Flashcards in Part 3B Deck (34):

1

## sampling error

### random variability between observations or statistics that is simply due to chance

2

## how to assess sampling error:

### sampling distribution

3

## sampling distribution

### the distribution of a statistic over repeated sampling from a specified population (a distribution of means)

4

## what is the formal procedure for hypothesis testing?

###
1. start with sample of participants that is the same as a specific population (null hypothesis)

2. find out what population does

3. compare participants to that standard

5

## how are sampling distributions created?

### formed when samples of sample size n are repeatedly taken from a population

6

## properties of sampling distributions of sample means

###
1. the mean of the sample means is equal to the population mean

2. the standard deviation of the sample means is equal to the population standard deviation divided by the square root of the sample size n (standard error of the mean)

7

## the Central Limit Theorem

### the larger the sample size that we draw from a population, the more normal the sampling distribution of the sample means become regardless of shape of population

8

## Central Limit Theorem: if sample sizes of n greater than or equal to 30 are drawn from any population...

### then the sampling distribution of the sample means approximates a normal distribution

9

## Central Limit Theorem: if the population itself is normally distributed...

### the sampling distribution of the sample means is normally distributed for ANY sample size n

10

## what is the purpose of hypothesis testing?

### to consider the probability that the results of a study could have come about if the experimental procedure had no effect (i.e. if null hypothesis is true)

11

## statistical hypothesis

### a statement, or claim, about a population parameter

12

## the alternative hypothesis

### the hypothesis that participants did not come from the population of normal responders

13

## the null hypothesis

### the hypothesis that participants came from the population of normal responders

14

## null hypothesis and alternative hypothesis must:

### COMPLEMENT EACH OTHER

15

## level of significance

### maximum allowable probability of rejecting the null if it is true (the point at which the null is probably false) alpha=0.05

16

## critical values

### these present the point at which the null hypothesis is rejected (ex. reject when p<0.05)

17

## reject null if:

### we exceed the critical value

18

## test statistic

### the results of a statistical test relating observed scores (generally means) to a standardized distribution

19

## p-value (probability value)

### the probability of obtaining an observed test statistic (calculated from the sample data) with a value that extreme if the null hypothesis is true

20

## statistically significant

### a set of measurements or observations in a study is statistically significant if it is unlikely to have occurred by chance (ex. less than 5% chance)

21

## what are the types of hypothesis tests

### one-tailed or two-tailed

22

## one-tailed test

### rejects null if obtained value is too low or too high, only set one side/direction for rejection (i.e. Ha is DIRECTIONAL)

23

## two-tailed test

### rejects null when obtained value is too extreme in either direction (i.e. Ha is NON DIRECTIONAL) (divide each tail to get 1/2 alpha level p)

24

## left-tailed test

### Ha contains the symbol

25

## right-tailed test

### Ha contains the symbol >, alpha (critical region is the area to the right of the test statistic)

26

## Decision Rule based on test statistic (z)

###
z-observed>z-critical, reject Ho

z-observed

27

## conclusion of decision should always be phrased:

### in relation to null hypothesis

28

## to determine whether some factor is causal to the result, requires:

### conducting an experimental study

29

## at the end of the test, what are the two possible decisions?

### reject null hypothesis or fail to reject null hypothesis

30

## type I error

### null hypothesis rejected when it is true

31

## type II error

### nulls hypothesis is not rejected when it is false

32

## which error is preferable?

### type II error (better than claiming an effect in error)

33

## power

### probability of correctly rejecting false null hypothesis

34