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If scores are ______, not very dispersed, a _______ score is a good representative stat of a sample. If scores are _____ ______, the ______ may be problematic
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SIQR and IQR are used in conjunction with the _______
Median
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mean deviation
know how far an individual score is from the man
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Sum of squares
- take the deviation scores for each score in distribution, square them, then add them
- gives an average amount of variability
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Variance/mean square
- take the sum of squares and divide by degrees of freedom
- like sum of squares, no units associated with it
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standard deviation
- take the square root of the variance
- returns values back to original units
- measure of average variability of a set of scores
- goes along with the mean
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The shape of distribution
- sometimes not normally distributed
- can be skewed positive or negative
- if distribution is normal, each measure of central tendency is roughly the same, but not true if skewed
- in general, the mean is pulled towards the skew
- in this case median is preferred
- floor and ceiling effects
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properties of the mean
- if a constant is added or subtracted from every score, the mean is increased or decreased by that constant
- if every score is multiplied or divided by a constant, the mean will be as well
- sum of deviations from the mean will always equal 0
- Sum of the squared deviations from the mean will be less than the sum of squared deviations around any other point in the distribution
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Properties of the standard deviation
- if a constant is added or subtracted, the SD will not be affected
- if the score is multiplied or divided by a constant, so will the SD
- the SD from the mean will be smaller than the SD from any other point in the distribution
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Parametric
- branch of stats
- uses entire population
- involves parameters and distributions around those parameters
- Denoted by greek letters
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used with interval and ratio level data
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Nonparametric stats
- used when assumptions are violated
- robust
- nominal level data
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descriptive stats
- tell you about a distribution
- usually from a sample
- includes measures of central tendency
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inferential stats
- draw a sample from the population, try to make a conclusion about the population from the sample
- how likely is a given result
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What is R?
open-source, downloadable package that is useful for
- stat analysis
- visualization
- reporting
- writing own unique code
- sharing code with others
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Nominal data
- Nominal scales are used for labeling variables, without any quantitative value. “Nominal” scales could simply be called “labels.”
- yes/no
- black/white
- male/female
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ordinal data
t is the order of the values is what’s important and significant, but the differences between each one is not really known.
- very unhappy
- unhappy
- ok
- happy
- very happy
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interval data
Interval scales are numeric scales in which we know not only the order, but also the exact differences between the values. The classic example of an interval scale is Celsius temperature because the difference between each value is the same.
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ration data
tell us about the order, they tell us the exact value between units, AND they also have an absolute zero–which allows for a wide range of both descriptive and inferential statistics to be applied.
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