1. 11 Norton university Research Method Topic: Determination of sample size Facilitated by: Dr. pheak sothea DEPARTMENT: MDM

2. 22 batch:16 Semester:2 session : weekend room ;e206 Academic year: 2009-2010 DATE OF PRESENTATION 18/07/2010

3. 3 33 Group Members CHEA SOKTA LY VANNY ROS VANNARY UNG RAKSMEY SOK TENG RORNG ROTHA TANG SITHARITH

4. 44 Content of Presentation A.Reviewing some basic terminology B.Population Parameters and Sample Statistics C.Making Data Usable D.Sample Distribution, and Sampling Distribution E.Sample Size F.Determining Sample Size

5. 55 A. Reviewing Some Basic Terminology A population is the entire collection of things under consideration.  parameter is a summary measure computed to describe a characteristic of the population

6. 6 A sample is a portion of the population selected for analysis  Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting numerical data to assist in making more effective decisions.

7. 7 Population versus Sample A population is a collection of all possible individuals, objects, or measurements of interest. A sample is a portion, or part, of the population of interest

8. Types of Statistics Descriptive Statistics: Methods of organizing, summarizing, and presenting data in an informative way. Inferential Statistics: A decision, estimate, prediction, or generalization about a population, based on a sample. 8

9. 99 Types of Variables A. Qualitative or Attribute variable - The characteristic being studied is nonnumeric. Examples: Gender, religious affiliation, type of automobile owned, state of birth, eye color are examples. B. Quantitative variable - Information is reported numerically. Examples: Balance in your checking account, minutes remaining in class, or number of children in a family.

10. 10 B. Population Parameters & Sample Statistics Population Parameters are summary descriptors (e.g., incidence proportion, mean, variance) of variables of interest in the population. Sample Statistics are descriptors of the relevant variables computed from sample data.  Sample Statistics are used as estimators of population parameters. They are the basis of our inferences about the population.

11. 11 C. Making Data Usable 11 Basic Business Statistics, 10e © 2006 Prentice-Hall, Inc.. Secondary Data Compilation Observation Experimentation Print or Electronic Survey Primary Data Collection

12. Making Data Usable 12 Collecting the Data Raw Data Analyzing and Interpreting Qualitative Data Quantitative Data

13. 13 D. Sample Distribution and Sampling Distribution The sample distribution is the distribution resulting from the collection of actual data. A major characteristic of a sample is that it contains a finite (countable) number of scores, the number of scores represented by the letter N.

14. 14 For example, suppose that the following data were collected 323542333638373338363534374038363531373633 36394033303537393239373536393331403734 37 These numbers constitute a sample distribution. Using the procedures discussed in on frequency distributions, the following relative frequency polygon can be constructed to picture this data:

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16. 16 Sampling Distribution Note the "-ING" on the end of SAMPLE. It looks and sounds similar to the SAMPLE DISTRIBUTION, but, in reality the concept is much closer to a population model. The sampling distribution is a distribution of a sample statistic. It is a model of a distribution of scores, like the population distribution, except that the scores are not raw scores, but statistics.

17. 17 In statistics, a sampling distribution is the distribution of a given statistic based on a random sample of size n. It may be considered as the distribution of the statistic for all possible samples of a given size. The sampling distribution depends on the underlying distribution of the population, the statistic being considered, and the sample size used.

18. 18 For example, suppose that a sample of size sixteen (N=16) is taken from some population. The mean of the sixteen numbers is computed. Next a new sample of sixteen is taken, and the mean is again computed. If this process were repeated an infinite number of times, the distribution of the now infinite number of sample means would be called the sampling distribution of the mean.

19. 19 Every statistic has a sampling distribution. For example, suppose that instead of the mean, medians were computed for each sample. The infinite number of medians would be called the sampling distribution of the median.

20. 20 E. Sample Size  What is sample size? - Specific size of the group or groups being studied in your research; - Number of participants planned to be included in your study; - In research terms, a sample is a group of people (individual persons, things), determine using specific criteria to be representative of a large population, who are chosen for observation and/or interviewing.

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22. 22 1. Define the target population 2. Define the sampling frame 3. Select a sampling technique (s) 4. Determine the sample size 5. Execute the sampling process

23. 23 Sampling with replacement Sampling without replacement A sampling technique in which an element can be included in the sample more than once A sampling technique in which an element cannot be included in the sample more than once Probability samplingNon-probability sampling Sampling technique that do not use chance selection procedures, rather they rely on the personal judgment of the researchers A sampling procedure in which each element of the population has a fixed probabilistic chance of being selected for the sample

24. 24 Non-probabilityProbability Convenience sampling Judgmental sampling Quota sampling Snowball sampling Simple random sampling Systematic sampling Stratified sampling Cluster sampling Other sampling techniques ProportionateDisproportionate

25. 25 Non-Probability Sampling Convenience sample Purposive sample Snow-ball sample That attempts to obtain a sample of convenient element. The selection of sampling units is left primarily to the interviewer The population elements are purposively selected based on the judgment of the researcher An initial group of respondents is selected randomly. Subsequent respondents are selected based on the referrals or information provided by the initial respondents. Quota sample Is a two-stage restricted judgmental sampling. The 1 st stage consists of developing control categories or quotas of population elements. In the 2 nd stage, sample elements are selected based on convenience or judgment

26. 26 Probability Sampling Simple random sampling Systematic sampling Stratified sampling Cluster sampling Multi-stage cluster sampling For small population, with possible assigned number For big population, make a sampling interval with impossible assigned number Different type of population, making a strata Complex population Sampling frame is not available, making a cluster Complex population, Sample selected from stages of cluster

27. 27 F. Determine of Sample Size  How to Determine Sample Size - To calculate your sample size you will need certain information; - Depend on the statistical test you plan to use; - Desirable effect size to determine sample size; - Define the alpha level you want to use for the statistical test.

28. 28 Determine of Sample Size  Assume that a researcher has set the alpha level a priori at.05,plans to use a seven point scale, has set the level of acceptable error at 3%, and has estimated the standard deviation of the scale as 1.167 Where t = value for selected alpha level of.025 in each tail = 1.96

29. 29 Determine of Sample Size Where s = estimate of standard deviation in the population = 1.167. (estimate of variance deviation for 7 point scale calculated by using 7 [inclusive range of scale] divided by 6 [number of standard deviations that include almost all (approximately 98%) of the possible values in the range]).

30. 30 Determine of Sample Size Where d = acceptable margin of error for mean being estimated =.21. (number of points on primary scale * acceptable margin of error; points on primary scale = 7; acceptable margin of error =.03 [error researcher is willing to except]).

31. 31 Determine of Sample Size =(t) 2 * (s) 2 / (d) 2 = (1.96)2* (1.167)2/(7*.03)2 = 118 Therefore, for a population of 1,679, the required sample size is 118.

32. 32 Determine of Sample Size Sample Size Calculator

33. 33 THANK YOU INDEED FOR YOUR ATTETION AND PARTICIPAITON