Chapter 1 introduction

1
Chapter 1 introduction

• What is social research?
• Way of knowing social reality by direct
  experience
• Definition
• The differences between social research and
  ??????

2
Functions or purposesof social research

• Description(??)
• A major purpose of many social scientific studies
  is to describe situations and events. The
  researcher observes and then describes what was
  observed. Since scientific observations is
  careful and deliberate, however, scientific
  descriptions are typically more accurate and
  precise than casual descriptions. (P73)
• Examples
• ???????? ????????

3
Explanation(??)

• The second general purposes of social scientific
  research is to explain things. Reporting the
  voting intentions of an electorate is a
  descriptive activity, but reporting why some
  people plan to vote for candidate A and others
  for candidate B is an explanatory activity.
  Reporting why some cities have higher crime rates
  than others is a case of explanation, but simply
  reporting the different crime rates is a case of
  description.

4
Prediction(??)

• For example, the goal of regression analysis is
  find out the relationship between two or more
  variables.

5
2. Types of research methods

• Objetctive dimension
• A. Census(??).
• An enumeration(??) of the characteristics of some
  population(??). A census is often similar to a
  survey, with the difference that the census
  collects data from all members of the population
  while the survey is limited to a sample.
• B.

6
B. Sampling survey (????)

• Careful probability sampling provides a group of
  respondents whose characteristics may be taken to
  reflect those of the larger population, and
  carefully constructed standardized questionnaires
  provide data in the same form from all
  respondents.

7
C. Case study (????)

• Take only several members from the population and
  study them in detail.

8
Purposive Dimension

• descriptive studies (?????)
• explanatory studies (?????)

9
time dimension.

• Cross-sectional Study(????). A study that is
  based on observations representing a single point
  in time.
• Longitudinal Study(????). A study design
  involving the collection of data at different
  points in time, as contrasted with a
  cross-sectional study.

10

• Longitudinal studies are designed to permit
  observations over an extended period. Three types
  of longitudinal studies should be noted here.
• Trend studies (????) are those that study changes
  within some general population over time.
  Examples would be a comparison of U. S. Census
  over time, showing growth in the national
  population, or a series of Gallup Polls during
  the course of an election campaign, showing
  trends in the relative strengths and standing of
  different candidates.

11

• Cohort Studies (?????) examine more specific
  subpopulations (cohorts) as they change over
  time. Typically, a cohort is an age group, such
  as those people born during the 1920s, but it can
  also be based on some other time grouping, such
  as people attending college during the Vietnam
  War, people who got married in 1964, and so forth.

12

• An example of cohort study would be a series of
  national surveys, conducted perhaps every 10
  years, to study the economic attitudes of the
  cohort born during the depression of the early
  1930s. a sample of persons 20-25 years of age
  might be surveyed in 1960, and another sample of
  those 40-45 years of age in 1970. Although the
  specific set of people studied in each of those
  surveys would be different, each sample would
  represent the survivors of the cohort born
  between 1930 and 1935.

13

• Panel Studies(????,????) are similar to trend and
  cohort studies except that the same set of people
  is studied each time. One example would be a
  voting study in which the same sample of voters
  was interviewed every month during an election
  campaign and asked for whom they would intended
  to vote. Such a study would make it possible to
  analyze overall trends in voter preferences for
  different candidates, but it would have the added
  advantage of showing the precise patterns of
  persistence and change in intentions.

14

• For example, a trend study that showed that
  Candidates A and B each had exactly half of the
  voters on September first and on October first as
  well could indicate that none of the electorate
  had changed voting plans, that all of the voters
  had changed their intentions, or something
  between. A panel study would eliminate this
  confusion by showing what kinds of voters
  switched from A to B and what kinds switched from
  B to A, as well as other facts.

15
Procedures of social research

• Preparatory stage(????)
• Data collection stage (??????)
• Analysis stage (????)
• Summary stage (????)

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Chapter 2 research design

• 1. Choose a research project
• a)  How to choose a research project
•   b)  Factors relating with research project
  choice
• c)  Principles regarding research project choice
• 2. Preliminary Exploration
• a)  Literature review
• b) Filed observation
• 3.Research Project Design
• a)  Research hypothesis
• b)  Research plan

17
2.1 Literature Review

• 1. Purposes of Literature Review
• To avoid redundant research and try to make new
  contributions
• To provide bases for hypothesis
• To take other researches as references for your
  research plan
• 2. How to Review Literature
• Snowball method according to the references and
  notes of the existing literature to look for more
  related literature
• Electronic resources

18
2.2 Field Observation

• Methods colloquia(???), interview, refer to
  literature
• Purpose1 for questionnaire design
• Example how to measure peasant family income
  into three levels high, medium and low
• Purpose 2 for hypothesis
• Example

Economic development
Implementation of electoral system
Villagers participation
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3. Research Project Design

