Univariate Stats Test 1

Front 1

mu =
x bar =
s =
s^2 =

Back 1

population average
sample average
sample standard deviation
sample variance

Front 2

skew:
which direction is a positive skew?

Back 2

departure from symmetry
a positive skew is to the left

Front 3

leptokurtic:
platykurtic:

Back 3

leptokurtic distribution has lots of tail
platykurtic distribution has lots of shoulder

Front 4

central tendency:
extremes have greatest effect on what statistic?

Back 4

best description of middle of distribution (mean, median, mode)
extremes affect the mean the most because median/mode are only concerned with number of values and not actual values

Front 5

central limit theorem

Back 5

Given a population with a finite mean (mu) and a finite variance (sigma^2), the sampling distribution of the mean will approach the normal distribution, with mean mu and variance (sigma^2/N), as N, the sample size, increases.

Front 6

given a population with the mean, mu, and a finite variance (sigma^2), ........

Back 6

the sampling distribution of the mean will approach the normal distribution with mean m and variance sigma^2/N as N, the sample size, increases

Front 7

DF for confidence interval:

Back 7

N-1

Front 8

DF for chi2 goodness of fit:

Back 8

g-1

Front 9

DF for chi2 test for independence:

Back 9

(rows-1)(columns-1)

Front 10

value for power in ANOVA:

Back 10

n-1

Front 11

chi2 goodness of fit is testing to see what? chi2 test for independence?

Back 11

goodness of fit: if events occurred by chance
independence: if 2 things are related

Front 12

how many dimensions in chi2 gf test? chi2 independence test?

Back 12

gf: 1 dimension with unlimited categories
independence: 2 dimensions with unlimited categories

Front 13

what type of error is it when the Ho is true, but you reject it?

Back 13

type one error; probability of occurring is alpha, 5%

Front 14

what type of error is it when the Ho is false, but you accept it?

Back 14

type two error; probability of occurring is beta,

Front 15

what does beta stand for?

Back 15

POWER! (the capacity for a type one or two error to occur)

Front 16

DF for critical f in ANOVA:

Back 16

numerator: g-1
denominator: N-g

Front 17

assumptions of ANOVA:

Back 17

1. normality (populations from which data is drawn are normally distributed)
2. homogeneity of variance (error variance in populations of each group are approx equal)
3. independent errors (scores are independent so errors are unrelated)

Front 18

power:

Back 18

capacity of a test to reject a false null.

Front 19

phi prime:

Back 19

measurement of effect size of experiment

Front 20

determinants of power:

Back 20

1. sample size
2. error variance (scores all over, but treated the same)
3. effect size (decaf coffee vs regular or decaf coffee vs poop)
4. alpha (larger alpha has more power)