W3 - Chapter 3 - DN Flashcards

1
Q

arithmetic mean

A
  • a measure of central tendency
  • derived by calculating an average of all scores in a distribution
  • also called the mean
    p. 89
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2
Q

average deviation

A
  • a measure of variability
  • derived by
    • summing the absolute value of all the scores in a distribution and
    • dividing by the total number of scores

p. 94

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3
Q

bar graph

A
  • a graphic illustration of data
  • numbers indicative of frequency are set on the vertical axis
  • categories are set on the horizontal axis
  • the rectangle bars that describe the data are typically noncontigous
    p. 85
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4
Q

bimodal distribution

A
  • a distribution where the central tendency consists of
    • two scores
    • occurring an equal number of times
    • and are the most frequently occurring scores in the distribution

p. 91

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5
Q

bivariate distribution

A
  • a graphic representation of correlation
  • accomplished by the simple graphing of the coordinate points for values of
    • the X-variable and
    • the Y-variable
  • also known as a
    • scatterplot
    • scatter diagram
    • scattergram

p. 111

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6
Q

coefficient of correlation

A
  • symbolised by **r **
  • the correlation coefficient is an index of the strength of the linear relationship between two continous variables
  • expressed as a number
    • can range from -1 to +1
  • most frequently used statistic to calculate is the Pearson r
    p. 106
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7
Q

coefficient of determination

A
  • a value indicating how much variance is shared by two variables
  • this value is obtained by
    • squaring the obtained correlation coefficient
    • multiplying by 100 and
    • expressing the result as a percentage
  • this indicates the amount of variance accounted for by the correlation coefficient
    • i.e., “total variance explained”

p.109

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8
Q

correlation

A
  • an expression of the degree and direction of relationship (correspondence) between two variables
  • where each variable is continuous in nature
    p. 106-116
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9
Q

curvilinearity

A
  • the degree to which a graph or scatterplot is characterized by curvature
    p. 111
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10
Q

distribution

A
  • in a psychometric context
  • a set of test scores arrayed for recording or study

p.83

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11
Q

dynamometer

A
  • an instrument used to measure the strength of hand grip
    p. 82
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12
Q

effect size

A
  • a statistic used to express
  • the strength of a relationship or
    • the **magnitude **of the differences in data
  • in meta-analysis - this statistic is most typically a correlation coefficient
    p. 115
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13
Q

error

A
  • all of the factors (other than what a test purports to measure) that contribute to scores on a test
  • error is a variable that exists on all testing and assessment
    p. 78-79
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14
Q

frequency distribution

A
  • a tabular listing of
    • scores
    • along with the number of times each score occurred

p.83-85

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15
Q

frequency polygon

A
  • a graphic illustration of data
  • frequency numbers set on the vertical axis
  • test scores or categories are set on the horizontal axis
  • data is described by a continous line connecting all of the points where the test scores or categories meet frequencies
    p. 85,86
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16
Q

graph

A
  • a diagram or chart
  • composed of lines, points, bars, or other symbols that describe and illustrate data

p.85

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17
Q

grouped frequency distribution

A
  • a tabular summary of test scores
  • the test scores are grouped by intervals
  • also referred to as class intervals
    p. 84-85
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18
Q

histogram

A
  • a graph with vertical lines drawn at the true limits of each test score (or class interval)
  • these lines form a contigous rectangle
    p. 85,86
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19
Q

interquartile range

A
  • an ordinal statistic of variability
  • equal to the difference between the third & first quartile points in a distribution that has been divided into quartiles
    p. 94
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20
Q

interval scale

A
  • a system of measurement
  • all items are rank-ordered into equal intervals
  • every unit on the scale is equal to every other
  • there is no absolute zero point
    • this precludes mathematical operations on the data

p.81

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21
Q

kurtosis

A
  • an indication of the nature of the steepness of the centre of the distribution
    • i.e., peaked vs flat

p.97-98

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22
Q

leptokurtic

A
  • a description of the kurtosis of a distribution that is relatively peaked at its centre
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23
Q