• 3.1 Research Hypothesis
• Hypothesis An expectation about the nature of
  things derived from a theory.
• Functions of hypothesis
• To guild a research
• To relate theoretical concepts with empirical
  data
• To explore new theoretical knowledge
• Principles for making hypothesis
• Consistent with existing theories
• Consistent with confirmed facts
• Can be verified by experience

20
3.2 Research Project Design

• Purposes
• Population and objects
• Sampling methods
• Methods of data collection and data analysis
• Organization
• Budget and facilities
• Wages, travelling expenses, expense for copying
  and printing
• Facilities camera, tape recorder, computer
• Timetable

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Chapter 3 Sampling

• 3.1 Introduction to Sampling
• 1. The history of sampling
• 2. Sampling concepts and terminology
• 3.2 Probability Sampling (????)
• 1. Simple random sampling (SRS) ??????
• 2. Systematic sampling ????
• 3. Stratified sampling ????
• 4. Cluster sampling ????
• 5. Multi-stage sampling ????
• 3.3 Non-Probability Sampling(?????)
• 1. Purposive or judgment sampling ????
• 2. Quota sampling ????
• 3. Snowball sampling ?????

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3.1 Introduction to Sampling

• 1. The history of sampling
• Political polling by Literacy Digest
• In 1920, Digest editors mailed postcards to
  people in six states, asking them who they were
  planning to vote for in the presidential campaign
  between Warren Harding and James Cox. Names were
  selected for the poll from telephone directories
  and automobile registration lists. Based on the
  postcards sent back, the Digest correctly
  predicted that Harding would be elected. In
  elections that followed, the magazine expanded
  the size of its poll, and made correct
  predictions in 1924, 1928, and 1932.
• In 1936, based on two million respondents
  answers, the Digest predicted that Republican
  candidate Alf Landon would get 57 ballots and
  incumbent President Franklin Roosevelt would get
  only 43. Two weeks later, voters gave Roosevelt
  a third term in office by the largest landslide
  in history, with 61 per cent of the vote.
• The problem lay in the sampling frame used
  telephone subscribers and automobile owners. Such
  a sampling design selected a disproportionately
  wealthy people, especially coming on the tail end
  of the worst economic depression in the nation
  history.

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3.1 Introduction to Sampling

• (continued)
• In contrast to the Literacy Digest, George Gallup
  correctly predicted that Roosevelt would beat
  Landon. Gallups success in 1936 hinged on his
  use of quota sampling.
• Quota sampling is based on a knowledge of the
  characteristics of the population being sampled
  what proportion are men, what proportion women,
  what proportions are of various incomes, ages,
  etc. People are selected to match the population
  characteristics.

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3.1 Introduction to Sampling 2. Sampling
Concepts and Terminology (1)

• i.      1.Element(????). An element is that
  unit about which information is collected and
  which provides the basis of analysis.
• Typically, in survey research, elements are
  people or certain types of people. However, other
  kinds of units can constitute the elements for
  social research families, social clubs, or
  corporations might be the elements of a study.
  (Note Elements and units of analysis are often
  the same in a given study, though the former
  refers to sample selection while the latter
  refers to data analysis.)

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2. Sampling Concepts and Terminology (2)

• 1.Population (??). A population is the
  theoretically specified aggregation of study
  elements.
• For example, specifying the term college
  students would include a consideration of
  full-time and part-time students, degree
  candidates and non-degree candidates,
  undergraduate and graduate students, and similar
  issues.
• 2. Study Population(????). A study population is
  that aggregation of elements from which the
  sample is actually selected.
• As a practical matter, you are seldom in a
  position to guarantee that every element meeting
  the theoretical definitions laid down actually
  has a chance of being selected in the sample.
  Even where lists of elements exist for sampling
  purposes, the lists are usually somewhat
  incomplete. Some students are always omitted,
  inadvertently, from student roster. Some
  telephone subscribers request that their names
  and numbers be unlisted. The study population,
  then, is the aggregation of elements from which
  the sample is selected.

26
2. Sampling Concepts and Terminology (3)

• 3. Sampling Unit(????). A sampling unit is that
  element or set of elements considered for
  selection in some stage of sampling.
• In a simple, single-stage sample, the sampling
  units are the same as the elements. In more
  complex samples, however, different levels of
  sampling units may be employed. For example, you
  might select a sample of census blocks in a city,
  then select a sample of households on the
  selected blocks, and finally select a sample of
  adults from selected households.
• 4. Sampling Frame(???). A sampling frame is the
  actual list of sampling units from which the
  sample, or some stage of the sample, is selected.
• 5. Observation Unit(????). An observation unit,
  or unit of data collection, is an elements from
  which information is collected.
• Again, the unit of analysis and unit of
  observation are often the samethe individual
  personbut that need not be the case. Thus the
  researcher may interview heads of households (the
  observation unit) to collect information about
  all family members of the households ( the units
  of analysis).

