Tata Tulis dan Komunikasi Ilmiah

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1 Tata Tulis dan Komunikasi Ilmiah Desain Sampel Dr. Eko Pujiyanto, S.Si., M.T.

2 Materi 1. Sensus dan survei sampel 2. Langkah-langkahdalamdesainsampling, 3. Kriteriamemilihprosedursampling, 4. Karakteristikdesainsampelyang baik, 5. Tipe desain sampel 6. Lampiran : Menentukan jumlah sampel

3 Sensusdansurveisampel Semuaobjekrisetberadadialamataupopulasi Sensus adalah enumerasi semua data dalam populasi. Surveisampeladalahmemilihsecaraselektifdata yang terdapat dalam populasi Census

4 Populasidansampel Population of Interest N ~ ( μ, σ ) Population Sample Sample Parameter x, s Statistic

5 Steps In Sample Design 1. Type of universe (population) 2. Sampling unit 3. Sampling frame 4. Size of sample 5. Parameters of interest 6. Budgetary constraint 7. Sampling procedure

6 Steps In Sample Design

7 Criteria Of Selecting A Sampling Procedure Researcher must keep in view the two causes of incorrect inferences : Systematic bias Sampling error A systematic bias results from errors in the sampling procedures, and it cannot be reduced or eliminated by increasing the sample size.

8 Criteria Of Selecting A Sampling Procedure Systematic bias is the result of one or more of the following factors : 1. Inappropriate sampling frame 2. Defective measuring device 3. Non-respondents 4. Indeterminancy principle 5. Natural bias in the reporting of data

9 Criteria Of Selecting A Sampling Procedure 1. Sampling errors are the random variations in the sample estimates around the true population parameters. 2. Sampling error decreases with the increase in the size of the sample. 3. Sampling error can be measured for a given sample design and size.

10 Characteristics Of A Good Sample Design 1. Sample design must result in a truly representative sample. 2. Sample design must be such which results in a small sampling error. 3. Sample design must be viable in the context of funds available for the research study. 4. Sample design must be such so that systematic bias can be controlled in a better way. 5. Sample should be such that the results of the sample study can be applied, in general, for the universe with a reasonable level of confidence.

11 Types of Sample Design

12 Non-probability sampling Sampling procedure which does not afford any basis for estimating the probability that each item in the population has of being included in the sample. Items for the sample are selected deliberately by the researcher. Types non-probability sampling 1. Convenience 2. Judgment 3. Quota 4. Snowball

13 Non-probability sampling 1. Convenience sampling Also called haphazard or accidental sampling The sampling procedure of obtaining the people or units that are most conveniently available 2. Judgment Sampling Also called purposive sampling An experienced individual selects the sample based on his or her judgment about some appropriate characteristics required of the sample member

14 Non-probability sampling 3. Quota sampling Ensures that the various subgroups in a population are represented on pertinent sample characteristics To the exact extent that the investigators desire It should not be confused with stratified sampling. 4. Snowball Sampling A variety of procedures Initial respondents are selected by probability methods Additional respondents are obtained from information provided by the initial respondents

15 Probability sampling Also known as random sampling or chance sampling. Every item of the universe has an equal chance of inclusion in the sample. Ensures the law of Statistical Regularity which states that if on an average the sample chosen is a random one, the sample will have the same composition and characteristics as the universe

16 Types probability sampling 1. Simple Random Sampling 2. Systematic Sampling 3. Stratified Sampling 4. Cluster Sampling 5. Area sampling 6. Multistage Sampling 7. Sampling with probability proportional to size 8. Sequential sampling

17 Simple Random Sampling A sampling procedure that ensures that each element in the population will have an equal chance of being included in the sample. Various statisticians like Tippett, Yates, Fisher have prepared tables of random numbers which can be used for selecting a random sample.

18 Systematic Sampling To select every i-thitem on a list Only the first unit is selected randomly and the remaining units of the sample are selected at fixed intervals. It is an easier and less costlier method of sampling and can be conveniently used even in case of large populations.

19 Stratified sampling Generally applied in order to obtain a representative sample Subsamples are drawn within different strata Each stratum is more or less equal on some characteristic The results in more reliable and detailed information.

20 Stratified sampling Three questions are highly relevant in the context of stratified sampling 1. How to form strata? 2. How should items be selected from each stratum? 3. How many items be selected from each stratum or how to allocate the sample size of each stratum?

21 Stratified sampling 1. How to form strata? Various strata be formed in such a way as to ensure elements being most homogeneous within each stratum and most heterogeneous between the different strata. 2. How should items be selected from each stratum? Systematic sampling can be used if it is considered more appropriate in certain situations

22 Stratified sampling 3. How many items be selected from each stratum Proportional allocation under which the sizes of the samples from the different strata are kept proportional to the sizes of the strata. To illustrate it, let us suppose that we want a sample of size n= 30 to be drawn from a population of size N= 8000 which is divided into three strata of size N 1 = 4000, N 2 = 2400 and N 3 = 1600.

23 Stratified sampling 3. How many items be selected from each stratum

24 Stratified sampling 3. How many items be selected from each stratum In cases where strata differ not only in size but also in variability

25 Stratified sampling

26 Cluster sampling A sample can be taken is to divide the area into a number of smaller non-overlapping areas and then to randomly select a number of these smaller areas (clusters), with the ultimate sample consisting of all (or samples of) units in these small areas or clusters. The purpose of cluster sampling is to sample economically while retaining the characteristics of a probability sample.

27 Cluster sampling Suppose we want to estimate the proportion of machine-parts in an inventory which are defective. Also assume that there are machine parts in the inventory at a given point of time, stored in 400 cases of 50 each. Now using a cluster sampling, we would consider the 400 cases as clusters and randomly select n cases and examine all the machine-parts in each randomly selected case.

28 Area sampling If clusters happen to be some geographic subdivisions,in that case cluster sampling is better known as area sampling

29 Multistage sampling Further development of the principle of cluster sampling. Suppose we want to investigate the working efficiency of nationalisedbanks in India and we want to take a sample of few banks for this purpose. The first stage is to select large primary sampling unit such as states in a country. Then we may select certain districts and interview all banks in the chosen districts. This would represent a two-stage sampling design with the ultimate sampling units being clusters of districts.

30 Sampling with probability proportional to size In case the cluster sampling units do not have the same number or approximately the same number of elements.

31 Sampling with probability proportional to size

32 Sequential Sampling This sampling design is some what complex sample design. The ultimate size of the sample under this technique is not fixed in advance, but is determined according to mathematical decision rules on the basis of information yielded as survey progresses. This is usually adopted in case of acceptance sampling plan in context of statistical quality control.

33 Lampiran Menentukan ukuran sampel Syarat

34 Lampiran ( Menentukan ukuran sampel )

35 Lampiran ( Menentukan ukuran sampel )

36 Referensi Khotari, C.R., 2004, Research Methodology: Methods and Techniques, New Age International (P) Ltd., Publishers. ( Chapter 4)

Chapter 8: Quantitative Sampling

Chapter 8: Quantitative Sampling I. Introduction to Sampling a. The primary goal of sampling is to get a representative sample, or a small collection of units or cases from a much larger collection or