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RESEARCH METHODOLOGY FEM 3002, Credit Hour = 3(2+1) face to face 2, APRIL 2015

RESEARCH METHODOLOGY FEM 3002, Credit Hour = 3(2+1) face to face 2, APRIL 2015. Instructor : Siti Nor Binti Yaacob Department of Human Development and Family Studies Faculty of Human Ecology Universiti Putra Malaysia Contact #: 012- 284-1844 Email: sitinor@putra.upm.edu.my.

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RESEARCH METHODOLOGY FEM 3002, Credit Hour = 3(2+1) face to face 2, APRIL 2015

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  1. RESEARCH METHODOLOGY FEM 3002, Credit Hour = 3(2+1)face to face 2, APRIL 2015 • Instructor:Siti Nor Binti Yaacob • Department of Human Development and Family Studies • Faculty of Human Ecology • Universiti Putra Malaysia • Contact #: 012-284-1844 • Email: sitinor@putra.upm.edu.my

  2. LECTURE 8

  3. Outline Population and Sampling • Probability Sampling • Non-probability Sampling

  4. POPULATION • Definition A group of potential participants to whom you want to generalize the results of a study.

  5. Generalize : The key to a successful study; because it is only the results that can be generalized from a sample to a population; that research results have meaning beyond the limited setting.

  6. Not generalize : The sample selected is not an accurate representation of the population.

  7. Important Terms:

  8. Population vs. Census • Population the a group of people or things you are interested in. • Census is a measurement of all the units in the population

  9. Population Parameter vs. Statistic • PP = number that results from measuring all the units in the population. • Statistic = number that results from measuring all the units in the sample; statistics from samples are used to estimate PP.

  10. Sampling Frame vs Unit of Analysis • SF = specific data from which sample is drawn, e.g., a phone book. • UA = type of object of interest, e.g., arsons, fire departments, firefighters.

  11. Sampling Frame • Is a list or quasi list of the members of a population. • Resource used in the selection of a sample. • A sample’s representativeness depends directly on the extent to which a sampling frame contains all the members of the total population that the sample is intented to represent.

  12. e.g., Sampling Frame • The data for this research were obtained from a random sample of parents of children in the third grade in government primary schools in Selangor.

  13. SAMPLES Definition : Sample is a subset of the population. • Good sampling : include maximizing the degree to which this selected group represent the population.

  14. POPULATION Sample Sample

  15. WHY SAMPLE?

  16. Types of sampling • Probability sampling • Non probability sampling

  17. Probability sampling • Allows use of statistics, tests hypotheses. • Can estimate population parameter. • Eliminates bias. • Must have random selections of units.

  18. Non-probability sampling • Exploratory research, generates hypotheses. • Population parameters not of interests. • Adequacy of sample unknown. • Cheaper, easier, quicker to carry out. • Cant generalized findings. • Non-representative.

  19. PROBABILITY SAMPLING • A type of sampling where the likelihood of any one member of the population being selected is known. • Commonly used because the selection of participants is determined by chance.

  20. e.g., if there are 4,500 students in the Faculty of Human Ecology, and if there are 1,000 seniors, the odds of selecting one senior as part of the sample is 1000:4,500 or 0.22.

  21. NON-PROBABILITY • Where the likelihood of selecting any one member from the population or where the probability of selecting a single individual is not known.

  22. e.g., if you do not know how many seniors in the Faculty of Human Ecology, the likelihood of anyone being selected cannot be computed.

  23. TYPES OF PROBABILITY SAMPLING • Simple Random Sampling • Systematic Sampling • Stratified Random Sampling • Cluster Sampling

  24. 1. Simple Random Sampling When the population’s members are similar to one another.

  25. http://www.google.com.my/search?q=cluster+sampling+design+ppt&ie=utf-8&oe=utf-8&aq=t&rls=org.mozilla:en-US:official&client=firefox-ahttp://www.google.com.my/search?q=cluster+sampling+design+ppt&ie=utf-8&oe=utf-8&aq=t&rls=org.mozilla:en-US:official&client=firefox-a

  26. Adv: • Ensures a high degree of representativeness Disadv: • Time consuming and tedious

  27. How to use a random number table? • Let's assume that we have a population of 185 students and each student has been assigned a number from 1 to 185. Suppose we wish to sample 5 students (although we would normally sample more, we will use 5 for this example). • Since we have a population of 185 and 185 is a three digit number, we need to use the first three digits of the numbers listed on the chart.