27
2. Sampling Concepts and Terminology (4)

• 6. Variable(??). A variable is a set of mutually
  exclusive attributes sex, age, employment
  status, and so forth.
• 7. Parameter(???). A parameter is the summary
  description of a given variable in a population.
• 8. Statistic(???). A statistic is the summary
  description of a given variable in a sample.
  Sample statistics are used to make estimates of
  population parameters.
• 9.Sampling Error(????). Probability sampling
  methods seldom, if ever, provide statistics
  exactly equal to the parameters that they are
  used to estimate. Probability theory, however,
  permits us to estimate the degree of error to be
  expected for a given sample design.

28
2. Sampling Concepts and Terminology (5)

• 10. Confidence Levels and Confidence
  Intervals(??????????).
• We express the accuracy of our sample statistics
  in terms of a level of confidence that the
  statistics fall within a specified interval from
  the parameter.
• For example, we may say we are 95 percent
  confident that our sample statistics are within
  plus or minus 5 percentage points of the
  population parameter.

29
3.2 Probability Sampling (1)

• Simple Random Sampling (??????). A type of
  probability sample in which the units composing a
  population are assigned numbers, a set of random
  numbers is then generated, and the units having
  those numbers are included in the sample.
  Although probability theory and the calculations
  it provides assume this basic sampling method, it
  is seldom used for practical reasons.

30
3.2 Probability Sampling (2)

• Systematic Sampling (????). A type of probability
  sample in which every kth unit in a list is
  selected for inclusion in the sample e.g., every
  25th student in the college directory of
  students. K is computed by dividing the size of
  the population by the desired sample size and is
  called the sampling interval. Within certain
  constraints, systematic sampling is a functional
  equivalent of simple random sampling and usually
  easier to do.
•           Sampling interval population size /
  sample size
• sampling ratio sample size / population
  size

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3.2 Probability Sampling (3)

• Stratified sampling (????) to organize the
  population into homogeneous subsets (with
  heterogeneity between subsets.) and to select the
  appropriate number of elements from each.

32
3.2 Probability Sampling (4)

• Cluster Sampling (????). A multistage sample in
  which natural groups (clusters) are sampled
  initially, with the members of each selected
  group being subsampled afterward .
• For example, you might select a sample of U.S.
  colleges and universities from a directory, get
  lists of the students at all the selected
  schools, then draw samples of students from each.

33
3.3 Non-Probability Sampling (1)

• Purposive or judgmental sampling(????). A type of
  nonprobability sampling in which you select the
  units to be observed on the basis of your own
  judgment about which ones will be the most useful
  or reprsentative.

34
3.3 Non-Probability Sampling (2)

• Quota sampling (????). A type of non-probability
  sampling in which units are selected into the
  sample on the basis of prespecified
  characteristics, so that the total sample will
  have the same distribution of characteristics as
  are assumed to exist in the population being
  studied.

35
3.3 Non-Probability Sampling (3)

• Snowball sampling (?????). A non-probability
  sampling method often employed in filed research.
  Each person interviewed may be asked to suggest
  additional people for interviewing.

36
3.4 Factors influencing sample size

• A. population size ????
• B. population heterogeneity ?????
• variance (??)
• C. permited sampling error ??????

37
Chapter 4 Social Measurement (??? ????)

• 4.1 Operationalization and Social
  Measurement(????????)
• A. Operationalization of Research Project
  (????????)
• B. Social Measurement (????)
• 4.2 Levels of Social Measurement (???????)
• A. Nominal Measure (????)
• B. Ordinal Measure (????)
• C. Interval Measure (????)
• D. Ratio measure (????)
• 4.3. Reliability and Validity
• A. Reliability (??)
• B. Validity (??)
• C. Relations between reliability and validity

38
4.1 Operationalization and Social Measurement
(????????)

• A. Operationalization of Research
  Project(????????)
• ????????????????????????????????????????,?????????
  ????????????,?????????????
• ??????????1)????????2)???????????3)??????????

39
a. Operational definition of concept(????)

• Operational definitiona definition that spells
  out precisely how the concept will be measured.
  Strictly speaking, an operational definition is a
  description of the operations that will be
  undertaken in measuring a concept.(???????????????
  ?????????????????????????????????????,????????????
  ??????????)
• ???????(??????????)

40
???????????

• ????
• ????????,??????
• ????
• ???12??30?????

41
b. Choice of indexes (?????)

• Examples
• Economic development(????)
• annual income per capita(?????)
• collective income(????)
• Intelligence(??)
• Couple relation(????)

42
??????????????????
????
?????
??????
1)???GDP 2)????GDP ??????? ????
43
???????????3???

• 1)???????
• 2)??????
• 3)????????
• ????????????,??????????????
• 5)???,4)???,3)???,2)???,1)???
• (??????????????????,??2005??2??)

44
??????????15???
45
?????????15???
46
c. Operationalization of hypothesis (??????)

• ?????????????,????????????????????????????????????
  ????
• ??1

????
?????
????1??? ???15???
????2??? ???3???
47
??2

• Concept Industrialization---------------
  -------?Human relation
• (??) (???)
  (????)
• Index industrial output---------------?
  times visiting each other
• (??) (??????) (??????)
• phone subscribers
• (??????)

