Econ408 population and sampling

1. Introduction Definition Types of Sampling Methods
Population and Sample
ECON408 (Reserach Methods in Economics)
Pairach Piboonrugnroj, PhD
Faculty of Economics, Chiang Mai University
me (at) pairach (dot) com
2016
This course is a part of Bachelor of Economics at Chiang Mai University, Thailand
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

2. Introduction Definition Types of Sampling Methods
Outline
What we will learn in this topic
1 Introduction
2 Definition
3 Types of Sampling Methods
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

3. Introduction Definition Types of Sampling Methods
Introduction
what is the population and sample in research?
Write down your definition of population
and sample on a paper (2 minutes)
Discuss
with a person next to you. Compare and
contrast your definitions (5 minutes)
Revise your definition if any
Share with the class
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

4. Introduction Definition Types of Sampling Methods
Definition of Population
Population is a complete set of elements (persons or objects)
that possess some common characteristic defined by the
sampling criteria established by the researcher
Composed of two groups - target population & accessible
population
Target population (universe) is the entire group of people or
objects to which the researcher wishes to generalize the study
findings. It meet set of criteria of interest to researcher
Accessible population is the portion of the population to which
the researcher has reasonable access; may be a subset of the
target population. May be limited to region, state, city, county,
or institution
source: http://www.umsl.edu/ lindquists/sample.html
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

5. Introduction Definition Types of Sampling Methods
Definition of Samples
Terminology used to describe samples and sampling methods
are:
Sample = the selected elements (people or objects) chosen for
participation in a study; people are referred to as subjects or
participants
Sampling = the process of selecting a group of people, events,
behaviors, or other elements with which to conduct a study
Sampling frame = a list of all the elements in the population
from which the sample is drawn
source: http://www.umsl.edu/ lindquists/sample.html
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

6. Introduction Definition Types of Sampling Methods
Sampling frame
Sampling frame could be extremely large if population is
national or international in nature. Frame is needed so that
everyone in the population is identified so they will have an
equal opportunity for selection as a subject (element).
Examples:
1 A list of all tourism companies that are the member of the
Chiang Mai Chamber of Commerce
2 A list of Economics students who are the member of
student association
3 A list of all children with disability who study in Chiang Mai
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

7. Introduction Definition Types of Sampling Methods
Sampling terminology
1 Randomization = each individual in the population has an
equal opportunity to be selected for the sample
2 Representativeness = sample must be as much like the
population in as many ways as possible
3 Parameter = a numerical value or measure of a
characteristic of the population; remember P for
parameter & population
4 Statistic = numerical value or measure of a characteristic
of the sample; remember S for sample & statistic
5 Precision = the accuracy with which the population
parameters have been estimated; remember that
population parameters often are based on the sample
statistics
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

8. Introduction Definition Types of Sampling Methods
Types of Sampling Methods
There are two main types of sampling methods:
probability and non-probability
Either of both method shall be selected carefully
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

9. Introduction Definition Types of Sampling Methods
Probability Sampling Methods
Also called random sampling
Every element (member) of the population has a
probability greater than) of being selected for the sample
Everyone in the population has equal opportunity for
selection as a subject
Increases sample’s representativeness of the population
Decreases sampling error and sampling bias
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

10. Introduction Definition Types of Sampling Methods
Types of probability sampling
Simple random
Stratified random
Cluster random sampling
Systematic
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

11. Introduction Definition Types of Sampling Methods
Types of probability sampling
Elements selected at random
Assign each element a number
Select elements for study by
1 using a table of random numbers in book
2 Computer generated random numbers table
3 Draw numbers for box (hat)
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

12. Introduction Definition Types of Sampling Methods
Stratified random
Population is divided into subgroups, called strata, according
to some variable or variables in importance to the study
Variables often used include: age, gender, ethnic origin,
SES, diagnosis, geographic region, institution, or type of
care
Two approaches to stratification - proportional &
disproportional
1 Proportional = Subgroup sample sizes equal the
proportions of the subgroup in the population
2 Disproportional = Subgroup sample sizes are not equal to
the proportion of the subgroup in the population
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

13. Introduction Definition Types of Sampling Methods
Cluster random sampling
A random sampling process that involves stages of sampling.
The population is first listed by clusters or categories. The
procedure are:
Randomly select 1 or more clusters and take all of their
elements (single stage cluster sampling); e.g. Northern
region of Thailand
Or, in a second stage randomly select clusters from the
first stage of clusters; eg 3 provinces in Northern region of
Thailand
In a third stage, randomly select elements from the
second stage of clusters; e.g. 30 county health dept.
nursing administrators from each state
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

14. Introduction Definition Types of Sampling Methods
Systematic
A random sampling process in which every kth (e.g. every 5th
element) or member of the population is selected for the
sample after a random start is determined. Example:
Population (N) = 2000, sample size (n) = 50, k=N/n, so k = 2000 ) 50 =
40
Use a table of random numbers to determine the starting point for
selecting every 40th subject
With list of the 2000 subjects in the sampling frame, go to the starting
point, and select every 40th name on the list until the sample size is
reached. Probably will have to return to the beginning of the list to
complete the selection of the sample.
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