  28. We close our eyes and randomly point to a spot on the chart. For this example, we will assume that we selected 20631 in the first column. • We interpret that number as 206 (first three digits). Since we don't have a member of our population with that number, we go to the next number 899 (89990). Once again we don't have someone with that number, so we continue at the top of the next column.

  29. As we work down the column, we find that the first number to match our population is 100 (actually 10005 on the chart). Student number 100 would be in our sample. Continuing down the chart, we see that the other four subjects in our sample would be students 049, 082, 153, and 005. http://www.google.com/imgres?imgurl=http://www.gifted.uconn.edu/siegle/research/Samples/RANTBLE.JPG&imgrefurl

  30. 2. Systematic Sampling When the population’s members are similar to one another.

  31. http://www.google.com.my/search?q=cluster+sampling+design+ppt&ie=utf-8&oe=utf-8&aq=t&rls=org.mozilla:en-US:official&client=firefox-ahttp://www.google.com.my/search?q=cluster+sampling+design+ppt&ie=utf-8&oe=utf-8&aq=t&rls=org.mozilla:en-US:official&client=firefox-a

  32. Adv : • Ensures a high degree of representativeness; no need to use a table of random numbers. Disadv : • Less truly random than simple random sampling

  33. 3. Stratified Random Sampling When the population is heterogeneous in nature and contains several different groups.

  34. http://www.google.com.my/search?q=cluster+sampling+design+ppt&ie=utf-8&oe=utf-8&aq=t&rls=org.mozilla:en-US:official&client=firefox-ahttp://www.google.com.my/search?q=cluster+sampling+design+ppt&ie=utf-8&oe=utf-8&aq=t&rls=org.mozilla:en-US:official&client=firefox-a

  35. Adv : • Ensures a high degree of representativeness of all the strata in the population. Disadv : • Time consuming and tedious

  36. Two Types of Stratified Random Sampling (SRM) • Proportionate SRM • Non-Proportionate SRM

  37. Proportionate SRM • Sampel selected is in proportion to the size of each stratum in the population

  38. example: PSRM • Population = 100 • Layer 1 = 40 males • Layer 2 = 60 females • For a sample size of 10, you will take 4 males + 6 females.

  39. Non-proportionate SRM • Selection of sample is not according to size of stratum in the population

  40. e.g., NPSRM • Population = 100 • Layer 1 = 40 males • Layer 2 = 60 females • For a sample size of 10, you will take 5 males + 5 females.

  41. 4. Cluster Sampling When the population consist of units rather than individuals.

  42. http://www.google.com.my/search?q=cluster+sampling+design+ppt&ie=utf-8&oe=utf-8&aq=t&rls=org.mozilla:en-US:official&client=firefox-ahttp://www.google.com.my/search?q=cluster+sampling+design+ppt&ie=utf-8&oe=utf-8&aq=t&rls=org.mozilla:en-US:official&client=firefox-a

  43. A two-step area cluster sample (sampling several clusters) is preferable to a one-step (selecting only one cluster) sample unless the clusters are homogeneous http://www.google.com.my/search?q=cluster+sampling+design+ppt&ie=utf-8&oe=utf-8&aq=t&rls=org.mozilla:en-US:official&client=firefox-a

  44. Adv : • Easy and convenient Disadv : • Possibility that members of units are different from one another, decreasing the sampling’s effectiveness

  45. TYPES OF NON-PROBABILITY SAMPLING • Convenience Sampling • Quota sampling • Purposive Sampling • Snowball sampling

  46. 1. Convenience Sampling When the sample is captive. • Adv : • convenient and inexpensive • Disadv : • results in questionable representativeness.

  47. 2. Quota sampling When strata are present, and stratified, sampling is not possible • Adv : • Ensures some degree of representativeness of all the strata in the population • Disadv : • Results in questionable representativeness

  48. 3. Purposive Sampling • Researcher uses own judgment in the selection of sample members • Sometimes called a judgmental sample.

  49. 4. Snowball sampling A technique often used in rare populations; each subject interviewed is asked to identify others.

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