48
B. Social Measurement (????)

• Definition in order to understand the nature,
  characteristics and conditions of the objects, we
  allocate some numbers or symbols to the objects
  according to some regulations. This process is
  called social measurement.(???????????????????,???
  ????????????????????)
• Three elements of social measurement(????????)
• Objects(??)
• Number or symbols(?????)
• Regulations(??)

49
??(????)????

• 1)????????????????
• 1??150??1??10??
• 1??10??1??10???
• 2)?????????????
• 1??1760?1?3??
• 1??12???
• 3)??????(m)???(km)???(dm)???(cm)???(mm)???(pm)?

50
4.2 Levels of Social Measuremnt(???????)

• A. Nominal Measure(????)
• Variables whose attributes have only the
  characteristics of exhaustiveness and mutual
  exclusiveness are nominal variables.
• Examples of these would be sex, religious
  affiliation, political party affiliation,
  birthplace, college major, and hair color.
• B. Ordinal Measure(????)
• Variables whose attributes may be logically
  rank-ordered are ordinal measures. The different
  attributes represent relatively more or less of
  the variable.
• Variables of this type are social class,
  conservatism, alienation, prejudice, and the
  like.

51
c. Interval Measure(????)

• For the attributes composing some variables, the
  actual distance separating those attributes does
  have meaning. Such variables are interval
  measures. For these, the logical distance between
  attributes can be expressed in meaningful
  standard intervals.
• A physical science example would be the
  Fahrenheit or Celsius temperature scale. The
  difference, or distance, between 80 degrees and
  90 degrees in the same that between 40 degrees
  and 50 degrees. However, 80 degrees Fahrenheit is
  not twice as hot as 40 degrees, since the zero
  point in the Fahrenheit and Celsius scales are
  arbitrary zero degrees does not really mean lack
  of heat, nor does 30 degrees represent 30
  degrees less than no heat.

52
D. Ratio Measures(????)

• In ratio measures , the attributes composing a
  variable, besides having all the structural
  characteristics mentioned above, are based on a
  true zero point.
• Examples from social scientific research would
  include age, length of residence in a given
  place, number of organizations belonged to,
  number of times attending church during a
  particular period of time, number of times
  married, and number of Arab friends.
• Most of the social scientific variables meeting
  the minimum requirements for interval measures
  also meet the requirements for ratio
  measurements.

53
?????????
54
4.3 Reliability and Validity (?????)

• Precision and accuracy are obviously important
  qualities in research measurement, and they
  probably need no further explanation. When social
  scientists construct and evaluate measurements,
  however, they pay special attention to two
  technical considerations reliability and
  validity.

55
A. Reliability(??)

• Reliability. That quality of measurement method
  that suggests that the same data would have been
  collected each time in repeated observations of
  the same phenomenon. (?????????????????????)
• Re-measurement reliability (?????????????????????
  ???)
• Duplicate reliability (?????????????????????????)
  
• Folded reliability (??????????????????,?????????
  ????)

56
B. Validity(??)

• Validity refers to the extent to which an
  empirical measure adequately reflects the real
  meaning of the concept under consideration.
  (??????????????????)
• Criterion-related validity(????) is based on some
  external criterion(????????????????,???????????,??
  ?????????).
• Content validity(????) refers to the degree to
  which a measure covers the range of meanings
  included within the concept(???????????????????).
  
• For example, a text of mathematical ability
  cannot be limited to addition alone but would
  also need to cover subtraction, multiplication,
  division, and so forth.

57
Construct validity (????)

• Construct validity (????)is based on the way a
  measure relate to other variables within a system
  of theoretical relationships(?????????????????????
  ??,???????????????????????????????)?

58
??2

• Concept Industrialization---------------
  -------?Human relation
• (??) (???)
  (????)
• Index industrial output---------------?
  times visiting each other
• (??) (??????) (??????)
• phone subscribers
• (??????)

59
C. Relations between Reliability and Validity

• a. reliable but not valid
• b. valid but not reliable
• C. valid and reliable

60
Chapter 5 Questionnaire

• 5.1 Types and Structure of Questionnaire
• 5.2 Questionnaire Construction
• 5.3 Attitudinal Scales

61
5.1 Types and Formats of Questionnaire (1)

• Questionnaire (??) a document containing
  questions and other types of items designed to
  solicit information appropriate to analysis.
• 1. Types of Questionnaire
• Self-administered questionnaire and
  interviewer-administered questionnaire(?????????)
• Questionnaires may be completed by the
  respondents themselves or by interviewers who
  read the items to respondents and record the
  answers.

62
5.1 Types and Formats of Questionnaire (2)

• Self-administered questionnaire
• Mailed questionnaire
• Distributed questionnaire

63
5.1 Types and Formats of Questionnaire (3)

• 2. Formats of questionnaire
• items in a questionnaire
• Instruction
• Questions and answers
• Open-ended questions (?????)
• Close-ended questions (?????)
• Codes (??)

