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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
Negatively skewed
Many high scores
26
Positively skewed
Many low scores
27
Bimodal
A distribution with 2 peaks. Usually an indication that sample contains two distinct subgroups.
28
Rectangular distribution
Uniform score distribution (like graphing ranks if there are no tied ranks)
29
Bar graph
Graph appropriate for nominal data with x-axis reflecting categories instead of scores
30
Pie graph
Circle graph with slices representing percentages
31
Inflection points
Changes in the curve direction of a graphical distribution.
32
Normal curve
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
In a normal curve the mean, media , and mode...
All fall at the same point
34
Asymptotic
Curve never reaches x-axis allowing for scores in tails of distribution.
35
Limits to normal curve
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
Normal curve is robust to minor violations of its shape assumptions
We can use the percentages associated with the normal curve to interpret data even when our data are only approximately normally distributed.
37
Dispersion
Measures of spread or variability within a set of scores
38
Central tendency
Summarize in a single value the centrality of the data
39
Mode
Most frequent score
40
Mo
Mode
41
Limits to mode
Least stable of 3 measures of central tendency. No additional statistics are based on mode.
42
Median
Middle score
43
Mdn
Median
44
Mean
Average score
45
M
Mean for samples
46
m (mew)
Mean for populations
47
Limits to mean
Most sensitive to score aberrations/outliers
48
Outlier
Score that is way out of line with rest of the data
49
What happens to median, mean, and mode in skewed data?
Mode remains stable, mean pulled toward tail, median falls between mean and mode.
50
If mean is lower than mode, distribution is...
Negatively skewed
51
If mean is higher than mode...
Distribution is positively skewed
52
Report the mean unless...
1. There are unknown values. 2. The distribution is seriously skewed 3. Distribution is bimodal or multimodal
53
Report what measure of central tendency for multimodal distributions?
1 mode for each sub-group (2 modes for bimodal)
54
Range
Difference between the lowest and highest scores in a data set.
55
Limits to range
Subject to vagaries of cases that happen to fall at either end of a particular sample. No other statistics are based on range.
56
Variance
Average area distance from the mean (average of squared deviation scores).
57
Deviation score
Amount by which a raw score deviates from the mean
58
Standard deviation
Average linear distance from the mean. Square root of the variance.
59
Average absolute deviation
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
Standard score
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
Z score
Raw score re-expressed in standard deviation units. The number of standard deviation units that a score is above or below the mean
62
Rescale
Change the scale of data to covert to different measurement
63
Z score accounts for...(3 things)
Central tendency (M), dispersion (s), and sample size (N)
64
What score allows for comparison across differing tests?
Z score
65
Transformation
An adjustment applied equally to all scores in a set
66
Effect on the mean of adding or subtracting a constant from every score
Mean goes up or down by same amount
67
Effect oh mean of multiplying or dividing every score by a constant
Mean is multiplied or divided by same amount
68
Effect on standard deviation of adding or subtracting a constant from every score
Standard deviation stays the sams
69
Effect on standard deviation of multiplying or dividing every score by a constant
Standard deviation is multiplied or divided by same amount
70
Probability
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
Equally likely model
Generating event yields possible outcomes that are equally likely (e.g coin tossing)
72
Mutually exclusive outcome
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
When does the addition theorem apply?
When outcomes are mutually exclusive
74
Addition theorem
The probability of any of the possible outcomes occurring on a particular trial is the sum of their individual probabilities
75
Ideoendent outcome
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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