chapter 7/8/9

Question 1

what is a z test

Answer 1

Determines the probability of obtaining a particular sample mean from a population just by chance

Question 2

what is the z test based on

Answer 2

The Z test is based on a theoretical concept called the “distribution of sample means”

Question 3

distribution of sample

Answer 3

A theoretical probability distribution that reflects the probability of obtaining different sample means from a population (given a particular sample n and given a known μ and σ .)

Question 4

what can you do if you have the distribution of sample?

Answer 4

You can calculate the mean of the means: The Expected Mean (also often called the “Grand mean”).
It will be equal to μ (the pop mean).

Question 5

what is the standard error of the mean?

Answer 5

the SD of all the means instead of scores. On average how far the sample means deviate from the grand mean

Question 6

is the Standard error of the mean much smaller or larger than the SD of each sample

Answer 6

the SEM will be much smaller than the SD of each sample. sample means tend to be much more consistent less variable than raw scores

Question 7

what happens to standard error of the mean as sample size increases?

Answer 7

it decreases the larger the sample, the less likely it will be to deviate substantially from μ

Question 8

central limit theorem

Answer 8

Sample means drawn from a population will be normally distributed, even if the parent population is not normal.

(As long as sample n = ~ 30 or larger)

Question 9

are extreme sample means common

Answer 9

no much rarer than extreme scores

Question 10

is the amount that individual sample means will deviate from the grand mean, small or large

Answer 10

small especially when samples are large

Question 11

if the sample n is large will there be small differences between M and μ that are found by chance?

Answer 11

If the sample n is large, even smallish differences between M and μ are unlikely to be found by chance.

Question 12

what is happening when M does not exactly equal u

Answer 12

There are 2 possibilities:
1.) Sampling Error: by chance we obtain a sample mean that does not equal the population mean

2.) The sample is truly different from the population (due to an experimental manipulation or maybe because it is actually a different population. This may be a big deal depending on the explanation.)

Question 13

what does it mean when p < .05?

Answer 13

The sample seems to represent a different population than the comparison population, the difference is statistically significant

Question 14

type I error

Answer 14

rejecting the null hypothesis when it’s actually true or a false positive

Question 15

Type II error

Answer 15

failing to reject the null hypothesis (retaining the null) when it’s actually false. false negative

Question 16

confidence intervals

Answer 16

Significance testing tells us if the sample means is different from the population mean.

Confidence intervals are used to estimate the likely mean of the population represented by the sample.

Question 17

when do you use a z test?

Answer 17

when you are comparing a sample mean to a known μ, and you know σ.

Question 18

when do you use one sample t test

Answer 18

when you are comparing a sample mean to a known μ, and you don’t know σ.

Question 19

when do you use a two-sample t test?

Answer 19

Comparing two sample means, don’t know μ or σ

Question 20

what is the denominator of a one-sample t test

Answer 20

Denominator called the estimated
standard error of the mean: sx

Question 21

pearsons r

Answer 21

is the most common way of measuring a linear correlation. It is a number between -1 and 1 that measures the strength and direction of the relationship between two variables.

Question 22

what is the denominator of a z test

Answer 22

the average distance between M and u that would be expected if the null was true

Question 23

As alpha increases, what happens to the risk of type 1 error? Liklihood of rejecting the null?

Answer 23

both increase

Question 24

What is the numerator of the z score formula?

Answer 24

actual distance between M and u

Question 25

what is the z obtained

Answer 25

the difference between the observed sample mean and the hypothesized population mean divided by the standard error of the mean

Question 26

what does it mean when the z obtained is in the critical region

Answer 26

reject the null hypothesis

Question 27

what does it mean when the data is not in the critical region?

Answer 27

sample data are not located in the critical region; the data do not provide strong evidence that the null hypothesis is wrong; decision: fail to reject the null hypothesis

Question 28

what it means to reject the null

Answer 28

It is very unlikely* (p < .05) that the difference between your groups is due to chance

Question 29

assumptions of the z test

Answer 29

1.) data are interval or ratio
2.) you know both the mean and the standard deviation of the population.

Question 30

power

Answer 30

The probability of rejecting the null hypothesis if the null hypothesis is false.

Question 31

power and sample size relationship?

Answer 31

The larger your sample size, the more power.

Question 32

power and effect size

Answer 32

The strength of the relationship that truly exists between IV and DV. (How far apart are the means in the population?)

Question 33

cohens d

Answer 33

form of effect size. the difference between two means divided by a standard deviation for the data

Question 34

difference between t test and z test

Answer 34

z-tests (population) are used when we have large sample sizes (n > 30), whereas t-tests are most helpful with a smaller sample size (n < 30) (sample).