15. Introduction Definition Types of Sampling Methods
Non-probability sampling methods
Issues to consider for Non-probability sampling methods.
Characteristics
Types of non-probability sampling methods
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

16. Introduction Definition Types of Sampling Methods
Characteristics
Not every element of the population has the opportunity
for selection in the sample
No sampling frame
Population parameters may be unknown
Non-random selection
More likely to produce a biased sample
Restricts generalization
Historically, used in most nursing studies
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

17. Introduction Definition Types of Sampling Methods
Types of non-probability sampling methods
Convenience - aka chunk, accidental & incidental
sampling
Quota
Purposive - aka judgmental or expert’s choice sampling
Snowball
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

18. Introduction Definition Types of Sampling Methods
Convenience - aka chunk, accidental & incidental
sampling
Selection of the most readily available people or objects
for a study
No way to determine representativeness
Saves time and money
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

19. Introduction Definition Types of Sampling Methods
Quota
Selection of sample to reflect certain characteristics of
the population
Similar to stratified but does not involve random selection
Quotas for subgroups (proportions) are established
E.g. 50 males & 50 females; recruit the first 50 men and
first 50 women that meet inclusion criteria
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

20. Introduction Definition Types of Sampling Methods
Purposive - aka judgmental or expert’s choice
sampling
Researcher uses personal judgement to select subjects
that are considered to be representative of the population
Handpicked subjects
Typical subjects experiencing problem being studied
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

21. Introduction Definition Types of Sampling Methods
Snowball
Also known as network sampling
Subjects refer the researcher to others who might be
recruited as subjects
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

22. Introduction Definition Types of Sampling Methods
Time Frame for Studying the Sample
See design notes on longitudinal & cross-sectional studies
Longitudinal
Cross-sectional
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

23. Introduction Definition Types of Sampling Methods
Sample Size
General rule - as large as possible to increase the
representativeness of the sample
Increased size decreases sampling error
Relatively small samples in qualitative, exploratory, case
studies, experimental and quasi-experimental studies
Descriptive studies need large samples; e.g. 10 subjects
for each item on the questionnaire or interview guide
As the number of variables studied increases, the sample
size also needs to increase in order to detect significant
relationships or differences
A minimum of 30 subjects is needed for use of the central
limit theorem (statistics based on the mean)
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

24. Introduction Definition Types of Sampling Methods
Large samples are needed if:
There are many uncontrolled variables
Small differences are expected in the sample/population
on variables of interest
The sample is divided into subgroups
Dropout rate (mortality) is expected to be high
Statistical tests used require minimum sample or
subgroup size
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

25. Introduction Definition Types of Sampling Methods
Power Analysis (I)
Power analysis = a procedure for estimating either the
likelihood of committing a Type II error or a procedure for
estimating sample size requirements.
Determine the sample size
Background Information for Understanding Power
Analysis: Type I and Type II errors
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

26. Introduction Definition Types of Sampling Methods
Type I Error
Based on the statistical analysis of data, the researcher
wrongly rejects a true null hypothesis; and therefore,
accepts a false alternative hypothesis
Probability of committing a type I error is controlled by the
researcher with the level of significance, alpha.
Alpha a is the probability that a Type I error will occur
Alpha a is established by researcher; usually a = .05 or .01
Alpha a = .05 means there is a 5% chance of rejecting a
true null hypothesis; OR out of 100 samples, a true null
hypothesis would be rejected 5 times out of 100 and
accepted 95 times out of 100.
Alpha a = .01 means there is a 1% chance of rejecting a
true null hypothesis; OR out of 100 samples, a true null
hypothesis would be rejected 1 time out of 100 and
accepted 99 times out of 100Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

27. Introduction Definition Types of Sampling Methods
Type II error
Based on the statistical analysis of data, the researcher
wrongly accepts a false null hypothesis; and therefore,
rejects a true alternate hypothesis
Probability of committing a Type II error is reduced by a
power analysis
1 Probability of a Type II error is called beta b
2 Power, or 1- b is the probability of rejecting the null
hypothesis and obtaining a statistically significant result
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

28. Introduction Definition Types of Sampling Methods
Sampling Error and Sampling Bias
Sampling error = The difference between the sample statistic
(e.g. sample mean) and the population parameter (e.g.
population mean) that is due to the random fluctuations in
data that occur when the sample is selected.
Sampling bias:
Also called systematic bias or systematic variance
The difference between sample data and population data
that can be attributed to faulty sampling of the population
Consequence of selecting subjects whose characteristics
(scores) are different in some way from the population
they are suppose to represent
This usually occurs when randomization is not used
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

29. Introduction Definition Types of Sampling Methods
Randomization Procedures in Research
Randomization = each individual in the population has an
equal opportunity to be selected for the sample
Random selection = from all people who meet the
inclusion criteria, a sample is randomly chosen
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number

30. Introduction Definition Types of Sampling Methods
Q&A
Pairach Piboonrugnroj, PhD Faculty of Economics, Chiang Mai University
ECON304 - 02. Index number