64
5.2 Questionnaire Construction

• 1. Questions
• Blank-filling questions (?????)
• Example How old are you? ______
• Multi-choice questions (???????)
• Example Married status
• 1)never married 2)married 3)divorced
• 4)married again after divorce

65
Matrix questions (?????)

• Example
• How satisfied are you with the following life
  domains?
• 
  1 2 3 4
• Relationships with your colleagues
• Relationships with your supervisors
• Labor type and intensity of your job
• Prestige of your job
• The numbers on the columns indicate the
  following
• 1. Very satisfied 2. Satisfied 3. Fairly
  satisfied
• 4. Somewhat unsatisfied 5. Very unsatisfied

66
Contingency Questions (????)

• A survey question that is asked only of some
  respondents, determined by their responses to
  some other question.
• Example
• Are you married?
• 1)Yes. When did you get married? ____
• 2)No.

67
2. answers

• Principles
• Exhaustiveness
• Example What is your religious affiliation?
• 1) Christianity 2)Buddhism
• 3)Islamism
• Mutual exclusiveness
• Example What is your occupation?
• 1) Cadre 2)worker 3)driver 4)doctor
• Levels of measurement

68
3. Guidelines for asking questions

• 1.Make items clear and shorter (???????????)
• 2.avoid double-barreled questions (??????????)
• 3.avoid biased items and term(???????)
• avoid giving hints for respondents
• 4.respondents must be competent to
  answers(????????????)
• avoid asking questions beyond respondents
  knowledge 5.avoid negative items
• 5. Order questions and limit question number
• Begin the questionnaire with the most interesting
  and easy set of questions

69
5.3 Scale Construction

• 1. Likert Scale (??????????)
• A type of composite measure developed by Rensis
  Likert in an attempt to improve the levels of
  measurement in social research through the use of
  standardized response categories in survey
  questionnaires. Likert-items are those utilizing
  such response categories as strongly agree,
  agree, disagree, and strongly disagree.

70
Procedures of Likert Scale Design

• 1.list all questions
• 2.stipulate how responses are scored
• For example, assign a score of 5 to strongly
  agree for positive items and to strongly
  disagree for negative items.
• 3.pretest
• 4.evaluate questions and delete questions with
  low distinguishability

71
2. Guttman Scale

• Characteristics
• First, only two options for each item.
• Second, each item with different degree of
  strength
• Procedures
• List all related questions
• Pretest and assign scores
• Evaluate questions
• Rearrange questions

72

• 1. ?????????????,???????????
• ?
  ?? ???
• 2. ??????????????????????????????????????
  ? ?? ???
• 3.????????????????,????????????????
  ? ?? ???
• 4.??????????????????,?????????????????????
  ? ?? ???
• 5.????????????? ? ?? ???
• 6.????????????,???????????????
• ? ??
  ???
• 7.?????????????????????????????
• ? ??
  ???
• 8.???????????????????????
• ? ??
  ???
• 9.??????????????? ? ?? ???

73
5.4 strengths and weaknesses of questionnaire
method

• 1. Strengths (??????)
• Generalizability
• Anonymity
• Suitable for quantitative analysis
• 2. Weaknesses (??????)
• Low return rate
• Educated respondents
• Difficult to monitor

74
Chapter 6 Interview

• 6.1 types of interview
• 6.2 procedures and techniques for interview
• 6.3 selection and training of interviewers

75
6.1 types of interview

• Interview a data collection method in which one
  person (an interviewer) asks questions of another
  ( a respondent).
• 1.Structured interview (?????)
• Interview with questionnaire or structural
  questions.
• --big sample (in contrast with non-structural
  interview) ???
• --superficial items ?????
• --high reliability (in contrast with
  self-administered questionnaire ) ????
• --suitable for illiterate respondents
  (??????????)

76
2. Unstructured interview (??????)

• An unstructured interview is an interaction
  between an interviewer and a respondent in which
  the interviewer has a general plan of inquiry but
  not a specific set of questions that must be
  asked in particular words and particular order.
• --without specific set of questions
• --More flexible The answers evoked by your
  initial questions should shape your subsequent
  ones.
• --greater depth

77
3. Colloquia (???)

• Characteristics
• Appropriate for understanding event, not facts
  about individuals
• Low generalizability
• Participants should be competent to your topic
• Number of participants for a colloquium
• Interviewer should be good at presiding over the
  colloquium

78
6.2 procedures and techniques

• 1. Entry stage
• To begin interview official certificates and
  informal social ties
• To reduce tension of respondents create an easy
  and trust atmosphere
• Solicit cooperation from respondents
• 2. Interviewing stage
• Focus on the topic (??????)
• Value-free (????)
• Expression (????)
• 3. Accomplish stage
• How to record interview informationRecord on the
  spot (????) record afterward(????)
• Leave the field and return

79
6.3 selection and training of interviewers

• 1. Selecting interviewers
• Special qualifications
• Sex Age Education Localities
• General qualifications
• Sincerity and staidness (????)
• Interests and ability (?????)
• Diligence (??)

