Kinh tế lượngTrắc nghiệm

112 câu trắc nghiệm Kinh tế lượng – Phần 2

Tổng hợp 112 câu trắc nghiệm + tự luận môn Kinh tế lượng, nội dung phần Nghiên cứu Marketing (Marketing research) có đáp án và lời giải thích kèm theo (bằng tiếng anh). Nội dung bao gồm 8 chương như sau:

1. Introduction to marketing research
2. Exploratory research design
3. Conclusive research design
4. Sampling
5. Measurement and scaling
6. Questionnaire design
7. Data preparation and preliminary data analysis
8. Report preparation and presentation

Phần 1 gồm nội dung của 4 chương cuối.

5. Measurement and scaling

KTL_003_C5_1: Most people use measurement in their daily lives.
● True
○ False

KTL_003_C5_2: The idea of assigning numbers can be helpful in:
○ allowing statistical testing
○ facilitating easier communication
● Both a and b
○ None

KTL_003_C5_3: The appropriateness of the raw data being collected depends directly on the scaling technique used by the researcher.
● True
○ False

KTL_003_C5_4: Which of the following scale has assignment property?
○ Nominal
○ Ordinal
○ Interval
○ Ratio
● All of the above
○ None of the above

KTL_003_C5_5: The interval scale possesses all of the below properties, except:
○ Assignment
○ Order
○ Distance
● Origin
○ All of the above
○ None of the above

KTL_003_C5_6: The origin property refers to a numbering system where zero is the displayed or referenced starting point in the set of possible responses.
● True
○ False

KTL_003_C5_7: Which among the following is not comparative scaling technique?
○ Paired comparison
○ Rank order
○ Constant sum scale
○ Q-sort
● Stapel scale

KTL_003_C5_8: Which among the following is not a noncomparative scaling technique?
○ Likert
○ Stapel
○ Semantic differential
● Rank order
○ None of the above

KTL_003_C5_9: Respondent characteristics such as intelligence, education does not have any affect the test score.
○ True
● False

KTL_003_C5_10: Validity refers to scale consistency over a period of time.
○ True
● False

KTL_003_C5_11: Write a brief note on fundamental properties of measurement.

There are four primary fundamental properties of measurement: assignment, order, distance and origin. The assignment property is also referred as description or category property. It refers to the researcher’s employment of unique descriptors, or labels to identify each object within a set. The second measurement scale property, order property, refers to the relative magnitude between the descriptors. The distance property refers to a measurement scheme where exact difference between each of the descriptors is expressed in absolute. The origin property is a measurement scheme wherein exists a unique starting point in a set of scale points. For the most part, the origin property refers to a numbering system where zero is the displayed or referenced starting point in the set of possible responses. Each scaling property builds on the previous one. For example, a scale which includes order property will have assignment property built in. Similarly, a scale which possesses distance property will have assignment and order property both. An origin property based scale will have all assignment, origin and distance properties included in itself.

KTL_003_C5_12: Discuss construct validity and the types of construct validity.

Construct validity addresses the question of what construct or characteristic the scale is, in fact, measuring. When assessing construct validity, the researcher attempts to answer theoretical questions about why the scale works and what deductions can be made concerning the underlying theory. Thus, construct validity requires a sound theory of the nature of the construct being measured and how it relates to other constructs. Construct validity is the most sophisticated and difficult type of validity to establish. Construct validity includes convergent, discriminant, and nomological validity.

Convergent validity is the extent to which the scale correlates positively with other measures of the same construct. It is not necessary that all these measures be obtained by using conventional scaling techniques. Discriminant validity is the extent to which a measure does not correlate with other constructs from which it is supposed to differ.

It involves demonstrating a lack of correlation among differing constructs. Nomological validity is the extent to which the scale correlates in theoretically predicted ways with measures of different but related constructs. A theoretical model is formulated that leads to further deductions, tests, and inferences. Gradually, a nomological net is built in which several constructs are systematically interrelated.

KTL_003_C5_13: Write a brief note about comparative and non-comparative scaling.

The scaling techniques regularly employed in marketing research can be classified into two basic strands: (a) comparative scaling and (b) non-comparative scaling. As the name suggests comparative scaling involves direct comparison of stimulus objects with one another. For example, managers are generally interested in knowing consumer preference regarding their brand in comparison to a competitor’s brand. A researcher can then ask question such as what of the two brands consumer prefers and this would provide the manager a clear idea of what consumer preferences are. There are several techniques which are used in building comparative scale such as paired comparison, rank order, constant sum scale, and q-sort.

While comparative scaling is used for comparison between stimuli, on the other hand, non-comparative scaling involves each stimulus object being scaled independently of the other objects in the stimulus set. The resulting data in non-comparative scale are assumed to be interval or ratio scaled. For example, instead of direct comparison between brands researcher may ask the respondent to rate each brand separately on a scale of 1 – 10 and can evaluate each brand as well as compare the brands also. Noncomparative scaling techniques involve continuous rating scales as well as itemised rating scales. The itemised rating scales are further sub-divided into likert scale, semantic differential scale and stapel scale.

KTL_003_C5_14: What are the various measures for reliability assessment of a scale?

Reliability in research relates to consistency of results over a period of time. A scale is called reliable if it produces consistent results when repeated measurements are made. As the name suggests, in test-retest reliability measurement, same respondents are administered identical sets of scale items at two different times (usually 2 – 4 weeks). The degree of similarity between the measurements (measured through correlation between both measurements) determines the reliability. The higher the correlation between the two measurements, the higher the scale reliability. In measuring alternative forms reliability, two equivalent forms of the scale are constructed and then the same respondents are measured at two different times. Internal consistency reliability is used to assess the reliability of a summated scale where several items are summated to form a total score. In simple words, each item in the scale must measure part of what the scale is developed to measure. Various techniques such as ‘split-half reliability’ or ‘coefficient alpha’ (also known as Cronbach’s alpha) are used to measure internal consistency reliability. In split-half reliability the scale is broken in two halves and the resulting half scores are correlated. High correlation between the two halves shows higher internal consistency. In case of coefficient alpha the average of all possible split-half coefficients is calculated. The value beyond 0.7 suggests acceptable internal reliability.

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