sampling design, measurement & scaling technique

Question 1

Steps in sampling design (7)

Answer 1

1) know type of universe
2) choose sampling unit
3) make a source list
4) sample size
5) parameter of interest
6) budgetary constraint
7) sampling procedure

Question 2

1) know type of universe

Answer 2

• clearly define the set of objects, Universe, to be studied
• finite / infinite
• finite universe, number of items is certain 肯定
  eg: population of city
• infinite universe, is infinite (cannot have any idea about the total number of item)
  eg: numbers of stars in the sky

Question 3

2) choose sampling unit

Answer 3

-geographical unit
eg: state
-construction unit
eg: house
-social unit
eg: school

Question 4

3) make a source list (sampling frame)

Answer 4

• sample to be drawn
• contain the names of all items of a universe (finite universe only)

Question 5

4) sample size

Answer 5

• number of items to be selected from the universe
• not excessively large, not too small
  (optimum - fulfills the requirements of efficiency, representativeness, reliability & flexibility)

Question 6

5) parameter of interest

Answer 6

• consider specific population parameters which are interest
• may be interest in estimate proportion of person with some characteristics in the population / average or other measure of the population
  -maybe important sub-groups in the population

Question 7

6) budgetary constraint

Answer 7

• from practical point of view, major impact upon the decision relate size & type of sample
• this fact may lead to use of non-probability sample

Question 8

7) sampling procedure

Answer 8

• finally, decide the type of sample, technique to be used in select for the sample
• must select the design which, for given sample size, cost, has a smaller sampling error

Question 9

criteria of select a sampling procedure

Answer 9

1) cost of collect data
2) cost of two incorrect inference result from data

Two causes of incorrect inference
a) systematic bias
- error in sampling procedure
- cannot reduce / eliminate by increase the sample size

[ these errors can be detected & corrected ]

Question 10

factors result of systematic bias (5)

Answer 10

1) inappropriate sampling frame
2) defective 缺陷 measuring
3) non-respondents
4) indeterminacy principle
5) natural bias in the reporting of data

Question 11

1) inappropriate sampling frame

Answer 11

eg: a biased representation of the universe

Question 12

2) defective measuring

Answer 12

• if measuring device is constantly in error
• if physical measuring device is defective, has systematic bias in data collected
  ( calibration of device / equipment to minimized the systematic bias)
• In survey work, result if the questionnaire / interviewer is biased

Question 13

3) non-respondents

Answer 13

• unable to get the proper / enough response

occur if
- refuse to answer due to embarrass info
- forgot return survey form
- survey didn’t reach all member in the sample
- invalidate无效 result
- result in higher variance for estimate, as sample size is smaller than expect

Question 14

4) indeterminacy principle

Answer 14

• individual act differently when observe

Question 15

5) natural bias in the reporting of data

Answer 15

eg:
1) understate the income if ask for the tax purpose, but overstate if ask for social status
2) in psychological survey, people give ‘correct’ answer rather than their true feeling

Question 16

characteristics of a good sample design (5)

Answer 16

1) sample design must result in a truly representative sample
2) must result in a small sampling error
3) must viable in context of funds 资金范围内 available for the research study
4) systematic bias can be control in a better way
5) result of sample study can be applied with a reasonable level of confidence

Question 17

different types of sample designs

Answer 17

1) probability sampling
- simple random
-complex random
eg: systematic sampling, stratified sampling

2) non-probability sampling
- convenience sampling
- purposive sampling
eg: quota sampling, judgment sampling

Question 18

measurement scales (4)

Answer 18

1) nominal scale
2) ordinal scale
3) interval scale
4) ratio scale

Question 19

1) nominal scale (qualitative)

Answer 19

• label / naming the variable
  eg: gender - male, female
• mutually exclusive (no overlap)

Question 20

2) ordinal scale (qualitative)

Answer 20

• not really know the differences between each one
  eg: satisfaction, happiness
  1,2,3,4,5

Question 21

3) interval scale (quantitative)

Answer 21

• know the exact difference between the values
• do not has a ‘true zero’
  eg: 0 celsius ( no such thing as no temperature)

Question 22

4) ratio scale (quantitative)

Answer 22

• have an absolute zero
  eg: height, weight, duration

Question 23

sources of error in measurement (4)

Answer 23

1) respondent
2) situation
3) measurer
4) instrument

Question 24

Techniques of develop measurement tools (4)

Answer 24

1) concept development
- researcher should understand the major concepts of the study

2) specification of concept dimensions
3) selection of indicators
4) formation of index

Question 25

scale classification bases (5)

Answer 25

1) subject orientation
2) response form
3) degree of subjectivity
4) scale properties
5) number of dimensions

Question 26

important scaling technique

Answer 26

1) rating 评分 scale
-graphic & itemized rating scale

2) ranking 排行 scale
-method of paired comparison