RESEARCH DESIGN PART 2 Siti Rohaida Bt Mohamed

RESEARCH DESIGN (PART 2) Siti Rohaida Bt Mohamed Zainal, Ph. D School of Management siti_rohaida@usm. my

What is Sampling? “Sampling is a process by which we study a small part of a population to make judgments about the entire population. ”

Why Sampling is Needed? n n n Lower cost Greater speed of data collection Greater accuracy

Factors to Consider in Sample Design Research objectives Resources Knowledge of target population Statistical analysis needs Degree of accuracy Time frame Research scope

The Nature of Sampling • • Population element Sampling frame Sample Subject Parameter Statistics Sampling error

The Nature of Sampling • Population - total collection of elements about which we wish to make some inferences. • Population element - the individual participant or object on which the measurement is taken--the unit of study. • Sampling frame - the listing of population elements from which the sample will be drawn—i. e. , master lists, directories etc

The Nature of Sampling • Sample - a part of the population from which we actually collect information which is used to draw conclusions about the whole population • Subject - a single member of the sample • Parameter - characteristics of the population • Statistics - characteristics of the sample • Sampling error: any error in a survey that occurs because of the sample

Inference Process Estimation & Hypothesis Testing Population Sample Statistics Sample

Parameter and Statistics: Example “Average income of engineers in Malaysia is RM 5000” Parameter Population “Average income of engineers in Penang is RM 5000” Statistic Sample

The Sampling Design Process Define the Population Determine the Sampling Frame Select Sampling Techniques Determine the Sample Size Execute the Sampling Process

Define the Target Population Important factors in determining the sample size: § § § the importance of the decision the nature of the research the number of variables the nature of the analysis sample sizes used in similar studies resource constraints-time and cost SAMPLE SIZE? ? ?

Sampling Error Sampling error is any type of bias that is attributable to mistakes in either drawing a sample or determining the sample size SAMPLE SIZE? ? ?

Two Basic Sampling Methods n Probability samples: ones in which members of the population have a known chance (probability) of being selected into the sample n Non-probability samples: instances in which the chances (probability) of selecting members from the population into the sample are unknown

Classification of Sampling Techniques SAMPLING TECHNIQUES Non-Probability Sampling Techniques Convenience Sampling Judgmental Sampling Simple Random Sampling Systematic Sampling Probability Sampling Techniques Quota Sampling Stratified Sampling Snowball Sampling Cluster Sampling Double Sampling

NONPROBABILITY SAMPLING

Non-probability Samples Reasons to use: Procedure satisfactorily meets the sampling objectives Lower Cost Limited Time Total list population not available

Non-probability Samples No need to generalize Feasibility Time Limited objectives Cost

Non-probability Sampling Methods Convenience Based on ease of accessibility Judgmental Deliberately select sample to conform to some criterion Quota Snowball Relevant characteristics are used to segregate the sample to improve its representativeness Referred by current sample elements

Convenience Sampling Convenience sampling – sample is selected base on ease of accessibility. Normally use in the early stage of exploratory study Often, respondents are selected because they happen to be in the right place at the right time. q use of students, and members of social organizations q mall intercept interviews without qualifying the respondents q “people on the street” interviews q pool of friends and contacts

Judgmental Sampling Ø Judgmental sampling is a form of convenience sampling in which the population elements are selected based on the judgment of the researcher or those conform to some criterion of interest. Useful when looking for information that only a few “experts” can provide. Example: q Academic expertise q Purchase engineers selected in industrial marketing research q Expert witnesses used in court Ø

Quota Sampling Quota sampling – relevant characteristics are used to stratify the sample. ¨ The first stage consists of developing categories of population elements. ¨ In the second stage, sample elements are selected based on convenience or judgment. ¨ Example: gender, religion, ethnicity, etc

Quota Sampling Population composition Characteristic Postgraduate MA Ph. D Sample composition Percentage Number 60% 40% ____ 100 600 400 ____ 1000 60% 40% ____ 100

Snowball Sampling In snowball sampling, an initial group of respondents is selected, usually at random. ¨ After being interviewed, these respondents are asked to identify others who belong to the target population of interest. ¨ Subsequent respondents are selected based on the referrals.