linear transformation

A
  • in psychometrics
  • a process of changing a score such that
    • the new score has a direct numerical relationship to the original score
    • the magnitude of the difference between the new score & other scores on the scale parallels the magnitude of differences on the scale from which it was derived
  • contrast with nonlinear transformation
    p. 104
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24
Q

mean

A
  • a measure of central tendency
  • derived by calculating an average of all scores in a distribution
  • also called an arithmetic mean
    p. 89
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25
Q

measurement

A
  • assigning numbers or symbols to characteristics of people or objects
    • according to rules

p.78-79

26
Q

measure of central tendency

A
  • one of three statistics indicating the average or middlemost score between the extreme scores in a distribution
  1. mean - ratio level
  2. median - ordinal (takes the order of scores into account)
  3. mode - nominal

p.89

27
Q

measure of variability

A
  • a statistic indicating how scores in a distribution are scattered or dispersed
  • common measures of variability are
    • range
    • standard deviation
    • variance

p.92

28
Q

median

A
  • a measure of central tendency
  • derived by identifying the middlemost score in a distribution
    p. 89-91
29
Q

mesokurtic

A
  • a description of the kurtosis of a distribution
    • that is neither extremely peaked nor flat in its centre

p.97

30
Q

meta-analysis

A
  • a family of techniques
  • used to statistically combine information across studies
  • to produce single estimates of the statistics being studied
    p. 115
31
Q

mode

A
  • a measureof central tendency
  • derived by identifying the most frequently occurring score in a distribution
    p. 89, 91-92
32
Q

negative skew

A
  • when relatively few scores fall at the lower end of the distribution
  • negatively skewed exmination results may indicate the test was too easy
    • some more difficult questions would better discriminate between scores at the higher end

p.97

33
Q

nominal scale

A
  • a system of measurement
  • all things being measured are classified or categorised, based on one or more distinguishing characteristics
  • placed into mutually exclusive & exhaustive categories
    p. 79-80
34
Q

nonlinear transformation

A
  • in psychometrics
  • a process of changing a score such that
    • the new score does not necessarily have a direct numerical relationship to the original score, and
    • the magnitude of the diffferences between the new score & the other scores on the scale, may not necessarily parallel the magnitude of differences of those from the original scale
  • contrast with linear transformation
    p. 104
35
Q

normal curve

A
  • bell-shaped, smooth, mathematically defined curve
  • highest at the centre & gradually tapered on both sides - approaching but never touching the horizontal axis
    p. 85, 87, 98
36
Q

normalized standard score scale

A
  • conceptually, the end product of “stretching” a skewed distribution into the shape of a normal curve
  • usually through a non-linear transformation
    p. 104-106
37
Q

normalizing a distribution

A
  • a statistical correction applied to distributions meeting certain criteria
    • for the purpose of approximating a normal distribution
    • thus making the data more readily comprehensible or manipulable

p.104

38
Q

ordinal scale

A
  • a system of measurement , where all things being measured can be rank-ordered
  • the rank-ordering implies nothing about how much greater one ranking is than another
  • no absolute zero point on the scale
  • most scales in psychology & education are ordinal
    p. 80-81
39
Q

outlier

A
  1. an extremely atypical plot point in a scatterplot
  2. any extremely atypical finding in research

p.111

40
Q

Pearson r

A
  • a widely used statistic for obtaining an index of the relationship between two variables
    • when that relationship is linear and
    • the two correlated variables are continuous (i.e., can theoretically take any value)
  • also known as
    • the Pearson coefficient of product-moment correlation and
    • the Pearson correlation coefficient
41
Q

platykurtic

A
  • a description of the kurtosis of a distribution that is relatively flat in its centre
    p. 97
42
Q

positive skew

A
  • when relatively few of the scores fall at the high end of the distribution
    • positively skewed examination results may indicate the test was too difficult
    • some easier questions would better discriminate at the lower end of the distribution

p.97

43
Q

quartile

A
  • one of the three dividing points between the four quarters of a distribution
  • each typically labelled
    • Q1
    • Q2
    • Q3
    • Q4

