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soc 210 > FINAL REVIEW > Flashcards

FINAL REVIEW Flashcards

1
Q

BIVARIATE TABLE

A

a table that displays the joint frequency distributions of 2 variables

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2
Q

CELLS

A

the cross classification categories of the variables in a big aria the table

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3
Q

X^2 (CRITICAL)

A

the score on the sampling distribution of ALL possible sample chi squares

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4
Q

X^2 (OBTAINED)

A

the test statistic as computed from SAMPLE RESULTS

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5
Q

CHI SQUARE TEST

A

a non-parametric test of hypothesis for variables that have been organized into a bivariate table

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6
Q

COLUMN

A

the vertical dimension of a bivariate table
- each column represents a score on the INDEPENDENT VARIABLE

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7
Q

EXPECTED FREQUENCY (fe)

A

the cell frequencies that’d be expected in a bivariate table if the variables were INDEPENDENT

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8
Q

GOODNESS OF FIT TEST

A

an additional use for chi square that tests the significance of the distribution of a single variable

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9
Q

INDEPENDENCE

A

the NULL hypothesis in the chi square test
- 2 variables are interdependent if, for all cases, the classification of a case on one variable has NO EFFECT on the probability that the case will be classified in any particular category of the second variable

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10
Q

MARGINALS

A

the row and column subtotals in the bivariate table

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11
Q

NONPARAMETRIC

A

a “distribution free” test
- these tests don’t assume a normal sampling distribution

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12
Q

OBSERVED FREQUENCIES (fo)

A

the cell frequencies actually observed in a bivariate table

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13
Q

ROW

A

the HORIZONTAL dimension of the bivariate table, conventionally representing a score on the dependent variable

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14
Q

THE DECISION TO REJECT THE NULL HYPOTHESIS IS NOT SPECIFIC

A
  • means that only ONE statement in the model OR the null hypothesis is WRONG
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15
Q

WHAT LEVEL CAN A CHI SQUARE TEST BE CONDUCTED AT

A

can be measured at the NOMINAL LEVEL, which is the lowest level of measurement
- because it is NONPARAMETRIC, chi square requires NO ASSUMPTION at all about the shape of the population or sampling distribution

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16
Q

THE ____ CERTAIN WE ARE OF THE MODEL, THE _____ OUR CONFIDENCE THAT THE NULL HYPOTHESIS IS THE FAULTY ASSUMPTION

A

more, greater

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17
Q

A “_____” OR EASILY SATISFIED MODEL MEANS THAT OUT DECISION TO ______ THE NULL HYPOTHESIS CAN BE MADE WITH EVEN GREATER CERTAINTY

A

weak, reject

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18
Q

CHI SQUARES FLEXIBILITY

A

can be used and conducted with any variables at ANY LEVEL OF MEASUREMENT

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19
Q

WHAT ARE A BIVARIATE TABLES TWO DIMENSIONS

A
  • the horizontal (across) dimension (ROWS)
  • the vertical (up and down) dimension (COLUMNS)
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20
Q

ROW = ________
COLUMN = ___________

A

dependent, independent

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21
Q

SUBTOTALS THAT ARE ADDED TO EACH COLUMN AND ROW IS CALLED _________

A

marginals

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22
Q

WHAT IS REPORTED AT THE INTERSECTION OF THE ROW AND COLUMN MARGINALS

A

the total number of cases

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23
Q

ON A TABLE, WHAT VARIABLE IS LISTED FIRST

A

the dependent variable

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24
Q

THE CONCEPT OF INDEPENDENCE

A

the relationship between the VARIABLES, not between SAMPLES

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25
Q

WHAT IS THE NULL HYPOTHESIS FOR CHI SQUARE

A

that the variables are INDEPENDENT

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26
Q

IF THE NULL HYPOTHESIS IS _____ AND THE VARIABLES ARE _________, THEN THERE SHOULD BE _________ DIFFERENCE BETWEEN THE EXPECTED AND OBSERVED FREQUENCIES

A

true, independent, little

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27
Q

IF THE NULL HYPOTHESIS IS ______, THERE SHOULD BE _______ DIFFERENCES BETWEEN THE EXPECTED AND OBSERVED FREQUENCIES

A

false, large

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28
Q

THE GREATER THE ________ BETWEEN EXPECTED AND OBSERVED FREQUENCIES, THE _____ LIKELY THAT THE VARIABLES ARE ______ AND _____ LIKELY THAT WE WILL BE ABLE TO _______ THE NULL HYPOTHESIS

