BRM_PPT_Ch_03 - VG.ppsnwntxJkxjdndnndndndbdnbdbx

Sbbsn

1. Chapter-3 Measurement and Scaling Concepts © 2016 Cengage Learning India Pvt. Ltd. All rights reserved.

2. Syllabus : - Measurement Concepts, Questionnaire design and Sampling Introduction – variables – constructs - measurement scales – nominal, ordinal, interval and ratio. Criteria for good measurement – reliability and validity. Attitude measurement – attitude rating scales – Likert scale, semantic differential scale. Questionnaire design – Basic considerations – wording questions – guidelines for constructing questions – questionnaire layout. Sampling – population, sample, sampling frame, sampling units, sampling and non – sampling errors. Non – probability sampling – convenience, judgment, quota and snowball sampling. Probability sampling – simple random sampling, systematic sampling, stratified sampling methods © 2016 Cengage Learning India Pvt. Ltd. All rights reserved.

3. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. What Do I Measure? Measurement The process of describing some property of a phenomenon, usually by assigning numbers in a reliable and valid way. Concept A generalized idea about a class of objects, attributes, occurrences, or processes

4. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Operational Definitions Operationalization The process of identifying scales that correspond to variance in a concept involved in a research process. Scales A device providing a range of values that correspond to different characteristics or amounts of a characteristic exhibited in observing a concept. Correspondence rules Indicate the way that a certain value on a scale corresponds to some true value of a concept.

5. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Operational Definitions (cont’d) Variable Anything that varies or changes from one instance to another; can exhibit differences in value, usually in magnitude or strength, or in direction. Capture different values of a concept. Constructs Concepts measured with multiple variables.

6. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Levels of Scale Measurement Nominal No order, distance and origin. Assigns a value to an object for identification or classification purposes. Most elementary level of measurement. Ordinal There is order, but no distance and origin Ranking scales allowing things to be arranged based on how much of some concept they possible. Have nominal properties.

7. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Levels of Scale Measurement (cont’d) Interval There are order and distance, but no origin Capture information about differences in quantities of a concept. Have both nominal and ordinal properties. Ratio There are order, distance and origin. Highest form of measurement. Have all the properties of interval scales with the additional attribute of representing absolute quantities. Absolute zero.

8. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 13. 4 Nominal, Ordinal, Interval, and Ratio Scales Provide Different Information

9. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 13. 5 Facts About the Four Levels of Scales

10. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Mathematical and Statistical Analysis of Scales Discrete Measures Measures that can take on only one of a finite number of values. Continuous Measures Measures that reflect the intensity of a concept by assigning values that can take on any value along some scale range.

11. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Computing Scale Values Summated Scale A scale created by simply summing (adding together) the response to each item making up the composite measure. Reverse Coding Means that the value assigned for a response is treated oppositely from the other items.

12. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 13. 6 Computing a Composite Scale

13. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Three Criteria for Good Measurement Sensitivity Reliability Validity Good Measurement

14. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Reliability Reliability The degree to which measures are free from random error and therefore yield consistent results. An indicator of a measure’s internal consistency. Internal Consistency Represents a measure’s homogeneity or the extent to which each indicator of a concept converges on some common meaning. Measured by correlating scores on subsets of items making up a scale.

15. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Validity Validity The accuracy of a measure or the extent to which a score truthfully represents a concept. Does a scale measure what was intended to be measured? Establishing Validity: Is there a consensus that the scale measures what it is supposed to measure? Does the measure correlate with other measures of the same concept? Does the behavior expected from the measure predict actual observed behavior?

16. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Validity (cont’d) Face Validity A scale’s content logically appears to reflect what was intended to be measured. Content Validity The degree that a measure covers the breadth of the domain of interest. Criterion Validity The ability of a measure to correlate with other standard measures of similar constructs or established criteria. Construct Validity Exists when a measure reliably measures and truthfully represents a unique concept.

17. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Validity (cont’d) Convergent Validity Another way of expressing internal consistency; highly reliable scales contain convergent validity. Discriminant Validity Represents how unique or distinct is a measure; a scale should not correlate too highly with a measure of a different construct.

18. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 13. 7 Reliability and Validity on Target

19. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. What is An Attitude? Attitude An enduring disposition to consistently respond in a given manner to various aspects of the world. Components of attitudes: Affective Component The feelings or emotions toward an object Cognitive Component Knowledge and beliefs about an object Behavioral Component Predisposition to action Intentions Behavioral expectations

20. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Techniques for Measuring Attitudes Ranking Requiring the respondent to rank order objects in overall performance on the basis of a characteristic or stimulus. Rating Asking the respondent to estimate the magnitude of a characteristic, or quality, that an object possesses by indicating on a scale where he or she would rate an object.

21. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Techniques for Measuring Attitudes Sorting Presenting the respondent with several concepts typed on cards and requiring the respondent to arrange the cards into a number of piles or otherwise classify the concepts. Choice Asking a respondent to choose one alternative from among several alternatives; it is assumed that the chosen alternative is preferred over the others.

22. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Attitude Rating Scales Simple Attitude Scale Requires that an individual agree/disagree with a statement or respond to a single question. This type of self-rating scale classifies respondents into one of two categories (e.g., yes or no). Example: THE PRESIDENT SHOULD RUN FOR RE-ELECTION _______ AGREE ______ DISAGREE

23. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Attitude Rating Scales (cont’d) Category Scale A more sensitive measure than a simple scale in that it can have more than two response categories. Question construction is an extremely important factor in increasing the usefulness of these scales. Example: How important were the following in your decision to visit San Diego? (check one for each item) VERY SOMEWHAT NOT TOO IMPORTANT IMPORTANT IMPORTANT CLIMATE ___________ ___________ ___________ COST OF TRAVEL ___________ ___________ ___________ FAMILY ORIENTED ___________ ___________ ___________ EDUCATIONAL/HISTORICAL ASPECTS ___________ ___________ ___________ FAMILIARITY WITH AREA ___________ ___________ ___________

24. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 14. 1 Selected Category Scales

25. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Attitude Rating Scales (cont’d) Likert Scale A popular means for measuring attitudes. Respondents indicate their own attitudes by checking how strongly they agree or disagree with statements. Typical response alternatives: “strongly agree,” “agree,” “uncertain,” “disagree,” and “strongly disagree.” Example: It is more fun to play a tough, competitive tennis match than to play an easy one. ___Strongly Agree ___Agree ___Not Sure ___Disagree ___Strongly Disagree

26. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 14. 2 Likert Scale Items for Measuring Attitudes toward Patients’ Interaction with a Physician’s Service Staff

27. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Attitude Rating Scales (cont’d) Semantic Differential A series of seven-point rating scales with bipolar adjectives, such as “good” and “bad,” anchoring the ends (or poles) of the scale. A weight is assigned to each position on the scale. Traditionally, scores are 7, 6, 5, 4, 3, 2, 1, or +3, +2, +1, 0, -1, -2, -3. Example: Exciting ___ : ___ : ___ : ___ : ___ : ___ : ___ Calm Interesting ___ : ___ : ___ : ___ : ___ : ___ : ___ Dull Simple ___ : ___ : ___ : ___ : ___ : ___ : ___ Complex Passive ___ : ___ : ___ : ___ : ___ : ___ : ___ Active

28. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 14. 3 Semantic Differential Scales for Measuring Attitudes Toward Supermarkets

29. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Other Scale Types (cont’d) Image Profile A graphic representation of semantic differential data for competing brands, products, or stores to highlight comparisons. Because the data are assumed to be interval, either the arithmetic mean or the median will be used to compare the profile of one product, brand, or store with that of a competing product, brand, or store.

30. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 14. 4 Image Profiles of Commuter Airlines versus Major Airlines

31. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Attitude Rating Scales (cont’d) Numerical Scales Scales that have numbers as response options, rather than “semantic space” or verbal descriptions, to identify categories (response positions). In practice, researchers have found that a scale with numerical labels for intermediate points on the scale is as effective a measure as the true semantic differential. Example: Now that you’ve had your automobile for about one year, please tell us how satisfied you are with your Ford Taurus. Extremely Dissatisfied 1 2 3 4 5 6 7 Extremely Satisfied

32. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Other Scale Types (cont’d) Stapel Scale Uses a single adjective as a substitute for the semantic differential when it is difficult to create pairs of bipolar adjectives. Tends to be easier to conduct and administer than a semantic differential scale.

33. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 14. 5 A Stapel Scale for Measuring a Store’s Image

34. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Other Scale Types (cont’d) Constant-Sum Scale Respondents are asked to divide a constant sum to indicate the relative importance of attributes. Respondents often sort cards, but the task may also be a rating task (e.g., indicating brand preference). Example: Divide 100 points among each of the following brands according to your preference for the brand: Brand A _________ Brand B _________ Brand C _________

35. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Other Scale Types (cont’d) Graphic Rating Scale A measure of attitude that allows respondents to rate an object by choosing any point along a graphic continuum. Advantage: Allows the researcher to choose any interval desired for scoring purposes. Disadvantage: There are no standard answers.

36. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 14. 6 Graphic Rating Scale

37. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 14. 7 A Ladder Scale

38. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 14. 8 Graphic Rating Scale with Picture Response Categories Stressing Visual Communication

39. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 14. 9 Summary of Advantages and Disadvantages of Rating Scales

40. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Measuring Behavioral Intention Behavioral Component The behavioral expectations (expected future actions) of an individual toward an attitudinal object. Example: How likely is it that you will purchase a Honda Fit? I definitely will buy I probably will buy I might buy I probably will not buy I definitely will not buy

41. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Measuring Behavioral Intention Behavioral Differential A rating scale instrument similar to a semantic differential, developed to measure the behavioral intentions of subjects toward future actions. A description of the object to be judged is placed on the top of a sheet, and the subjects indicate their behavioral intentions toward this object on a series of scales. Example: A 25 year-old woman sales representative Would ___ : ___ : ___ : ___ : ___ : ___ : ___ : Would Not ask this person for advice.

42. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Ranking An ordinal scale may be developed by asking respondents to rank order (from most preferred to least preferred) a set of objects or attributes. Paired comparisons Sorting

43. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Paired Comparison A measurement technique that involves presenting the respondent with two objects and asking the respondent to pick the preferred object; more than two objects may be presented, but comparisons are made in pairs. Number of comparisons = [(n)(n-1)/2] Example: I would like to know your overall opinion of two brands of adhesive bandages. They are MedBand and Super-Aid. Overall, which of these two brands—MedBand or Super-Aid—do you think is the better one? Or are both the same? MedBand is better _____ Super-Aid is better _____ They are the same _____

44. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Sorting Require that respondents indicate their attitudes or beliefs by arranging items on the basis of perceived similarity or some other attribute. Example: Here is a sheet that lists several airlines. Next to the name of each airline is a pocket. Here are ten cards. I would like you to put these cards in the pockets next to the airlines you would prefer to fly on your next trip. Assume that all of the airlines fly to wherever you would choose to travel. You can put as many cards as you want next to an airline, or you can put no cards next to an airline. Cards American Airlines _____ Delta Airlines _____ United Airlines _____ Southwest Airlines _____ Northwest Airlines _____

45. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Selecting a Measurement Scale Some Practical Questions: Is a ranking, sorting, rating, or choice technique best? Should a monadic or a comparative scale be used? What type of category labels, if any, will be used for the rating scale? How many scale categories or response positions are needed to accurately measure an attitude? Should a balanced or unbalanced rating scale be chosen? Should a scale that forces a choice among predetermined options be used? Should a single measure or an index measure be used?

46. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Selecting a Measurement Scale (cont’d) Monadic Rating Scale Asks about a single concept in isolation. The respondent is not given a specific frame of reference. Example: Now that you’ve had your automobile for about 1 year, please tell us how satisfied you are with its engine power and pickup.

47. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Please indicate how the amount of authority in your present position compares with the amount of authority that would be ideal for this position. TOO MUCH  ABOUT RIGHT  TOO LITTLE  Selecting a Measurement Scale (cont’d) Comparative Rating Scale Asks respondents to rate a concept in comparison with a benchmark explicitly used as a frame of reference. Example:

48. Questionnaire Design © 2016 Cengage Learning India Pvt. Ltd. All rights reserved.

49. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Questionnaire Quality and Design: Basic Considerations Questionnaire design is one of the most critical stages in the survey research process. A questionnaire (survey) is only as good as the questions it asks —ask a bad question, get bad results . Composing a good questionnaire appears easy, but it is usually the result of long, painstaking work. The questions must meet the basic criteria of relevance and accuracy .

50. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Decisions in Questionnaire Design What should be asked? How should questions be phrased? In what sequence should the questions be arranged? What questionnaire layout will best serve the research objectives? How should the questionnaire be pretested? Does the questionnaire need to be revised?

51. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. What Should Be Asked? Questionnaire Relevancy All information collected should address a research question in helping the decision maker in solving the current business problem. Questionnaire Accuracy Increasing the reliability and validity of respondent information requires that: Questionnaires should use simple, understandable, unbiased, unambiguous, and nonirritating words. Questionnaire design should facilitate recall and motivate respondents to cooperate. Proper question wording and sequencing to avoid confusion and biased answers.

52. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Wording Questions Open-ended Response Questions Pose some problem and ask respondents to answer in their own words. Advantages: Are most beneficial in exploratory research, especially when the range of responses is not known. May reveal unanticipated reactions toward the product. Are good first questions because they allow respondents to warm up to the questioning process. Disadvantages: High cost of administering open-ended response questions. The possibility that interviewer bias will influence the answer. Bias introduced by articulate individuals’ longer answers.

53. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Wording Questions (cont’d) Fixed-alternative Questions Questions in which respondents are given specific, limited-alternative responses and asked to choose the one closest to their own viewpoint. Advantages: Require less interviewer skill Take less time to answer Are easier for the respondent to answer Provides comparability of answers Disadvantages: Lack of range in the response alternatives Tendency of respondents to choose convenient alternative

54. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Types of Fixed-Alternative Questions Simple-dichotomy (dichotomous) Question Requires the respondent to choose one of two alternatives (e.g., yes or no). Determinant-choice Question Requires the respondent to choose one response from among multiple alternatives (e.g., A, B, or C). Frequency-determination Question Asks for an answer about general frequency of occurrence (e.g., often, occasionally, or never). Checklist Question Allows the respondent to provide multiple answers to a single question by checking off items.

55. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Phrasing Questions for Self-Administered, Telephone, and Personal Interview Surveys Influences on Question Phrasing: The means of data collection—telephone interview, personal interview, self-administered questionnaire—will influence the question format and question phrasing. Questions for mail, Internet, and telephone surveys must be less complex than those used in personal interviews. Questionnaires for telephone and personal interviews should be written in a conversational style.

56. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 15. 1 Reducing Question Complexity by Providing Fewer Responses for Telephone Interviews

57. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Guidelines for Constructing Questions Avoid complexity: Simpler language is better. Avoid leading and loaded questions. Avoid ambiguity: Be as specific as possible. Avoid double-barreled items. Avoid making assumptions. Avoid burdensome questions that may tax the respondent’s memory. Make certain questions generate variance.

58. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. What Is the Best Question Sequence? Order bias Bias caused by the influence of earlier questions in a questionnaire or by an answer’s position in a set of answers. Funnel technique Asking general questions before specific questions in order to obtain unbiased responses. Filter question A question that screens out respondents who are not qualified to answer a second question. Pivot question A filter question used to determine which version of a second question will be asked.

59. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 15. 2 Flow of Questions to Determine the Level of Prompting Required to Stimulate Recall

60. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. What Is the Best Layout? Traditional Questionnaires Multiple-grid question Several similar questions arranged in a grid format. The title of a questionnaire should be phrased carefully: To capture the respondent’s interest, underline the importance of the research Emphasize the interesting nature of the study Appeal to the respondent’s ego Emphasize the confidential nature of the study To not bias the respondent in the same way that a leading question might

61. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 15. 3 Layout of a Page from a Telephone Questionnaire

62. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 15. 4 Telephone Questionnaire with Skip Questions

63. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 15. 5 Personal Interview Questionnaire

64. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 15. 6 Example of a Skip Question

65. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Internet Questionnaires Graphical User Interface (GUI) Software The researcher can control the background, colors, fonts, and other features displayed on the screen so as to create an attractive and easy-to-use interface between the user and the Internet survey. Layout Issues Paging layout - going from screen to screen. Scrolling layout – entire questionnaire appears on one page and respondent has the ability to scroll down.

66. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Internet Questionnaire Layout Push Button A small outlined area, such as a rectangle or an arrow, that the respondent clicks on to select an option or perform a function, such as submit. Status Bar A visual indicator that tells the respondent what portion of the survey he or she has completed. Radio Button A circular icon, resembling a button, that activates one response choice and deactivates others when a respondent clicks on it.

67. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Internet Questionnaire Layout (cont’d) Drop-down Box A space saving device that reveals responses when they are needed but otherwise hides them from view. Check Boxes Small graphic boxes, next to an answers, that a respondent clicks on to choose an answer; typically, a check mark or an X appears in the box when the respondent clicks on it. Open-ended Boxes Boxes where respondents can type in their own answers to open-ended questions. Pop-up Boxes Boxes that appear at selected points and contain information or instructions for respondents.

68. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 15. 7 Question in an Online Screening Survey for Joining a Consumer Panel

69. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. EXHIBIT 15. 8 Alternative Ways of Displaying Internet Questions

70. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Internet Questionnaire Layout (cont’d) Software That Makes Questionnaires Interactive Variable piping software Allows variables to be inserted into an Internet questionnaire as a respondent is completing it. Error trapping software Controls the flow of an Internet questionnaire. Forced answering software Prevents respondents from continuing with an Internet questionnaire if they fail to answer a question. Interactive help desk A live, real-time support feature that solves problems or answers questions respondents may encounter in completing the questionnaire.

71. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Pretesting and Revising Questionnaires Pretesting Process Seeks to determine whether respondents have any difficulty understanding the questionnaire and whether there are any ambiguous or biased questions. Preliminary Tabulation A tabulation of the results of a pretest to help determine whether the questionnaire will meet the objectives of the research.

72. © 2016 Cengage Learning India Pvt. Ltd. All rights reserved. Designing Questionnaires for Global Markets Back Translation Taking a questionnaire that has previously been translated into another language and having a second, independent translator translate it back to the original language. A questionnaire developed in one country may be difficult to translate because equivalent language concepts do not exist or because of differences in idiom and vernacular.

73. Sampling: - Concepts- Types of Sampling - Probability Sampling – simple random sampling, systematic sampling, stratified random sampling, cluster sampling -Non Probability Sampling –convenience sampling- judge mental sampling, snowball sampling- quota sampling - Errors in sampling.

74. Sampling Sampling: The process of using a small number of items or parts of a larger population to make conclusions about the whole population. OR A method by which some items of a given population are selected as representatives of the entire population OR A subset, or some part of a larger population. Population: A complete group of entities sharing some common set of characteristics.

75. Sampling Sample Frame: The list of elements from which a sample may be drawn is called sample frame. Ex: The list of all members of city cricket association, the list of students who are studying MBA will be a sample frame. Sampling Frame Error: Error that occurs when certain sample elements are not listed or available and are not represented in the sampling frame. Sampling Unit: A single element or group of elements subject to selection in the sample. Example: If an airline, wishes to sample passengers, every 25th name on a complete list of passengers may be taken. In a random digit dialing, a sample unit will be telephone numbers. Random sampling error: It is the difference between the sample result and the result of a census conducted by the identical procedures.

