Stats review

Question 1

Population variance:

Answer 1

the average of the distances from the mean within a population distribution of scores

Question 2

Parameter:

Answer 2

numerical characteristic of a population distribution of scores

Question 3

Sample variance:

Answer 3

the average of the distances from the mean within a sample distribution of scores

Question 4

Statistic:

Answer 4

numerical characteristic of a sample distribution of scores

Question 5

sigma squared

Answer 5

population variance

Question 6

Standard normal distribution:

Answer 6

X is distributed normally with a mean of 0 and variance of 1

Question 7

standard normal distribution +/- 1 SD contains __% of scores

Answer 7

68

Question 8

standard normal distribution +/- 2 SD contains __% of scores

Answer 8

95

Question 9

standard normal distribution +/- 3 SD contains __% of scores

Answer 9

99

Question 10

Random:

Answer 10

each observation has an equal and independent probability of being selected

Question 11

Sampling distribution:

Answer 11

frequency distribution of a particular statistic (ex. Sample mean) obtained from repeated sampling from the population

Question 12

standard error of mean

Answer 12

standard deviation of sampling distribution of mean

Question 13

how to interpret standard error of mean?

Answer 13

average distance of possible sample means from the true population mean u

Question 14

as sample size increases, standard error of mean ____

Answer 14

decreases

Question 15

law of large numbers

Answer 15

As sample size increases, x bar will approach u

Question 16

95% Confidence interval

Answer 16

In repeated samples, 95 of 100 confidence intervals calculated in this way will contain the true value of the mean difference in the population.

Question 17

Central limit theorem: what happens as sample size increases?

Answer 17

As sample size N increases, the sampling distribution of the mean more closely approximates a normal distribution (even if the original distribution of X is not normal) AND the mean of the sampling distribution of the mean will more closely resemble the population mean

Question 18

p-value:

Answer 18

the probability of finding a test statistic more extreme than the one we found if the null hypothesis is true

Question 19

critical value

Answer 19

point at which you would reject the null if sample means exceeds the critical value

Question 20

Type I error

Answer 20

reject the null hypothesis when the null hypothesis is true (alpha)

Question 21

Type II error

Answer 21

fail to reject the null hypothesis when the null hypothesis is false (beta)

Question 22

alpha is equal to what type of error?

Answer 22

1

Question 23

beta is equal to what type of error?

Answer 23

2

Question 24

Power:

Answer 24

probability of rejecting the null hypothesis when it is false
probability of detecting an effect when the effect exists

Question 25

Relationship between power and beta?

Answer 25

power=1-beta

Question 26

What happens to power when alpha increases?

Answer 26

increases

Question 27

what happens to power when sample size increases? and why?

Answer 27

as n increases, power will increase due to smaller standard error

Question 28

what happens to power when population SD increases

Answer 28

if sigma increases, power decreases

Question 29

what happens to power when effect size increases?

Answer 29

As effect size increases, power increases

Question 30

Which has more power: one-tailed or two-tailed test?

Answer 30

One-tailed

Question 31

one-sample z test? which distribution does it use?

Answer 31

inference about a single population value when standard deviation is KNOWN

*uses standard normal distribution

Question 32

t-test? which distribution does it use?

Answer 32

A statistical test used to make an inference about one or two values when standard deviation is UNKNOWN that uses the t-distribution

Question 33

when does t distribution approach normal distribution?

Answer 33

as degrees of freedom increases

Question 34

degrees of freedom

Answer 34

number of independent pieces (values) free to vary given the summary statistic (N-number of things you are estimating)

Question 35

correlation

Answer 35

Correlation: linear relationship between x and y; between -1 and 1, implies direction and strength of the relationship, **independent of the scales of x and y

Question 36

true or false: covariance is independent of the scales of x and y

Answer 36

false

Question 37

true or false: correlation is independent of the scales of x and y

Answer 37

true

Question 38

how to calculate t statistic?

Answer 38

coefficient/standard error

Question 39

how do you standardize a variable?

Answer 39

subtract mean and then divide by sd