A

differences, less, independent, more, reject

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29
Q

X^2(OBTAINED) = Σ (fo - fe) ^2 / fe

A

calculation of chi square

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30
Q

FE = ROW MARGINAL X COLUMN MARGINAL / N

A

expected frequency formula of each cell

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31
Q

STEP ONE : MAKING ASSUMPTIONS AND MEETING TEST REQUIREMENTS

A

model : independent random samples
- level of measurement is NOMINAL

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32
Q

STEP TWO : STATING THE NULL HYPOTHESIS

A

ho : the two variables are INDEPENDENT
(h1 : the two variables are DEPENDENT)

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33
Q

STEP THREE : SELECTING THE SAMPLING DISTRIBUTION AND ESTABLISHING THE CRITICAL REGION

A
  • the sampling distribution of sample chi squares are POSITIVELY SKEWED, with higher values of sample chi squares in the upper tail of the distribution
  • the critical region is established in the UPPER TAIL OF THE SAMPLING DISTRIBUTION
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34
Q

DF = (R-1)(C-1)

A

degrees of freedom formula

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35
Q

STEP FOUR : COMPUTING THE TEST STATISTIC

A

x^2 (obtained) = Σ (fo - fe) ^2 / fe

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36
Q

CHI SQUARE TEST OF STATISTICAL SIGNIFICANCE

A

tests the null hypothesis that the variables are INDEPENDENT in the population

37
Q

IF WE _______ THE NULL HYPOTHESIS, WE ARE CONCLUDING, WITH A KNOWN PROBABILITY OF ERROR (determined by alpha level), THAT THE VARIABLES ARE ________ ON EACH OTHER IN THE POPULATION

A

reject, dependent

38
Q

A _____ SMALL SAMPLE SIZE IS DEFINED AS ONE WHERE A _____ PERCENTAGE OF THE CELLS HAVE EXPECTED FREQUENCIES OF 5 OR LESS

A

small, high

39
Q

CONSIDERING TWO VARIABLES SIMULTANEOUSLY

A

relationship between variables

40
Q

RELATIONSHIP

A

2 variables are related if the distribution of cases in (or among) the values (or categories) of one variable differs depending on which value (or category) of the other variable is considered

41
Q

WHEN IS THERE A RELATIONSHIP

A

when there are two variables
- never when there’s one, three, four, five, etc

42
Q

RELATIONSHIP BETWEEN

A

the distributions differ

43
Q

NO RELATIONSHIP BETWEEN

A

distributions don’t differ

44
Q

NULL

A

no relationship

45
Q

OBSERVED FREQUENCIES

A

all we have is the null hypothesis of relationships
- shows some coordination

46
Q

EXPECTED FREQUENCIES

A

no coordination
- “what we think is in the world”

47
Q

X^2 (OBTAINED) = Σ (Fo - Fe)^2 / Fe

A

formula for x^2
- “how far is what i’m observing to what i expect”

48
Q

BECOMES MORE NORMAL = __________

A

becomes a sampling distribution

49
Q

PHI Φ

A

a chi square based measure of association
- appropriate for nominally measured variables that have been organized into a 2x2 bivariate the table

50
Q

MEASURES OF ASSOCIATION ARE DESCRIPTIVE STATISTICS THAT

A

summarize the overall strength of the association between 2 variables

51
Q

WHATS COMPUTED TO MEASURE THE STRENGTH OF THE ASSOCIATION

A

phi Φ

52
Q

Φ = √ X^2 / N

A

formula for phi Φ

53
Q

MEASURES OF ASSOCIATION

A

number that talks about the extent to the measures

54
Q

DISTRIBUTIONS NOT DIFFERING

A

0.0

55
Q

DISTRIBUTIONS DIFFERING AS MUCH AS POSSIBLE

A

1.0

56
Q

CORRELATIONS NEAR 0

A

weak

57
Q

CORRELATIONS NEAR 1

A

stronger

58
Q

LINEAR RELATIONSHIP

A

a relationship between 2 variables in which the observation points (dots) in the scatter gram can be approximated with a straight line

59
Q

REGRESSION LINE

A

the simple, best fitting straight line that summarizes the relationship between 2 variables

60
Q

SCATTERGRAM

A

graphic display device that depicts the relationship between 2 variables

61
Q

SLOPE (b)

A

the amount of change in one variable per unit change in the other

62
Q

TOTAL VARIATION

A

the spread of the Y scores around the mean of Y
- equal to Σ(Yi - Ybar)^2

63
Q

UNEXPLAINED VARIATION

A

the proportion of the total variation in Y that’s NOT accounted for by X

64
Q

Y INTERCEPT (a)

