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1. Psychology > Statistics Alive! > Flashcards

Statistics Alive! Flashcards

1
Q

Kurtosis

A

Height of a distribution is affected by too many or too few middle scores

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2
Q

Leptokurtic

A

A distribution with many middle scores

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3
Q

Platykurtic

A

A distribution with few middle scores

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4
Q

Nominal scale

A

Classifies cases into categories

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5
Q

Ordinal scale

A

Ranks scores by degree to which they possess the measured trait

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6
Q

Interval scale

A

Distances between adjacent scores are equal and consistent throughout the scale. (equal-interval scale)

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7
Q

Ratio scale

A

Interval scale with addition of absolute zero point.

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8
Q

Continuos variable

A

Variables where values could theoretically fall between adjacent scale units (height, weight, time)

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9
Q

Discrete data

A

Values that cannot theoretically fall between adjacent scale units (people, photos, etc)

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10
Q

Real limit

A

Half the scale’s unit (real limit opposed to observed scores)

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11
Q

Frequency table

A

Lists each observed score along with number of cases falling at each score

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12
Q

Cumulative frequency table

A

Shows how many scores are at or below (or at or above) any given score

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13
Q

Relative frequency or percentage table

A

Gives each score’s frequency relative to 100% (values will all be between 0-100).

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14
Q

Cumulative relative frequency or cumulative percentage table

A

Shows percentage above or below a given score

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15
Q

Grouped frequency table

A

Frequency table with score intervals. Can show patterns but have to get right size intervals (not too big or small) by guess and check.

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16
Q

Percentile rank table

A

Indicates percentage of cases falling at or below a given score (not below a given score)

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17
Q

Percentile

A

The score falling at a particular percentile rank (can be any score on table while percentages will be between 0-100)

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18
Q

Stem-and-leaf display

A

Hybrid between table and graph with left column indicating first digit of a score and right column indicating every instance of the next digit

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19
Q

Abscissa

A

X-axis

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20
Q

X-axis

A

Abscissa

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21
Q

Ordinate

A

Y-axis

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22
Q

Y-axis

A

Ordinate

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23
Q

Frequency curve or line graph

A

Midpoints of data connected by a line without bars

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24
Q

Skewed

A

Asymmetric distribution with a single peak

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25
Q

Negatively skewed

A

Many high scores

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26
Q

Positively skewed

A

Many low scores

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27
Q

Bimodal

A

A distribution with 2 peaks. Usually an indication that sample contains two distinct subgroups.

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28
Q

Rectangular distribution

A

Uniform score distribution (like graphing ranks if there are no tied ranks)

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29
Q

Bar graph

A

Graph appropriate for nominal data with x-axis reflecting categories instead of scores

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30
Q

Pie graph

A

Circle graph with slices representing percentages

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31
Q

Inflection points

A

Changes in the curve direction of a graphical distribution.

32
Q

Normal curve

A

Symmetric bell-shaped curve having inflection points at exactly 1 standard deviation above and 1 standard deviation below the mean. At the points indicated, steepness of the curve changes from steeply down to gently out.

33
Q

In a normal curve the mean, media , and mode…

A

All fall at the same point

34
Q

Asymptotic

A

Curve never reaches x-axis allowing for scores in tails of distribution.

35
Q

Limits to normal curve

A

Only a theoretical distribution. How scores would distribute if infinite scores were collected. The smaller the sample size, the greater the deviation from percentages associated with normal curve.

36
Q

Normal curve is robust to minor violations of its shape assumptions

A

We can use the percentages associated with the normal curve to interpret data even when our data are only approximately normally distributed.

37
Q

Dispersion

A

Measures of spread or variability within a set of scores

38
Q

Central tendency

A

Summarize in a single value the centrality of the data

39
Q

Mode

A

Most frequent score

40
Q

Mo

41
Q

Limits to mode

A

Least stable of 3 measures of central tendency. No additional statistics are based on mode.

42
Q

Median

A

Middle score

43
Q

Mdn

44
Q

Mean

A

Average score

45
Q

M

A

Mean for samples

46
Q

m (mew)

A

Mean for populations

47
Q

Limits to mean

A

Most sensitive to score aberrations/outliers

48
Q

Outlier

A

Score that is way out of line with rest of the data

49
Q

What happens to median, mean, and mode in skewed data?

A

Mode remains stable, mean pulled toward tail, median falls between mean and mode.

50
Q

If mean is lower than mode, distribution is…

A

Negatively skewed

51
Q

If mean is higher than mode…

A

Distribution is positively skewed

52
Q

Report the mean unless…

A
  1. There are unknown values. 2. The distribution is seriously skewed 3. Distribution is bimodal or multimodal
53
Q

Report what measure of central tendency for multimodal distributions?

A

1 mode for each sub-group (2 modes for bimodal)

54
Q

Range

A

Difference between the lowest and highest scores in a data set.

55
Q

Limits to range

A

Subject to vagaries of cases that happen to fall at either end of a particular sample. No other statistics are based on range.

56
Q

Variance

A

Average area distance from the mean (average of squared deviation scores).

57
Q

Deviation score

A

Amount by which a raw score deviates from the mean

58
Q

Standard deviation

A

Average linear distance from the mean. Square root of the variance.

59
Q

Average absolute deviation

A

Take absolute value of each deviation rather than squaring. Then sum and average. (compare to variance/SD). Does not fall in known locations on normal curve and infrequently used.

60
Q

Standard score

A

Score expressed in standardized unit of measurement in interval measure. Tells value of a score relative to all other scores (and central tendency and dispersion scores)

61
Q

Z score

A

Raw score re-expressed in standard deviation units. The number of standard deviation units that a score is above or below the mean

62
Q

Rescale

A

Change the scale of data to covert to different measurement

63
Q

Z score accounts for…(3 things)

A

Central tendency (M), dispersion (s), and sample size (N)

64
Q

What score allows for comparison across differing tests?

65
Q

Transformation

A

An adjustment applied equally to all scores in a set

66
Q

Effect on the mean of adding or subtracting a constant from every score

A

Mean goes up or down by same amount

67
Q

Effect oh mean of multiplying or dividing every score by a constant

A

Mean is multiplied or divided by same amount

68
Q

Effect on standard deviation of adding or subtracting a constant from every score

A

Standard deviation stays the sams

69
Q

Effect on standard deviation of multiplying or dividing every score by a constant

A

Standard deviation is multiplied or divided by same amount

70
Q

Probability

A

Relative frequency of a particular outcome occurring over an infinite number of trials or occasions. Expressed as a proportion from .00 to 1.00

71
Q

Equally likely model

A

Generating event yields possible outcomes that are equally likely (e.g coin tossing)

72
Q

Mutually exclusive outcome

A

Outcome of a particular trial precludes any other outcome for that same trial (as opposed to embedded [college student and sophomore] or overlapping [college student and employee] outcomes)

73
Q

When does the addition theorem apply?

A

When outcomes are mutually exclusive

74
Q

Addition theorem

A

The probability of any of the possible outcomes occurring on a particular trial is the sum of their individual probabilities

75
Q

Ideoendent outcome

A

Outcome of one trial had no relation to the outcome of another trial. Always refers to series of trials.

1. Psychology (13 decks)

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