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SOC 2294 > Bivariate and Trivariate Relationships > Flashcards

Bivariate and Trivariate Relationships Flashcards

1
Q

what is covariation?

A

association/ a relationship

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2
Q

what is independence when regarding variables?

A

no pattern/association

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3
Q

what is a hypothesis?

A

a tentative statement about a relationship between variables

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4
Q

what is a directional/one-tailed hypothesis?

A

a hypothesis that states the direction of a relationship

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5
Q

what is a non-directional/two-tailed hypothesis?

A

a hypothesis that doesn’t state the direction of a relationship

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6
Q

are most hypotheses directional or non-directional?

A

non-directional

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7
Q

what is a positive relationship?

A

variable A increases when variable B increases and vice versa

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8
Q

what is a negative relationship?

A

variable A increases when variable B decreases and vice versa

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9
Q

how can you establish causation?

A

-replication
-controlling for a 3rd variable
-manipulate the IV
-use logic and reasoning

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10
Q

what is induction?

A

qualitative and exploratory approach; start with specific observations to general theory

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11
Q

what is deduction?

A

quantitative approach; start with general theory to specific observations

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12
Q

which levels of measurement can contingency tables be used for?

A

any, but primarily…
- nominal (x) and nominal (y)
- ordinal (x) and ordinal (y)
- nominal (x) and ordinal (y)

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13
Q

in a contingency table, what is the maximum amount of difference allowed between DV values?

A

it should be less than or equal to 10%

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14
Q

in a contingency table, what is the maximum amount of categories a DV and IV can have?

A

DV should have less than 7 categories and IV should have less than 4 categories

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15
Q

in a contingency table, what are the marginals?

A

the totals

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16
Q

in a contingency table, where should the DV and IV be placed?

A

DV should be at the very left and IV should be at the very top

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17
Q

what is a measure of association (correlation coefficient)?

A

a single # expressing strength and direction of a bivariate relationship

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18
Q

what are characteristics of correlation coefficients?

A
  • some only detect linear, others only detect non-linear
  • can include direction of relationship when using minimal ordinal level
  • strength is always been 0 and (-)1
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19
Q

what is a symmetric coefficient?

A

unaffected by which variable is the IV; value remains the same whether X is IV and Y is DV or X is DV or Y is IV

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20
Q

what is an asymmetric coefficient?

A

affected by which variable is the IV; value of coefficients are different and depend on which variable is the IV

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21
Q

which level of measurement is most appropriate for correlation coefficients?

A

interval/ratio

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22
Q

what is proportion reduction error (PRE)?

A

looks at how well we can predict the DV value using the IV value

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23
Q

how does PRE determine strength of a relationship?

A

fewer errors in predictions means a stronger relationship

24
Q

PRE compares errors in which 2 situations?

A
  1. using the IV to make predictions
  2. not using the IV
25
Q

which levels of measure is lambda appropriate for?

A
  • nominal (x) and nominal (y)
  • nominal (x) and ordinal (y)
  • ordinal (x) and nominal (y)
26
Q

which measure of central tendency is best to use with lambda?

A

the mode

27
Q

does lambda show direction and/or strength?

A

lambda only shows strength, not direction

28
Q

which level of measurement is most useful in lambda calculations?

A

nominal

29
Q

what is E1 in the lambda formula?

A

errors made without using the IV for prediction (found in the marginal)

30
Q

what is E2 in the lambda formula?

A

errors made using the IV for prediction

31
Q

for lambda, how do you find errors in contingency tables?

A

sum of the cells excluding the mode

32
Q

what are limitations of lambda?

A
  • less useful for variables beyond nominal
  • doesn’t show distribution among categories, thus can’t detect direction of association
33
Q

what is gamma?

A

predicts the ordinal arrangement of values

34
Q

in gamma, what is the pairs concept?

A

looks at relative ranking of 2 parts of the pair on both variables

35
Q

what is the unit of analysis in gamma?

A

the pair

36
Q

what are the types of pairs?

A

concordant, discordant, tied

37
Q

what is a concordant pair?

A

in accordance with each other; two IV levels go up and down together on the DV

38
Q

what is a discordant pair?

A

not in accordance with each other; two IV levels inconsistently go up and down together on the DV

39
Q

what is a tied pair?

A

exact same values; two IV levels have the same value on one/more DV levels

40
Q

what is Ns and Nd in the gamma formula?

A

Ns is the number of concordant pairs and Nd is the number of discordant pairs

41
Q

how do you calculate Ns in gamma?

A

using raw data, multiply the cell frequency by sum of all frequencies below and to the right of it, then add all products

42
Q

how do calculate Nd in gamma?

A

using raw data, multiply the cell frequency by sum of all frequencies below and the to the eft of it then add all products

43
Q

what indicates a positive relationship in gamma?

A

if there are more concordant pairs than discordant

44
Q

what indicates a negative relationship in gamma?

A

if there are more discordant pairs than concordant

45
Q

what are the characteristics of gamma?

A
  • best to use when both variables have few categories
  • symmetric (doesn’t matter which variable is the IV)
  • assumes linearity
  • ignores pairs tied on X, Y, or both X and Y
46
Q

what is an elaboration model?

A

looks at what happens to a zero-order when you control for a 3rd variable

47
Q

what is a zero-order relationship?

A

the original bivariate relationship; without the 3rd variable

48
Q

which criteria of causation does the elaboration model determine?

A

non-spuriousness

49
Q

in an elaboration model, what the do the partial results include?

A

the 3rd variable

50
Q

what are the 4 elaboration models?

A

replication, explanation, interpretation specification

51
Q

what is the replication elaboration model?

A

partial and original order are the same; all relationships are small in zero-scale

52
Q

what is the explanation elaboration model?

A

partial relationships are 0 or less than original order, and the 3rd variable is antecedent

53
Q

what is an antecedent variable?

A

comes before the IV in time

54
Q

what is the interpretation elaboration model?

A

partial relationships are 0 or less than original order, and the 3rd variable is intervening

55
Q

what is an intervening variable?

A

comes after the IV in time

56
Q

what is the specification elaboration model?

A

one partial is the same or more than the original order and the other partial is 0 or less than the original order

SOC 2294 (9 decks)

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