80
2. Training of interviewers

• Introduction by organizer
• Research methods
• The project goals, sample, and etc.
• Read questionnaire
• Pilot interview

81
Chapter 7 Observation

• 1. Definition and categories
• 2. Participant observation and structured
  observation
• 3. Improving observation

82
7.1 definition and categories(1)

• 1. Definition
• Observation(???), also called field
  research(????), is a social research method that
  involves the direct observation of social
  phenomena in their natural settings (get data by
  sensory organs, e.g. eyes, ears).

83
7.1 definition and categories(2)

• Characteristics
• 1. with research plan and purposes
• 2. get behavioral data (non-oral information)
• 3. With the help of scientific facilities
• 4. Observe what is happening here and now

84
7.1 definition and categories(3)

• 2. Categories
• Participant observation v.s. non-participant
  observation (??????????)
• Structured observation v.s. non-structured
  observation (????????????)
• Direct observation v.s. indirect observation
  (?????????)
• Indirect observation
• Abrased objects (???)
• Accumulated objects (???)

85
7.2 participant observation and structured
observation(1)

• 1. Participant observation
• Enter field (????)
• cultivate relations with objects(????)
• Prepare observation plan(??????)
• Observe and record (?????)
• Leave field (????)

86
7.2 participant observation and structured
observation(2)

• 2. Structured observation
• Plan observation objects and dimensions(?????????)
  
• Operationalization of observation items(????????)
• Go to field and observe (?????????)
• analyze data quantitatively (??????????????)

87
3. Improving reliability and validity of
observation

• Factors influencing reliability and validity of
  observation
• Hawthorne effect
• Observers knowledge, interests, experiences and
  values
• Complexity of social phenomena
• Limits of observation method by chance
• Improvements
• Improve observation ability
• Better organization
• Take full advantages of modern facilities

88
Chapter 8 Literature Method

• 1. Literature and literature method
• 2. Content analysis
• 3. Advantages and disadvantages of
  literature method

89
8.1 literature and literature method (1)

• 1. Literature
• The body of written work produced by scholars or
  researchers in a given field.
• Three elements of literature
• data
• Media The material on which data and
  instructions are recorded, e.g., magnetic disk,
  paper tape, floppy disk, magnetic tape, punch
  card, etc.
• symbols

90
8.1 literature and literature method (2)

• Categories (1)
• Written literature
• Journals, newspapers,published booksarchivesdiar
  ies,letters,notebooks
• image literature
• Film copies, pictures, photos, video tapes,VCDs
• audio literature
• Music discs, audiotapes

91
8.1 literature and literature method (3)

• Categories (2)
• Formal documents and archives of governmental
  organs
• Documents and archives of associations
• Personal literature
• Letters,diaries,memoirs (???) and
  autobiographies.
• Categories (3)
• First hand literature and second hand literature

92
8.1 literature and literature method (4)

• 2. Literature methods
• Case literature study v.s. Content analysis
• Different types of literature personal
  literature v.s. published literature
• Different sample sizes
• Different analysis methods

93
8.2 content analysis

• Quantitative analysis of literature
• Procedures
• 1)Sampling (??)
• 2)delimitate categories (??????)
• 3)choose record units (??????)
• Words,themes,characters,sentences and paragraphs
• 4) define counting systems (??????)
• Binary code frequencies spaces intensity of
  statements
• (???? ?? ?? ????)

94
Example of content analysis

• TrendPersonal orientation---?social orientation
• Personal or group acceptance
• Indicator 1 ????
• Indicator 2 ????
• Indicator 3 ???????
• Human relation
• Indicator 4 ????
• Indicator 5 ????
• Indicator 6 ????

95
8.3 advantages and disadvantages of literature
method

• Advantages
• Without limits of time and space
• No impact of researcher on the subject of study
  (Hawthorne effect)
• Low expenditures
• Disadvantages
• With bias of literature authors
• Inaccessible (especially for personal literature)
• Sampling error

96
Chapter 9 Data Entry and Reduction

• 9.1 data checking and entry
• 1. Data checking ????
• Integrality
• Consistency
• Reliability calculation, spot-check
• 2. Data coding ????
• 3. Data entry ????

97
9.2 data reduction (1)

• 1. Frequency distribution ????
• Frequency ????? (f)
• Cumulative frequency ???? (cf)
• Upward cumulative frequency ??????
• Downward cumulative frequency ??????

98
???????

99
9.2 data reduction (2)

• 2. Grouping data ????
• Interval ??
• Lower limit ??
• Upper limit ??
• Midpoint ???

100
9.2 data reduction (3)

• 3. Plotting data
• Bar ???
• Line ??
• Pie ??
• Histogram ???

101
Bar ??? (discrete variable ????)
102
Pie ??????
103
Line ??
104
Histogram???(continuous variable ????)
105
Chapter 10 statistical analysis

• 10.1 descriptive statistics ????
• Univariate descriptive statistics???????
• Bivariate descriptive statistics ???????
• 10.2 inferential statistics ????

