analysis of the attributes of
the variables being examined to better describe the relationship
between two variables

Answer 11

comparative statistics

Question 12

First comparative statistic:
Frequently presented in research

Usually reflects the number of crimes divided by the population multiplied by 100,000

This equation gives you the crime count per 100,000 people; could be per million, ten thousand, thousand, hundred etc

Answer 12

crime rates

Question 13

Second comparative statistic:
Same as above, except that the chosen denominator is not the population count, but rather a factor related to the crime type

For example, dividing the number of burglaries by the number of households; number of MVTs by number of registered vehicles in an area and so on

Answer 13

crime-specific rates

Question 14

Third comparative statistic:

Great for comparing data fluctuations over time

Easy to calculate: Subtract the first-time value from the second-time value, then divide by the first-time value

Answer 14

Percentage change

Question 15

fourth comparative statistic:

Great for examining the behavior of data over time
Great for comparing similar and/or different data side by side over time
Can apply lines of best fit (linear, average, polynomial etc.)
Good for assessing the impact of crime prevention strategies

Answer 15

Trend analysis

Question 16

_____ _______ involves not only describing relationships,
but makes predictions and/or inferences about dependent variables based on the influence of independent variables

Answer 16

inferential statistics

Question 17

We have many different types of inferential statistics to choose from:
1) B a
2) C t
3) t-t
4) C
5) A
6) B r
7) M r

Answer 17

• Bivariate analyses
• Contingency tables
• t-tests
• Correlations
• ANOVAs
• Bivariate regression
• Multivariate regression

Question 18

INFERENTIAL STATS:
Which for the seven (7) inferential stats should we use for this?

Examining the relationship between to variables

b a

Answer 18

Bivariate analyses

Question 19

INFERENTIAL Stats:
Which for the seven (7) inferential stats should we use for this?

Usually used when you have two nominal variables you want to compare
Can simply use cross-tabulation tables
Can also use Chi-square (2) to test for statistical significance

c t

Answer 19

Contingency tables

Question 20

INFERENTIAL Stats:
Which for the seven (7) inferential stats should we use for this?

Used to test whether group means are statistically significantly different from each other

Independent samples ____ versus paired(aka dependent) samples _____

t-t

Answer 20

t-tests

Question 21

INFERENTIAL Stats:
Which for the seven (7) inferential stats should we use for this?

Again, used for assessing the relationship between two variables (review previous slide on correlation types)
If we square the correlational value, we have the proportion of explained variance

Answer 21

correlations

Question 22

INFERENTIAL Stats:
Which for the seven (7) inferential stats should we use for this?

Principally used to determine whether three or more groups significantly vary in
relation to each other

We can determine if the mean values of a measure for each group are
significantly different from each other

Example: we have three groups of officers and want to know whether the
number of arrests significantly differ between groups

A

Answer 22

ANOVA’s (analysis of variance)

Question 23

what does ANOVA stand for

Answer 23

analyisis of variance

Question 24

INFERENTIAL Stats:
Which for the seven (7) inferential stats should we use for this?

Based on the principle that over time things tend to regress toward the mean

Use one variable (IV) to predict another variable (DV)
Several assumptions must be met in order to use linear regression (Normality, linearity, homoscedasticity)

B r

Answer 24

Bivariate regression

Question 25

INFERENTIAL Stats:
Which for the seven (7) inferential stats should we use for this?

Same as above, but you are assessing the predictive potential of multiple IVs and control variables in relation to a dependent variable

m r

Answer 25

multivariate regression