L6 - Survey design and sampling

Question 1

Quantitative research method definition

Answer 1

Research techniques seeking for quantify data and typically applying some form of statistical analysis.

Question 2

Difference between quantitative and qualitative methods:

Answer 2

Quantitative methods are descriptive research methods that answer the questions of “what” is happening for a particular phenomenon.
Meanwhile, qualitative explanatory research answers the questions of “why” and “how”.

Question 3

Quantitative research methods include

Answer 3

Experiments, Questionnaires, and Surveys. (Technique: Observation, research, physical measurements, questionnaires, etc.)

Question 4

Questionnaire

Answer 4

Has fixed set of answers and is most commonly administered as part of surveys.

Question 5

7 steps before conducting survey

Answer 5

1) Develop question topics
2) Select question and response formats
3) Select wording
4) Determine sequence
5) Design layout and appearance
6) Pilot test
7) Undertake survey

Question 6

How to motivate answering when designing a questionnaire

Answer 6

Simple, easy to understand questions to motivate complete, honest and accurate answers.

Question 7

Misleading scale formats

Answer 7

Double-barrelled questions, leading questions, ambiguous questions, complex questions, double negative questions.

Question 8

Double-barrelled question

Answer 8

Include two or more different attributes or issues in the same question, but responses allow only a single issue.
(Two or more questions are combined into one)

Question 9

Leading question

Answer 9

Introduce bias and influence the way respondent answer a question.
» Clue to what respondents should answer.

Question 10

Loaded question

Answer 10

Suggest a socially desirable answer or involve an emotionally charged issue.

Question 11

Ambiguous question

Answer 11

A situation in which possible responses can be interpreted in many ways.
» Respondent find it difficult to remember very specific information of the question.

Question 12

Complex question

Answer 12

A situation in which question is worded that respondent isn’t sure how they are supposed to respond.
» Solution: Defining the issue through the 5 Ws (who, what, when, where, why)

Question 13

Double negative question

Answer 13

2 negatively signed statements that lead towards a positive direction.
» Contain two negative thoughts in the same question.

Question 14

Optimal number of response in rating scales

Answer 14

• Rating scale with few response categories yield the least reliable score and perform the worst.
• 10, 9, 7 are the most preferred.
• Different scales may be best suited to different purposes: 2, 3, 4 can be quick, easy to use and reduce demotivation.

Question 15

Two tasks in measurement process

Answer 15

(1) construct selection/development and (2) scale measurement.

Question 16

Construct definition (Hair et al., 2017)

Answer 16

A hypothetical variable made up of a set of component responses or behaviour that are thought to be related.
Ex of marketing construct: Customer satisfaction, Brand loyalty, Service quality, Advertising recall.

Question 17

Construct development definition (Hair et al., 2017)

Answer 17

Construct development: the process in which researchers identify characteristics that define concept being studied by the researcher.

Question 18

Scale measurement definition

Answer 18

The process of assigning a set of scale descriptors to represent the range of possible responses to a question about an object or construct.

Question 19

Evaluating the measurement scales based on two criteria:

Answer 19

Reliability: the extent to which the scale can reproduce the same or similar measurement results in repeated trials. It is a measure of consistency.
Validity: the extent to which the scale measures what is supposed to measure.

Question 20

Three basic scale levels:

Answer 20

Nominal, Ordinal and Interval/Ratio scale

Question 21

Nominal variable

Answer 21

Variables have no logical order or value.

> Equivalence

Question 22

Ordinal variable

Answer 22

Variables have a logical order to the value labels.

> Equivalence & Order

Question 23

Ratio variable

Answer 23

Actual value is measured directly.

> Equivalence, Order & Equal intervals.

Question 24

Criteria for scale development

Answer 24

1) Understanding of the questions: to consider the intellectual capacity and language ability of respondents
2) Discriminatory power of scale descriptors: the scale’s ability to differentiate between the scale responses. The more scale points, the greater discriminatory power, the greater the variability in the data.
3) Types: balanced / unbalanced scale; forced / non-forced choice scales; negatively worded statements; desired measures of central tendency and dispersion.
4) Adapting established scales.

Question 25

Types of scales to measure attitudes and behaviour

Answer 25

Likert scale, Semantic differential scale, and Behavioural intention scale

Question 26

Likert scale

Answer 26

Agree / disagree with a series of mental or behavioural belief statements about a given objects. It is often expanded to the format of 7-point scale. It is best used for self-administered surveys, personal interviews or online surveys.

Question 27

Semantic differential scale

Answer 27

Ask about the attitude regarding the bipolar adjectives. It is used to develop and compare profiles of different brands, or indicate how an ideal product would rate.

Question 28

Behavioural intention scale

Answer 28

Ask the likelihood that people will demonstrate some type of predictable behaviour intent toward purchasing an object in a future time frame.

Question 29

Comparative and non-comparative scales

Answer 29

1) Comparative rating scale: when the objective is to have a respondent express her attitudes, feelings, behaviour about an object or its attributes.
2) Non-comparative rating scale: (…) without making reference to other object or its attributes.

Question 30

Dichotomous scale

Answer 30

Scales that provide only 2 possible outcomes (ex: Yes/No)

Question 31

Open-ended questions

Answer 31

Allow respondents to provide a non-numerical answer and instead express themselves through words. It represents the qualitative element of surveys and qualitative analysis.

Question 32

Pilot study / test

Answer 32

A preliminary small scale study conducted before the main data collection stage.
It is done to test the first draft of the questionnaire in order to spot potential issues like long or difficult to understand questions, and spelling mistakes.