106

• Signs for mathematical operation
• Plus ?
• Summation ??
• Minus ?
• Multiply ? product ?
• Divide? dividend ??? divisor?? quotient?
• Radical sign ??
• Evolution or extraction ?? square??
• Denominator ? ??
• Numerator ??
• Formula ?? equation ??

107
10.1 descriptive statistics

• 1. Univariate analysis ???????
• Measures of Central tendency ????
• The phrase of measures of central tendency refers
  to the set of measures that deals with where on
  the scale the distribution is centered. The three
  major measures of central tendency are the mode,
  median, and mean.

108
The mode ??

• The mode (Mo) is simply the most common scorethe
  score obtained from the largest number of
  subjects. Thus, the mode is the value of X that
  corresponds to the highest point on the
  distribution.

109
The Median ???

• The median (Mdn) is the point that corresponds to
  the score that lies in the middle of the
  distribution when the data are arranged in
  increasing or decreasing numerical orderin other
  words, it is the point that divides the
  distribution in half.

110
Median example

• Example
• for the umbers 3, 5, 7, 8, 15
• 7 is the median
• For an even number of scores
• 3, 5, 7, 8, 14, 15
• The middle of the distribution is halfway between
  7 and 8. So the median is 7.5.
• Median location(N1)/2

111
The Mean ???

• The mean, the most common measure of central
  tendency, is the total of the scores divided by
  the number of scores. The sample mean is usually
  designated as X (read X Bar)
• XSX/N

112
????

• For grouped data
• XSfX/N

113
Measure of variability ????

• Variability or dispersion
• Two distributions may have the same mean but
  different degrees of dispersion of scores around
  those means. In one distribution, the average may
  reflect the general location of most of the
  scores. In the other distribution, the scores may
  be distributed over a wide range of values, and
  the average may be some sort of bad compromise.
• Group A 68, 69, 70, 71, 72 X170
• Group B 15, 60, 80, 95, 100 X270

114

• Range ??
• The range is a measure of distancenamely, the
  distance from the lowest to the highest score.
  For group A, the range is ( 72-68)4, for group B
  is (100-15)85.

115

• The variance or standard deviation
• ??????
• Sample variance (S2) ????
• Population variance (?2) ????
• S(Xi X) 2
• s
• n
• The standard deviation (s) is the positive square
  root of the variance.
• For group A,
• (68-70) 2 (69-70) 2(70-70) 2(71-70) 2
  (72-70) 2
• S 5
• 1.41

116

• The coefficient of variation ????
• the standard deviation divided by the mean
• CV s/X
• For group A, CV1.41/702.1
• For group B, CV30.8/7044

117

• 2. Bivariate descriptive statistics
• Measures of association ????
• Scatter diagram ???

118

• Relationships
• -strong relationship
• -perfect relationship
• -no relationship
• -negative relationship
• Examples
• -weight and height of respondents
• -schooling years of respondents and their
  fathers

119

• The pearson product-moment correlation
  coefficient
• NSXY-(SX)(SY)
• r
• N SX2-(SX)2N SY2-(SY)2

120

• ??????????

121

• 121334-146102
• r
• (121902-1462) (12 990 -102 2 )
• 0.75

122

• --regression analysis ????
• linear regression
• YbXa
• Ythe predicted value
• bthe slope of the regression line
• athe intercept
• n S XY- S XSY
• b
• n SX2-(SX) 2
• aY-bX

123

• Example
• Education and income
• 12 1334 - 146 102
• b 0.74
• 12 1902 - 1462
• a 146 12 - 0.74 102 12 5.87
• Y5.87 0.74X

124

• 10.2 Inferential Statistics
• Interval estimate
• when we have one specific estimate of a
  parameter, we call this a point estimates (???).
  There are also interval estimates (????), which
  are attempts to set limits that have a high
  probability of encompassing the true (population)
  value of the mean.
• 1)level of significance ?????
• 2)standard error ????

125

• Level of significance ?????
• In the context of tests of statistical
  significance, the degree of likelihood that an
  observed, empirical relationship could be
  attributable to sampling error. Three levels of
  significance are frequently used in research
  reports .05, .01, and .001. These mean,
  respectively, that the chances of obtaining the
  measured association as a result of sampling
  error are 5/100, 1/100, 1/1000.
• confidence level ???

126

• Standard error ???
• standard deviation of sample means.
• s S S
• SEX
• n n1 n

127

• Interval estimate for mean ????????
• S
• x Z(1-a)
• n
• ?????400?????,??????????645?,????120????????0.95
  ,????????????????
• 645 1.96 120 / 400
• 645 1.96 3
• 650.88 - 639.12

128

• Interval estimate of percentage????????
• p(1 - p)
• p Z(1-a)
• n
• ??????80?????, 65??????.???????????,????95 .
  
• 0.65 1.96 0.65 (1-0.65)/80
• 0.65 1.96 0.053
• 55 - 75

129
Chapter 10 statistical analysis

• 10.1 descriptive statistics ????
• Univariate descriptive statistics???????
• Bivariate descriptive statistics ???????
• 10.2 inferential statistics ????

