Flashcards in Final Deck (44):

1

## Critical value

### First value for which we would reject the null hypothesis

2

## If p-value is less than or equal to alpha(significance level)

### Then we reject the null hypothesis

3

## Sentence if u reject the null

### We reject the null hypothesis and conclude the alternative hypothesis is true. The results of our sample are statistically significant

4

## Failing to reject null

### We fail to reject the null hypothesis and conclude the alternative is false. The results of our sample are not statistically significant. There is not sufficient evidence against the null hypothesis

5

## Type 1 error

###
The null hypothesis is true, but we mistakenly reject it

Alpha

6

## Type 2 error

###
The null hypothesis is false, but we fail to reject it

Beta

7

## Power depends on effect size. The larger the effect size,

### The greater the power of the test

8

## Power of the test

###
1-Type 2 error(beta)

The tests ability to detect a false hypothesis

9

## Effect size

### Distance between the null value and the true parameter

10

## How to describe confidence interval

### We are blank % confident that the true proportion of (subject) is captured within the interval

11

## Confidence interval

### Represents success rate of the method used to construct the interval

12

## Confidence intervals for proportions are based on

### Point estimate and margin of error

13

## 4 requirements for confidence interval to be valid estimate

###
1.np>10, nq>10

2.sample size is less than 10% of pop, of sampling without replacement

3. Sample can be regarded as a simple random sample

4. Data values are assumed to be independent of each other

14

## In order to decrease the margin of error for greater precision we should

###
1. Decrease the confidence level

2. Increase the sample size

15

## Describe confidence interval for population mean

### We are blank% confident that the true mean of (subject) is captured within the interval

16

## T values account for

### Confidence level

17

## In order for a confidence interval to be valid what must u assume about its graph

### Bell shaped + other stuff

18

## For a sampling distribution model for a sample mean, as sample size increases the mean

### Of our sample will stay the same

19

## Taking the average of larger sample sizes gives a more or less precise estimate of the true mean, thus the spread around the center gets smaller or larger

### More precise, gets smaller

20

## The central limit theorem(CLT)

### Draw a simple random sample of size n(>30) from any non-normal population with a mean and a standard deviation, then the sample mean has a sampling distribution that is approximately normal as long as the sample is large enough.

21

## For CLT to be applicable the sample values must be

### Independent of one another

22

## A categorical parameter that describes the difference in 2 population proportions

### P1-p2

23

## Quantitative parameter that describes the population mean of paired differences(dependent samples)(matched pairs)

### (Sigma)d or Xd(for a sample)

24

## Quantitative parameter that describes the difference in 2 population means for independent samples(drug trials)

### Mean1-mean2

25

## Use t distribution table when working when the blank is unknown

### The population standard deviation signs

26

## Cumulative probability

### P(Xa)

27

## Use a binomial model when

### NP<10

28

## Binomial sampling distribution

###
X~B(n,p)

N=total sample

P=proportion

29

## nCk by hand

### N/(k)(n-k)

30

## Binomial mean

### Np

31

## Binomial standard deviation

### Square root(np(1-p))

32

## Variance for binomial

### Npq

33

## Normal approximation for a binomial distribution

### X~AN(mean=np,sigma=square root (npq)

34

## Standard deviation of the sample mean

### Sigma(population standard deviation)/square root(n)

34

## Standard deviation of a sample proportion

### Square root (pq/n)

35

## Standard error of sample proportion

### Square root of [sample (pq)/n)]

36

## Margin of error general formula

### Z*SE(sample p)

37

## Standard error of sample mean

### S/Square root(n)

38

## If you know the standard deviation of the sample mean then which test statistic do you use

### Z score

39

## If you know the standard error of the sample mean then which test statistic do you use

### T score

40

## Mu(u) symbolizes

### Population mean

41

## Ud symbolizes

### Population mean of paired differences(matched pairs)

42

## Difference in 2 pop means for independent samples

### U1-U2

43