Question 33

Sampling

Answer 33

Selection of small number of elements from a larger defined target group to conclude about a larger group.
> It is often used when it is impossible or unreasonable to conduct a census (every member of target population).

Question 34

Role of sampling

Answer 34

• Less time-consuming and costly than conducting a census.

- Influence the type of research design, survey instrument and actual questionnaire.

Question 35

Factors underlying sampling theory

Answer 35

The central limit theorem (CLT) - the sampling distribution derived from a simple random sample will be approximately normally distributed.

Question 36

Tools used to assess the quality of samples

Answer 36

Sampling error and Non-sampling error

Question 37

Sampling error definition

Answer 37

any bias type that is attributable to mistakes in selection process for prospective sampling units or in determining the sample size. It can be reduced by increasing the sample size.

Question 38

Non-sampling error definition

Answer 38

Regardless of whether a sample or census is used, it occurs at any stage of the research process. For example, inappropriate question/scale measurements or poorly designed questionnaire.

Question 39

Differences between probability and non-probability sampling

Answer 39

1) Probability:
- Specific selection rules to ensure unbiased selection and proper sample representation of the population => Can judge the data reliability and validity.
- The observed difference can be partially attributed to the existence of sampling error. The results can be generalized to the target population with a specified margin of error.
2) Non-probability: Selection is based on intuitive judgement or researcher knowledge. Sample error is unknown.

Question 40

Probability sampling include 3 types:

Answer 40

Simple random sampling; Systematic random sampling; and Stratified random sampling

Question 41

Non-probability sampling include 4 types:

Answer 41

Convenience sampling; Judgment sampling; Quota sampling; and Snowball sampling

Question 42

Simple random sampling

Answer 42

A known and equal chance of being selected.

Question 43

Systematic random sampling

Answer 43

Known and equal chance of being selected, but the target population is ordered in some way, and selected systematically > Frequently used

Question 44

Stratified random sampling

Answer 44

Separate the target population into different homogenous groups (strata), then select samples from each stratum.

Question 45

Convenience sampling

Answer 45

Draw samples based on convenience (people who are the most available or most easily selected).

Question 46

Judgment sampling

Answer 46

Select samples based on an experienced individual’s belief that they will meet the requirements.

Question 47

Quota sampling

Answer 47

Select samples based on prespecified quotas regarding demographics, attitudes, behaviour, etc.

Question 48

Snowball sampling

Answer 48

Respondents are chosen and help researcher identify additional people to be included in the study.

Question 49

Factors to consider when determining sample size

Answer 49

• Probability sample sizes: variance, level of confidence, desired error.
• Non-probability sample sizes: specific characteristics of sample like age, income, education.
• Other sample size determination approaches

Question 50

Questionnaire can be failed due to:

Answer 50

• Incomplete with missing values
• Pattern of responses indicate participant did not understand or follow the instructions
• Received after pre-established cut-off date
• Answered by unqualified person.

Question 51

Verifying the questionnaire by several methods

Answer 51

• Discarding unsatisfactory participants
• Assigning missing values
• Returning to the field

Question 52

Pros and Cons of simple random sampling

Answer 52

• Pros: (1) Easily understood. (2) Can be generalized to the defined target population with a prespecified m.e. (3) Unbiased estimates of population’s characteristics.
• Cons: Difficulty in obtaining a complete and accurate listing of the target population elements.

Question 53

Pros and Cons of Systematic random sampling

Answer 53

• Pros: Less costly and easier than SRS due to availability of lists and shorter time to draw a sample.
• Cons: (1) of hidden patterns in the list that create bias. (2) The number of sampling units must be known

Question 54

Pros and Cons of Stratified random sampling

Answer 54

• Pros: (1) Assure the representativeness of the sample. (2) Study each stratum and compare between strata. (3) Estimate population with greater precision and less error.
• Cons: Difficult to determine the basis for stratifying (target population’s characteristics of interests), unavailable required information to select criteria as factors to stratify.

Question 55

Pros and Cons of Convenience random sampling

Answer 55

• Pros: Able to interview many respondents in a relatively short time. > Early stages of research
• Cons: (1) Unreliable constructs if used to study a broader target population (2) Ungeneralized data.

Question 56

Pros and Cons of Judgement sampling

Answer 56

• Pros: Correct judgment will generate better than convenience sampling.
• Cons: (1) Ungeneralized data. (2) Data should be interpreted cautiously.

Question 57

Pros and Cons of Quota sampling

Answer 57

• Pros: (1) Contain specific subgroups in the proportions desired by researchers. (2) Reduce selection bias by the field workers.
• Cons: (1) Ungeneralized data. (2) The success depends on subjective decisions made by researchers.

Question 58

Pros and Cons of Snowball sampling

Answer 58

• Pros: (1) Able to identify small, hard-to-reach, uniquely defined target populations. (2) Most useful in qualitative research.
• Cons: 1) Ungeneralized data. (2) Allow bias in the study

Question 59

Pros of Survey method

Answer 59

(1) Accommodate large sample sizes so results can be generalized
(2) Produce precise enough estimates to identify even small differences
(3) Easy to administer and record answers to structured questions
(4) Facilitate advanced statistical analysis
(5) Concepts and relationships not directly measurable can be studied

Question 60

Cons of Survey method

Answer 60

(1) Difficult to develop questions that accurately measure respondent attitudes and behavior.
(2) Difficult to obtain In-depth data.
(3) Low response rates can be a problem.

Question 61

Two methods of stratified random sampling

Answer 61

• Proportionately stratified sampling: the sample size from each stratum is dependent on that stratum’s size relative to the defined target population.
• Disproportionately stratified sampling: the sample size selected from each stratum is independent of that stratum’s proportion of the total defined target population.