A

the point where the regression line crosses the y axis

65
Q

THE STATISTICAL TECHNIQUES OF CORRELATION AND REGRESSION ARE MORE APPROPRIATELY USED WITH HIGH QUALITY, PRECISELY MEASURED VARIABLES AT THE _____ ______ ________

A

interval ratio level

66
Q

WHICH SCORE IS ARRAYED ALONG THE HORIZONTAL AXIS

A

independent (X) value

67
Q

WHICH SCARES ARE ALONG THE VERTICAL AXIS

A

dependent (Y) variables

68
Q

2 REASONS WHY SCATTERGRAMS ARE USED

A
  1. provide at least impressionistic information about the existence, strength, and direction of the relationship of linearity
  2. the scattergram can be used to predict the score of. case on one variable from the score of that case on the other variable
69
Q

WHERE WOULD ALL DOTS LIE IN A PERFECT ASSOCIATION

A

all dots would lie on the regression line

70
Q

THE ________ OF THE BIVARIATE ASSOCIATION CAN BE JUDGED BY OBSERVING THE SPREAD OF DOTS AROUND THE _______ ______

A

spread, regression line

71
Q

AS ___ INCREASES, ___ ALSO INCREASES

A

X, Y

72
Q

IF THE RELATIONSHIP HAD BEEN NEGATIVE, THE REGRESSION LINE WOULD HAVE SLOPED IN THE _________ DIRECTION TO INDICATE THAT ______ SCORES ON ONE VARIABLE WERE ASSOCIATED WITH ____ SCORES ON THE OTHER

A

opposite, high, low

73
Q

THE OBSERVATION POINTS OR DOTS ON A SCATTERGRAM ___________.

A

must form a pattern that can be approximated with a straight line

74
Q

IF THE RELATIONSHIP IS NON LINEAR, YOU MIGHT NEED TO TREAT THE VARIABLES AS IF THEY WERE _______ RATHER THAN _______ IN LEVEL OF MEASUREMENT

A

ordinal, interval ratio

75
Q

THE MEAN OF ANY DISTRIBUTION OF SCORES IS THE POINT AROUND WHICH _____________

A

the variation of the scores, as measured by squared deviations, is minimized

76
Q

Σ(Xi - XBar) ^2

A

variance of x

77
Q

IF THE REGRESSION LINE IS DRAWN SO THAT IT TOUCHES EACH _____________, IT WOULD BE THE STRAIGHT LINE THAT COMES AS CLOSE AS POSSIBLE TO ALL THE SCORES

A

conditional mean of Y

78
Q

CONDITIONAL MEANS ARE FOUND BY

A

summing all Y values for each value of X and then dividing by all numbers of the cases

79
Q

THE Y INTERCEPT, OR THE POINT WHERE THE REGRESSION LINE CROSSES THE Y AXIS

A

a

80
Q

THE SLOPE OF THE REGRESSION LINE, OR THE AMOUNT OF CHANGE PRODUCED IN Y BY A UNIT CHANGE IN X

A

b

81
Q

SCORE OF INDEPENDENT VARIABLE

A

x

82
Q

THE POINT AT WHICH THE REGRESSION LINE CROSSES THE VERTICAL, OR Y, AXIS

A

y intercept (a)

83
Q

THE LEAST SQUARES REGRESSION LINE IS THE AMOUNT OF CHANGE PRODUCED IN THE DEPENDENT VARIABLE (Y) BY A UNIT CHNGW IN THE INDEPENDENT VARIABLE (X)

A

slope (b)

84
Q

IF THE VARIABLES HAVE A ______ ASSOCIATION, THEN CHANGES IN THE VALUE OF X WILL BE ACCOMPANIED BY SUBSTANTIAL CHANGES IN THE VALUE OF Y, AND THE SLOPE (b) WILL HAVE A _________ VALUE

A

strong, high

85
Q

THE ________ THE EFFECT OF X ON Y, THE _______ THE VALUE OF THE SLOPE (b)

A

weaker, lower

86
Q

IF THE TWO VARIABLES ARE UNRELATED, THE LEAST SQUARES REGRESSION LINE WOULD BE PARALLEL TO THE X AXIS, AND SLOPE (b) WOULD BE

A

0.0, line would have NO slope

87
Q

B = COV(X,Y) / VAR (X)

A

formula for slope (b)

88
Q

VERTICAL ABOVE MEAN

A

x

89
Q

DEVIATIONS FROM THE MEAN

A

“how far are my dispersions from the mean?”

soc 210 (1 decks)

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