130

• Signs for mathematical operation
• Plus ?
• Summation ??
• Minus ?
• Multiply ? product ?
• Divide? dividend ??? divisor?? quotient?
• Radical sign ??
• Evolution or extraction ?? square??
• Denominator ? ??
• Numerator ??
• Formula ?? equation ??

131
10.1 descriptive statistics

• 1. Univariate analysis ???????
• Measures of Central tendency ????
• The phrase of measures of central tendency refers
  to the set of measures that deals with where on
  the scale the distribution is centered. The three
  major measures of central tendency are the mode,
  median, and mean.

132
The mode ??

• The mode (Mo) is simply the most common scorethe
  score obtained from the largest number of
  subjects. Thus, the mode is the value of X that
  corresponds to the highest point on the
  distribution.

133
The Median ???

• The median (Mdn) is the point that corresponds to
  the score that lies in the middle of the
  distribution when the data are arranged in
  increasing or decreasing numerical orderin other
  words, it is the point that divides the
  distribution in half.

134
Median example

• Example
• for the umbers 3, 5, 7, 8, 15
• 7 is the median
• For an even number of scores
• 3, 5, 7, 8, 14, 15
• The middle of the distribution is halfway between
  7 and 8. So the median is 7.5.
• Median location(N1)/2

135
The Mean ???

• The mean, the most common measure of central
  tendency, is the total of the scores divided by
  the number of scores. The sample mean is usually
  designated as X (read X Bar)
• XSX/N

136
????

• For grouped data
• XSfX/N

137
Measure of variability ????

• Variability or dispersion
• Two distributions may have the same mean but
  different degrees of dispersion of scores around
  those means. In one distribution, the average may
  reflect the general location of most of the
  scores. In the other distribution, the scores may
  be distributed over a wide range of values, and
  the average may be some sort of bad compromise.
• Group A 68, 69, 70, 71, 72 X170
• Group B 15, 60, 80, 95, 100 X270

138

• Range ??
• The range is a measure of distancenamely, the
  distance from the lowest to the highest score.
  For group A, the range is ( 72-68)4, for group B
  is (100-15)85.

139

• The variance or standard deviation
• ??????
• Sample variance (S2) ????
• Population variance (?2) ????
• S(Xi X) 2
• s
• n
• The standard deviation (s) is the positive square
  root of the variance.
• For group A,
• (68-70) 2 (69-70) 2(70-70) 2(71-70) 2
  (72-70) 2
• S 5
• 1.41

140

• The coefficient of variation ????
• the standard deviation divided by the mean
• CV s/X
• For group A, CV1.41/702.1
• For group B, CV30.8/7044

141

• 2. Bivariate descriptive statistics
• Measures of association ????
• Scatter diagram ???

142

• Relationships
• -strong relationship
• -perfect relationship
• -no relationship
• -negative relationship
• Examples
• -weight and height of respondents
• -schooling years of respondents and their
  fathers

143

• The pearson product-moment correlation
  coefficient
• NSXY-(SX)(SY)
• r
• N SX2-(SX)2N SY2-(SY)2

144

• ??????????

145

• 121334-146102
• r
• (121902-1462) (12 990 -102 2 )
• 0.75

146

• --regression analysis ????
• linear regression
• YbXa
• Ythe predicted value
• bthe slope of the regression line
• athe intercept
• n S XY- S XSY
• b
• n SX2-(SX) 2
• aY-bX

147

• Example
• Education and income
• 12 1334 - 146 102
• b 0.74
• 12 1902 - 1462
• a 146 12 - 0.74 102 12 5.87
• Y5.87 0.74X

148

• 10.2 Inferential Statistics
• Interval estimate
• when we have one specific estimate of a
  parameter, we call this a point estimates (???).
  There are also interval estimates (????), which
  are attempts to set limits that have a high
  probability of encompassing the true (population)
  value of the mean.
• 1)level of significance ?????
• 2)standard error ????

149

• Level of significance ?????
• In the context of tests of statistical
  significance, the degree of likelihood that an
  observed, empirical relationship could be
  attributable to sampling error. Three levels of
  significance are frequently used in research
  reports .05, .01, and .001. These mean,
  respectively, that the chances of obtaining the
  measured association as a result of sampling
  error are 5/100, 1/100, 1/1000.
• confidence level ???

150

• Standard error ???
• standard deviation of sample means.
• s S S
• SEX
• n n1 n

151

• Interval estimate for mean ????????
• S
• x Z(1-a)
• n
• ?????400?????,??????????645?,????120????????0.95
  ,????????????????
• 645 1.96 120 / 400
• 645 1.96 3
• 650.88 - 639.12

152

• Interval estimate of percentage????????
• p(1 - p)
• p Z(1-a)
• n
• ??????80?????, 65??????.???????????,????95 .
  
• 0.65 1.96 0.65 (1-0.65)/80