Flashcards in Sampling Deck (40)

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1

## What is a population or universe?

### Any complete group with common characteristics

2

## What is a population element?

### Single member of a population

3

## What is a census?

### Investigation of all individual elements that make up a population

4

## What is a sample?

###
- Subset of the larger population of interest

- This is the subset of group that the researcher will actually study or investigate

5

## What is a population frame?

### A list of all the elements in the population

6

## What is a sample frame?

### A list of all the elements in the population from which the sample may be drawn

7

## What is sampling frame error?

### An error which occurs when certain sample elements are not listed or are not accurately represented in a sampling frame

8

## What is a sampling unit?

### An element or group of elements subject to selection in the sample

9

## What is inclusion/exclusion criteria?

### The criteria potential participants must meet in order to be included in the study

10

## What are the core statistical concepts?

###
* Descriptive statistics

* Inferential statistics

* Population parameters

* Sample statistics

11

## What are descriptive statistics?

###
- Describe the data

- Measure of central tendency, frequencies, dispersion

- Trends

12

## What are inferential statistics?

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- Project characteristics of a sample to an entire population

- Make an inference about a population from a sample

- Used in hypothesis testing

13

## What are population parameters?

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- Characteristics of the population

- Variable in a population or measure characteristics of the populaiton

- Greek letters as notation

- μ = ∑X/N

14

## What are sample statistics?

###
- Estimates of population parameters

- Variables in a sample or measures computed from sample data

- English letters for notation

- X̅ = ∑X/N

15

## What is the cost associated with sampling and the solution to this?

###
- A loss of information

- To make up for this loss we have to ensure that the sample is representative of the population

16

## What does representativeness determine?

### The representativeness of the sample determines the extent to which generalisable inferences can be made

17

## What does the CLT imply?

###
- Suggests that the sampling distribution of the sample mean produces a normal curve

- As the sample size increases, the means of random samples taken form the population approach a normal distribution

- This means we have a representative sample - and our sample mean will be within close range of the true population mean

18

## What is probability sampling?

### Chance of selecting any particular member is known and is equal for all units (probability is non-zero)

19

## What methods of probability sampling are there?

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* Simple random

* Systematic

* Stratified

* Cluster

20

## What is simple random sampling?

### A sampling procedure that ensures that each elements in the population will have an equal chance of being included in the sample

21

## What is systematic sampling?

### Every nth name from a list (sampling frame) will be drawn

22

## What is stratified sampling?

###
- Subsamples are drawn within different strata

- Strata are subgroups of elements that may be expected to have different parameters on a variable of interest

- Each stratum is more or less equal on some characteristic

23

## What different types of stratified sampling are there?

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- Subjects drawn from each stratum can be either dispropriationate or proportionate to the number of elements in the stratum

- Proportionate stratified sampling (20% of members from each stratum)

- Disproportionate stratified sampling (% of members disproportionate across stratum)

24

## What is cluster sampling and what is the important aspect of it?

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- Purpose is to sample economically while retaining the characteristics of a probability sample

- Primary sampling unit

- No longer the individual elements in the population

- Instead, a larger cluster of elements located in proximity to on another

25

## What is non-probability sampling and when is it useful?

###
- Chance of selecting any particular member is unknown

- Useful when sampling frame cannot be created

26

## What kinds of non-probabilty sampling are there?

###
* Convenience methods

* Purposive Methods

27

## What types of convenience methods of sampling are there?

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* Convenience

* Snowball

28

## What is convenience sampling?

###
- The sampling procedure of obtaining the people or units that are most consistently available

- Least reliable of all sampling designs in terms of generalisability, but may be the only viable alternative when quick and timely information is needed

29

## What is snowball sampling?

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- Initial respondents are selected by probability methods

- Additional respondents are obtained form information provided by the initial respondents

30