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Flashcards in Midterm 1 Deck (52):
1

which of the following is true about a 95 confidence interval of the mean of a given sample.

There is a 95 chance that the population mean will fall within the limits of the confidence interval.

2

What does a significance test tell us?

There is an effect in the population of sufficient magnitude to be scientifically interesting.

3

A type 1 error....

We conclude that there is a meaningful effect in the population when in fact there is not

4

A null hypothesis is....

Predicts that the experimental treatment will have no effect.

5

What does a box plot not display?

The mean

6

Which of the following is least affected by outliers....

The median

7

What does it mean when a researcher rejects a null hypothesis at the .05 level?

There is less than 5% chance of getting such an extreme result by chance if the null hypothesis is true.

8

The results of the study are not extreme enough to reject the null hypothesis...

None of the above, the results are inconclusive.

9

Failing to reject the null hypothesis when the research hypothesis is true is referred to as a...

A type 2 error.

10

In a histogram the vertical dimension shows....

Frequency....

11

In a distribution of Z scores the mean is always

zero and the standard deviation is always 1

12

Interval scales of measurment

Have equal distant scales...

13

example of a ratio scale

Physical distance, there can be a true zero.

14

The mean is an appropriate measure when....

The data is normally distributed, interval or ratio scale, date in which the mean, median and mode are all equal.

15

Small overlap

Increase power

16

A small sample size

Decrease power

17

A large population standard deviation

Decrease power

18

Using a higher significance level ex 99%

Decrease power

19

P-Value

You can't be absolute

20

Confidence level and power

If you increase confidence level, you decrease power because you have to prove more.....

21

P value

You can use it to see if data is significant but can't say if it's true for certain.

22

Repetition of experiment

it doesn't matter independent won't increase power.

23

Large N sample

Sample means will be approximately equal to the population mean.

24

larger N

the more normal the sampling distribution

25

You need to know the sample size and the population mean to determine the

standard deviation

26

SD goes up

power goes down

27

Sampling size goes up

power goes up

28

And =

multiply

29

The mean of a sample distribution is equal to

population not sample mean.

30

Confi int

Consist of a range of values that act as good estimates of the unknown population parameter.

31

Confi int

A major factor in determining the length of a confidence interval is the size of the sample.

32

Sampling observations

From a sampling distribution comes from a theoretical population that is normally distributed.

33

Normal distribution

mean, median and mode is the same.

34

Density

The height of the curve at different values of X

35

Bayes theorem

A theorem that tells us how to accumulate information to revise est. of probabilities.

36

Binomial distribution

Deals with situations in which each of the independent trials results in one of two mutually exclusive outcomes.

37

Q-Q

Test for normal distribution

38

Conditional probability

One event will occur given that some other event occurred.

39

innerfence

1.5x the interquartile range.

40

Galton

Gave the normal distribution a central role in psychological theory. Especially the theory of mental abilities.

41

mu

is the population mean.

42

kernel density plot

Ignore mean and standard deviation.

43

Problem with histogram

They lose the numerical value of the individual scores.

44

Stem and Leaf

Most significant digits are the stem, less significant are the leaves. Useful for comparing 2 dif distrubutions

45

External validity

random selection

46

Internal validity:

Random assignment

47

Area under normal distribution equals

1

48

Two purposes of inferential statistics

Parameter estimation  Hypothesis testing

49

standard error of mean

is the standard deviation of the distribution of sample means. When it is large, the means are widely scattered  The standard error of mean provides a measure of how much distance is expected on average between sample means and

50

Neyman and Pearso

Type 1 and 2 error

51

A Type I error

α, is the probability of falsely rejecting the complementary hypothesis when it is true 

52

type 2

is the probability of not rejecting the complementary hypothesis when it is false