5 Written Questions
5 Matching Questions
- standard deviation
- computing the S.D.
- ratio scales (#4, most complex---four properties)
- types of variables: discrete
- a measures of variability that divide the distribution of scores into four quarters.
GOOOOOOOOOOSH... this stuff blows my brain into tiny bits. I am praying this part isn't on the exam!!!!
- b have properties of identity, rank order, distance between numbers AND "additivity"
"additivity" means they can be added, subtracted, multiplied, divided... with meaningful results.
ratio scales have a zero point (see pg 41 for this... I don't get it... lol) This means that it measures things that start at zero. (spead for example, or money- you can have zero money in your account so a measure could be 0 to 5,000 to 10,000 and so on).
- c The square root of the variance. If the variance is 6.5, the SD is 2.55. It is the quintessential measure of variability for testing.
- d you can estimate the S.D. by taking the range of scores and dividing by 6 (the approximate number of standard deviations in a normal curve); e.g.,
high score = 76, low score = 10, range = 66
standard deviation (estimated) = 11
- e discrete variables have a finite range of values.
discrete variables are dichotomous if there are only 2 values possible (you will have a boy or a girl. You will flip heads or tails on a coin.)
discrete variables are polytomous if more than 2 values are possible (rolling dice, you could roll any value 2-12)
*in principle, discrete variables can be counted precisely without error.
5 Multiple Choice Questions
- ("the tail is the clue to the skew")
long tail pointing in the positive direction: positively skewed
long tail pointing in the negative direction: negatively skewed
- +1 S.D. = 84th percentile ("in a room of 100 people, about 16 will score higher")
+2 S.D. = 97th percentile
+3 S.D. = 99th percentile
-1 S.D. = 16th percentile ("in a room of 100 people, about 84 will score higher")
- 2 S.D. = 3rd percentile
- 3 S.D. = 1st percentile
- mean (statistical average)
median (lands in the middle of all scores listed in numerical order)
mode (most frequently occurring value in a distribution)
- the distance between the highest value in the bottom quartile and the highest value in the third quartile, thus covering the middle fifty percent of a distribution
- bell shaped
bilaterally symmetrical with each half containing 50% of the area under the curve
tails approach but never touch the baseline (thus extends to ± infinity)
unimodal (a single point of maximum frequency or maximum height-- ONE MODE.)
mean, median, mode coincide at the center of the distribution
5 True/False Questions
Variation and the "standard deviation" (S.D.) → The square root of the variance. If the variance is 6.5, the SD is 2.55. It is the quintessential measure of variability for testing.
ordinal scales (#2--two properties) → also known as equal-unit scales
they have the properties of identity, rank order AND the distance between numbers
(ex: see page 40 for an example about minutes and hours and days that is too complicated for me to rephrase... lol)
variability → "the degree to which the scores in a sample differ from each other or, as more commonly expressed, differ from the mean of the sample" (Penguin Dictionary of Psychology)
value of the normal curve → the most prominent probability distribution in stats
used throughout the natural and social sciences as a simple model for complex phenomena
user-friendly analytically (i.e., a large number of results can be derived from it)
based on the "central limit theorem" (i.e., under mild conditions a large number of random variables are distributed approximately normally)
"bell" shape makes it convenient for modeling a large variety of real world variables
Kurtosis: score variability → Kurtosis refers to the degree to which scores cluster about the mean (i.e., degree of variability in scores)
A normal curve (or distribution or variability of scores) is mesokurtic
Two other possibilities, platykurtic distributions and leptokurtic distributions