quantitative data management - statistics

Question 1

raw data

Answer 1

all of the individual data points, must be made sense of

Question 2

data reduction

Answer 2

can add up the scores for each person, then create the mean. then see how variable the data is (how spread out) we can then answer the questions

Question 3

measure of central tendency

Answer 3

usually the mean - an average
a single value that describes a set of data.

Question 4

quasi experiments

Answer 4

can conclude a mean of the whole sample. useful to compare to pre-existing groups.
male v female etc

Question 5

variability in scores

Answer 5

too see how much the lowest and highest is - how much scores vary.

Question 6

variance

Answer 6

a large variance is a larger distance from the mean and vice versa.
we must quantify variance

Question 7

calculating variance

Answer 7

calculate the mean, subtract from each ppt score to work out the deviation, square each deviation, add up the squared deviations of each ppt, divide squared deviation by 1 less number than ppts. square root that. = standard deviation

Question 8

what does standard deviation tell us

Answer 8

e.g. 2.7 SD shows that most ppts recall scores where within 2.7 words above or below the mean e.g. 10

Question 9

COHENS d effect size

Answer 9

group 1 M- group 2 M / SD pooled
small effect - 0.2
medium - 0.5
large - 0.8
big or small difference in variance.