76. Steps in Sampling Process: Defining the target population Select a sampling frame Determine if a probability or non probability sampling method will be chosen Plan procedure for selecting sampling units Determine sample size Select actual sampling units Conduct field work

77. Types of Sampling Probability sampling -- every member has an equal chance of being selected. Non-probability sampling - we don’t know the probability of selecting a unit into a particular sample.

78. Probability Sampling simple random sampling, systematic sampling, stratified random sampling, cluster sampling. Multiple stage sampling

79. Simple random sampling Simple random sampling ensures that each possible sample has an equal probability of being selected, and each item in the entire population has an equal chance of being included in the sample. The entire process of sampling is done in a single step with each subject selected independently of the other members of the population. There are many methods to proceed with simple random sampling. The most primitive and mechanical would be the lottery method.

80. Conti… Each member of the population is assigned a unique number. Each number is placed in a bowl or a hat and mixed thoroughly. The blind-folded researcher then picks numbered tags from the hat. All the individuals bearing the numbers picked by the researcher are the subjects for the study. Another way would be to let a computer do a random selection from your population. For populations with a small number of members, it is advisable to use the first method but if the population has many members, a computer-aided random selection is preferred.

81. Systematic Sampling In systematic random sampling, the researcher first randomly picks the first item or subject from the population. Then, the researcher will select each n'th subject from the list. The procedure involved in systematic random sampling is very easy and can be done manually. The results are representative of the population unless certain characteristics of the population are repeated for every n'th individual, which is highly unlikely.

82. Conti… The process of obtaining the systematic sample is much like an arithmetic progression. Starting number : The researcher selects an integer that must be less than the total number of individuals in the population. This integer will correspond to the first subject. Interval : The researcher picks another integer which will serve as the constant difference between any two consecutive numbers in the progression. The integer is typically selected so that the researcher obtains the correct sample size For example, the researcher has a population total of 100 individuals and need 12 subjects. He first picks his starting number, 5. Then the researcher picks his interval, 8. The members of his sample will be individuals 5, 13, 21, 29, 37, 45, 53, 61, 69, 77, 85, 97.

83. Stratified Sampling Stratified sampling is a probability sampling technique wherein the researcher divides the entire population into different subgroups or strata, then randomly selects the final subjects proportionally from the different strata . It is important to note that the strata must be non-overlapping. This completely negates the concept of stratified sampling as a type of probability sampling. Equally important is the fact that the researcher must use simple probability sampling within the different strata. The most common strata used in stratified random sampling are age, gender, socioeconomic status, religion, nationality and educational attainment.

84. Stratified Sampling

85. Cluster Sampling In cluster sampling, instead of selecting all the subjects from the entire population right off, the researcher takes several steps in gathering his sample population. First, the researcher selects groups or clusters, and then from each cluster, the researcher selects the individual subjects by either simple random or systematic random sampling. The researcher can even opt to include the entire cluster and not just a subset from it. The most common cluster used in research is a geographical cluster. For example, a researcher wants to survey academic performance of high school students in Spain. He can divide the entire population (population of Spain) into different clusters (cities).

86. Conti… Then the researcher selects a number of clusters depending on his research through simple or systematic random sampling. Then, from the selected clusters (randomly selected cities) the researcher can either include all the high school students as subjects or he can select a number of subjects from each cluster through simple or systematic random sampling. The important thing to remember about this sampling technique is to give all the clusters equal chances of being selected. Types of cluster sample. ONE-STAGE CLUSTER SAMPLE TWO-STAGE CLUSTER SAMPLE