PROBABILITY SAMPLING

Simple Random Sampling All elements in the population are considered and each has equal chance to be selected. Each possible sample of a given size (n) has a known and equal probability of being the sample actually selected. Advantages • High generalisability of the findings • Easy to implement with random number table. Disadvantages • Requires list of population elements • Time consuming • Uses larger sample sizes

Systematic Random Sampling q The sample is chosen by selecting a random starting point and then picking every kth element from the sampling frame. q To draw a systematic sample, the steps are as follows: 1) Identify, list, and number the elements in the population 2) Identify the skip interval 3) Identify the random start 4) Draw a sample by choosing every kth element. * kth element is the skip interval

Systematic Random Sampling EXAMPLE: There are 100, 000 elements in the population and a sample of 1, 000 is desired. In this case the sampling interval, k, is 100. A random number between 1 and 100 is selected. If, for example, this number is 23, the sample consists of elements 23, 123, 223, 323, 423, 523, and so on. Advantages • Simple to design • Easier than simple random if population frame is available Disadvantages • Systematic biases are possible

Stratified Sampling All Postgraduates • Population is divided into sub-population and subjects are selected randomly. • Homogeneity within group and heterogeneity across groups. Masters Ph. D Sample

Stratified Sampling q A two-step process in which the population is partitioned into sub-population. q Elements are selected from each sub-population by a random procedure, usually simple random sampling. q The elements within each sub-population should be as homogeneous as possible, but the elements across sub-population should be as heterogeneous as possible. q The stratification variables should also be closely related to the characteristic of interest.

Stratified Sampling Example: University students can be divided into: q Gender q Race q School/department q Class level: undergraduate and postgraduate q Off campus and on-campus

Stratified Sampling Advantages Disadvantages • Most efficient among all probability designs. • Increased statistical efficiency • Provides data to represent subgroups • Stratification must be meaningful • Time consuming

Cluster Sampling All Managers in Malaysia • Population is divided into clusters. • Heterogeneity within group and homogeneity across groups. Kuala Lumpur Penang Sample Johor

Cluster Sampling Population Element Possible Clusters in Malaysian adult population States Districts Metropolitan Statistical Area Housing Area Households

Cluster Sampling q The target population is first divided into mutually exclusive clusters. q Then a random sample of clusters is selected, based on a probability sampling technique q Elements within a cluster should be as heterogeneous as possible, but clusters themselves should be as homogeneous as possible. q Ideally, each cluster should be a small-scale representation of the population.

Area Sampling (example of cluster) A cluster sampling technique applied to a population with well-defined political or geographic boundaries.

Double Sampling q The sample or a subset of the sample is studied twice. q Double and multiple sampling plans were invented to give a questionable lot another chance. q For example: a structured interview might indicate that a subgroup of the respondents has more insights into a problem in the organization, these respondents might be approached again with additional questions.

Double Sampling

What Is a Valid Sample? Accurate The degree to which bias is absent from the sample. The sample is drawn properly. Precise The degree to which the sample selected closely represent the population.

What Is a Valid Sample? High accuracy but low precision High precision but low accuracy

RULE OF THUMB FOR SAMPLE SIZE: According to ROSCOE (1975): (1) Sample size larger than 30 and less than 500 are appropriate for most research. (2) Where samples are to be broken into subsamples (male/female, masters/Ph. D etc), a minimum sample size of 30 for each category is necessary. (3) In multivariate research, sample size should be, preferably, 10 times (or more) as large as the number of variables in the study.

LET’S RECAP. . .

Nonprobability Sampling Methods Convenience sampling relies upon convenience and access Judgment sampling relies upon belief that participants fit characteristics Quota sampling emphasizes representation of specific characteristics Snowball sampling relies upon respondent referrals of others with like characteristics

Exercise 1 A researcher wants a sample of 35 households from a total population of 260 houses in Medan, Indonesia. He samples every 7 th house starting from a random number of 1 to 7. He then choose houses numbered 7, 14, 21, 28 and so on. What type of sampling technique does the researcher adopt? a) a simple random sampling b) a stratified random sampling c) a cluster sampling d) a systematic random sampling 43

Exercise 2 A pharmaceutical company wants to trace the effects of a new drug on patients with specific health problems. It then contacts such individuals and with the group of voluntarily consenting patients, tests the drugs. What type of sampling is appropriate? a) a simple random sample b) a stratified random sample c) a cluster sample d) a judgmental sample 44

Exercise 3 The director of human resources of a manufacturing firm wants to offer stress management seminars to the personnel who are exposed to high levels of stress. He predicts that three groups are most prone to stress; (1) those who handle dangerous chemicals, (2) counselors who listen to problems, and (3) those who handle production line. What type of sampling is most appropriate in this case? a) a simple random sample b) a stratified random sample c) a cluster sample d) a judgmental sample 45

The end Questions?