p.93

44
Q

range

A
  • a descriptive statistic of variability
  • derived by calculating the difference between the highest & lowest scores in a distribution
    p. 93
45
Q

rank-order/rank-difference correlation coefficient

A
  • an index of correlation
  • statistic of choice when
    • sample size is small, and
    • both sets of measurement are ordinal
  • also referred to as the Spearman’s rho
    p. 110-111
46
Q

ratio scale

A
  • a system of measurement where all things being measured can be rank-ordered
  • the rank-ordering does imply something about exactly how much greater one ranking is than another
  • equal intervals exist between each number on the scale
  • all mathematical operations can be performed meaningfully
    • because a true zero point exists
  • few scales in psychology & education use ratio scales
    p. 81-83
47
Q

raw score

A
  • a straight forward, unmodified accounting of performance
  • usually numerical
  • typically used for evaluation or diagnosis
48
Q

scale

A
  • 1) a system of ordered numerical or verbal descriptors
    • usually occurring at fixed intervals
    • used as a reference standard in measurement
  • 2) a set of numbers or other symbols whose properties model empirical properties of the objects or traits to which numbers or other symbols are assigned
49
Q

scatter diagram

A
  • a graphic description of correlation
  • achieved by graphing the coordinate points for the two variables
  • also referred to as a
    • scatterplot
    • scattergram, or
    • bivariate distribution

p.111

50
Q

scattergram

A
  • a graphic description of correlation
  • achieved by graphing the coordinate points for the two variables
  • also referred to as
    • scatterplot
    • scatter diagram or
    • bivariate distribution

p.111

51
Q

scatterplot

A
  • a graphic description of correlation
  • achieved by graphing the coordinate points for the two variables
  • also referred to as
    • scatter diagram
    • scattergram, or
    • bivariate distribution

p.111

52
Q

semi-interquartile range

A
  • a measure of variability
  • equal to the
    • interquartile range divided by two

p.94

53
Q

skewness

A
  • an indication of the nature & extent to which symmetry is absent in a distribution
  • a distribution is said to be
    • skewed positively when relatively few scores fall at the positive end and
    • skewed negatively when relatively few scores fall at the negative end

p.96-97

54
Q

Spearman’s rho

A
  • an index of correlation
  • statistic of choice when
    • sample size is small, and
    • both sets of measurement are ordinal
  • also referred to as the
    • rank-order correlation coefficient, and
    • rank-difference correlation coefficient

p.110-111

55
Q

standard deviation

A
  • a measure of variability
  • equal to the square root of the averaged squared deviations about the mean
  • also equal to the square root of the variance
    p. 94-96
56
Q

standard score

A
  • a raw score that has been converted from one scale into another
  • the new scale has
    • arbitrarily set M & SD
    • is more widely used & readily interpretable
  • examples of standard scores are
    • z scores
    • T scores
57
Q

stanine

A
  • a standard score derived from a scale with
    • a mean of 5 and
    • a standard deviation of approx. 2

p.103-104

58
Q

T score

A
  • a standard score
  • calculated using a scale with
    • a mean set at 50 and
    • a standard deviation set at 10
  • used by the developers of the MMPI
  • named for Thorndike
    p. 103, 429
59
Q

tail

A
  • the area on the normal curve between
    • 2 and 3 standard deviations above the mean, and
    • -2 and -3 standard deviations below the mean
  • a normal curve has two tails
    p. 101
60
Q

variability

A
  • an indication of how scores in a disrtibution are scattered or dispersed
    p. 92-96
61
Q

variance

A
  • a measure of variability
  • equal to the
    • arithmetic mean of the squares of the differences
    • between the scores in a distribution
    • and their mean

p.95, 146

62
Q

z score

A
  • a **standard score **
  • derived by calculating the difference between
    • a particular raw score & the mean
    • and then dividing by the standard deviation
  • a z score expresses a score in terms of the number of standard deviation units the raw score is below or above the mean of the distribution
    p. 102-103