87. Cluster Sampling

88. Multiple stage sampling Multistage sampling: The given population is heterogeneous, so it is broken into two which will give you homogenous data. Those data is called clusters or strata. This method of study is Multistaged sampling. Ex: If you are doing census then you divide people into urban, semi-urban groups which will be your strata. You can also divide people into different age groups that you can arrange systematically & study. consecutive sampling example : sampling unit = household 1 st stage: draw neighborhoods 2 nd stage: draw buildings 3 rd stage: draw households

89. Multiple stage sampling

90. Probability Sampling Comparision

91. Non random sampling (Non-probability sampling) Non probability sampling is also known by different names such as deliberate sampling, purposive and judgement sampling. It is that 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. It does not allow the study's findings to be generalized from the sample to the population. When discussing the results of a non-probability sample, the researcher must limit his/her findings to the persons or elements sampled.

92. Non random sampling (Non-probability sampling) Non probability sampling is also known by different names such as deliberate sampling, purposive and judgement sampling. It is that 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. It does not allow the study's findings to be generalized from the sample to the population. When discussing the results of a non-probability sample, the researcher must limit his/her findings to the persons or elements sampled.

93. Non-Probability Sampling: Convenience sampling : Quota sampling : Judgment sampling Snow-balling :

94. Convenience sampling Convenience sampling is a non-probability sampling technique where subjects are selected because of their convenient accessibility and proximity to the researcher. The subjects are selected just because they are easiest to recruit for the study and the researcher did not consider selecting subjects that are representative of the entire population.

95. Conti… Any thing which is convenient that is related to your friends, relatives etc. so that data can be collected conveniently. This method is called convenience sampling. In all forms of research, it would be ideal to test the entire population, but in most cases, the population is just too large that it is impossible to include every individual. This is the reason why most researchers rely on sampling techniques like convenience sampling, the most common of all sampling techniques. Many researchers prefer this sampling technique because it is fast, inexpensive, easy and the subjects are readily available.

96. Quota Sampling Quota sampling is a non-probability sampling technique wherein the assembled sample has the same proportions of individuals as the entire population with respect to known characteristics, traits or focused phenomenon. In addition to this, the researcher must make sure that the composition of the final sample to be used in the study meets the research’s quota criteria. The main reason why researchers choose quota samples is that it allows the researchers to sample a subgroup that is of great interest to the study. If a study aims to investigate a trait or a characteristic of a certain subgroup, this type of sampling is the ideal technique. Quota sampling also allows the researchers to observe relationships between subgroups. In some studies, traits of a certain subgroup interact with other traits of another subgroup. Ex: An interviewer may fix a quota that out of 100 questionnaires 70 has to be men amd 30 has to be female.

97. Quota Sampling

98. Purposive sampling In purposive sampling we sample with a purpose in mind. In purposive sampling, the researcher employs his or her own "expert” judgment about who to include in the sample frame. Prior knowledge and research skill are used in selecting the respondents or elements to be sampled. We usually would have one or more specific predefined groups we are seeking . Used for situations for reaching a target sample quickly. used in pilot studies , selection of few cases for intensive study, Studying critical cases-- key informants.

99. Judgement sampling : A non probability sampling technique in which an experienced individual selects the sample based upon some appropriate characteristic of the sample members. A form of convenience sampling in which the population elements are purposively selected based on the judgement of the researcher. It is low cost, convenient and quick. It is useful if broad population inferences are not required. Good reasons for use of purposive sampling

100. Judgement sampling

101. Snowball sampling A sampling procedure in which initial respondents are selected by probability methods and additional respondents are obtained from information provided by the initial respondents. In snowball sampling, you begin with identifying someone who meets the criteria for inclusion in your studies You then ask them to recommend others who they may know who also meet the criteria. It is useful when you are trying to reach populations that are inaccessible or hard to find.

102. Errors in Sampling: Conscious or unconscious bias in the selection of a sample Deliberate selection of a non-representative sample Substitution of an item in place of the one chosen in a random sampling. Incomplete coverage of the units in the sample. Defective process of selection Faulty work during the collection of information and Incorrect methods of analysis.