Flashcards in Sampling CI Deck (57):

1

## What is Sampling?

### The process to determine who we are going to study/examine

2

## What is the purpose of Sampling?

### To find out information without talking to everyone.

3

## What are two types of sampling?

###
Nonprobability

Probability

4

## What is Probability sampling?

### Systemic technique that is used to select respondents - goal is to create a sample as representative of the population as possible.

5

## When is Probability sampling used most frequently?

###
Quantitative research

--> Leaving the selection up to chance

6

## What is Non-probability sampling?

### Based on researcher subjective judgment rather than random selection

7

## What are traits of Non-probability Sampling?

###
-Less generalizability; problem with representativeness

-Lower confidence in findings

-Useful when probability sampling can't be used

-Four common methods

8

## What are the four common methods of Non-probability sampling?

###
-Purposive

-Convenience

-Snowball

-Quota

9

## What are four traits of Probability Sampling?

###
1. Used to Generalize population at large

2. Works toward representativeness

3. Used in all large-scale surveys/observational studies

4. Avoids Sampling Bias

10

## What is Sampling Bias?

###
Selecting atypical folks.

-Numerous ways to introduce bias into your sample.

11

## What is a "Representative" sample?

###
-Your sample is like the population

-Random selection!

-All members have an equal chance of being selected...

12

## Probability samples are. . .

###
. . .never perfect.

-More representative than non-probability.

13

## What is an Element?

### Individual members of the population to which the study would be generalized

14

## What is the Population?

### The entire set of elements. Doesn't have to just be individuals - other entities - to which the study findings will be generalized.

15

## What is the Sampling Frame?

###
LIST of all the elements in a population. Want to study students - registrar's list of students - the students selected to be interviewed would be the elements

-Important for representativeness but not easy to acquire

16

## What are examples of Sampling Frames?

###
-Telephone directories

-Tax records

-Registrar's list

17

## What is the key question with Probability Sampling?

### Who can I generalize these findings to?

18

## What is Parameter?

### Summary of a given variable in a population

19

## What is a Statistic?

### Summary of a given variable in a sample

20

## What is the Sampling Distribution?

### All the possible random samples that could be selected

21

## What are random samples?

### Samples that represent a population

22

## What are four commonly discussed sample types?

###
1. Simple Random

2. Systematic

3. Stratified

4. Multistage Cluster

--PPS sampling (a form of cluster sampling)

23

## What is Simple Random Sampling?

###
-Base of sampling

--Need a list (sampling from)

--Assign a number

--Select by a random number

---> Random number list

-Seldom used in this deliberate way; some use of computer generated random numbers

24

## What is Systematic Sampling?

###
-Determine number needed

-Divide population by sample number desired (we call this our sampling interval, denoted here by 'k')

-List and number our elements

-Randomly select start point

-Select every k-th elements within groups

-Caution: avoid periodicity!

25

## What is Stratified Sampling?

###
-Possible modification of previous techniques

-Random sample from subpopulation

-Better representativeness

-Decreases some sampling error

--> Homogenous subsets

-Allows oversampling

26

## What is Cluster Sampling?

###
-More complex methodologically (not conceptually, I hope)

-Cluster = Groups of elements

-Multi-stage

---> Basic stages/steps: listing and sampling

-Helps with cost and dispersed populations

-Increases sampling error potential

--> Two samples: double the error opportunity

27

## What two techniques are used to make experiments Comparable (between control & experimental groups)?

###
-Randomization

-Matching

28

## What is Randomization?

### Recruited folks (who may have been selected using nonprobability sampling techniques) are randomly placed into control and exp. groups

29

## What is Matching?

### Assign people to group based on characteristics so groups match

30

## As the sample size goes up, the shape of the sampling distribution takes on an important shape. . .

### . . .the normal curve!

31

## What is Sampling Error?

###
-Variation in values of your sample mean compared to the population mean

-Because of sampling error, we probably won't always have completely accurate estimates

-Deviation between sample results and population

32

## How can you reduce Sampling Error?

###
-Increase sample size

-Increase homogeneity

33

## What are six characteristics of the Normal Curve from the Central Limit Theorem?

###
1. Theoretical distribution of scores

2. Perfectly symmetrical

3. Bell-shaped

4. Unimodal

5. Tails extend infinitely in both directions

6. Mean, median, and mode are equal

34

## Assumption of normality of a given empirical distribution . . .

### . . .makes it possible to describe this "real-world" distribution based on what we know about the (theoretical) normal curve.

35

## What do we use the normal curve assumption for?

### To generalize sample findings to a population.

36

## How many cases/how much area falls within 1 standard deviation of the mean?

### 0.68 of the area, 0.34 on each side of the mean.

37

## How many cases/how much area falls within 2 standard deviation of the mean?

### 0.95 of the area or 95% of cases

38

## How many cases/how much area falls within 3 standard deviation of the mean?

### 0.997 of the area or 99% of cases

39

## What is the Sampling Distribution used as?

### An Estimate!

40

## If an infinite number of samples were conducted and some outcome was plotted. . .

### The resulting distribution (for mans and proportions) would be "normal"

41

## Over the long run, any particular largish random sample estimate (outcome) has a 95% chance of being within. . .

### . . .1.96 standard error units of the population parameter it represents.

42

## What is the Z-distribution?

### Just a special case of the normal distribution.

43

## What is the mean and S.D. of the Z-distribution?

###
Mean = 0

S.D. = 1

44

## What does the Z-distribution allow us to do?

### Use a corresponding z-table to look up critical values

45

## What are the common z-scores for each confidence level (90%, 95%, 99%)?

###
1.65 = 90% CL

1.96 = 95% CL

2.58 = 99% CL

46

## What is the Confidence Level?

###
(Significance Level)

-Probability our sample statistics fall within a given confidence interval

-We set this ahead of time and denote as alpha. Most frequently, it's alpha = 0.05 (95%).

47

## What is the Confidence Interval?

###
-Range within 'true' parameters should lie, range of values around the estimate (point estimate)

-Upper and lower limit for the confidence level

48

## What confidence interval do many of the biomedical books use?

### CI = mean +/- 1.96 (standard errors), but this assumes a 95% confidence level (that's where they are getting the z-score of +/- 1.96).

49

## What does random selection allow us to do?

### Connect our sample findings to 'probability theory' concepts so we can estimate how accurate our findings are.

50

## I am x% confident that the population parameter falls between a-b. What is the confidence interval? What is the confidence level?

###
x% = confidence LEVEL (alpha)

Values between a - b = confidence INTERVAL

51

## The large the confidence level. . .

### . . .the narrower our confidence interval (CI).

52

## How do you calculate Standard Error?

### SE = SD/sq. rt. [N]

53

## How do you calculate confidence interval?

### Mean score +/- Z-score (which is usually 1.96) X SE

54

## What is the SE for each Confidence level?

###
90% - 1.65

95% - 1.96

99% - 2.58

55

## Wider the interval...

### ...weaker the evidence.

56

## Narrower the interval...

### ...stronger our case.

57