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Question Bank for Chapter 2 mobile computing
SVM and kNN exemplify several important trade-offs in machine learning...
Course
Computer Science, Engineering (CSC502)
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Academic year: 2017/2018
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Unit II. Data Collection & Sampling Methods
- What is Data? Explain primary data & secondary data. List advantages and disadvantages of primary & secondary data.
- Explain Primary Data Collection Methods from the perspective of Quantitative and Quantitative approach.
- Explain following Quantitative methods of data collection Time series, Smoothing, Barometer, Econometric Methods [ Covered these types]
- Qualitative Methods: Survey, Polls, Interview, Delphi technique, Focus group, Questionnaire [ Covered these types]
- Methods of Collecting Secondary Sources of Data Published Printed Sources, Books, Journals/Periodicals, Magazines/Newspapers Published Electronic Sources, E-journals, General Websites, Weblogs, Diaries, Letters Government Records, Public Sector Records
- When sampling is preferred? What are characteristics/advantages of sampling?
- Explain Probability Sampling types in detail with examples, advantages and disadvantages
- Simple Random Sampling
- Systematic Sampling
- Stratified Random Sample
- Cluster Sampling
- Multistage Sampling [ Covered these types]
- Explain Non-Probability Sampling types in detail with examples, advantages and disadvantages 1. Convenience Sampling 2. Purposive/Judgement/Deliberate/Authoritative Sampling 3. Quota Sampling 4. Snowball Sampling [ Covered these types]
- Differentiate between probability and non-probability sampling Stratified Random Sample & Cluster Sampling Stratified Random Sample & Quota Sampling
- Explain subtypes of snowball sampling? Linear, Exponential Non Discriminative, Exponential Discriminative
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Question Bank for Chapter 2 mobile computing
Course: Computer Science, Engineering (CSC502)
41 Documents
Students shared 41 documents in this course
University: Datta Meghe Institute of Medical Sciences
Was this document helpful?
Unit II. Data Collection & Sampling Methods
1. What is Data? Explain primary data & secondary data. List advantages and disadvantages of
primary & secondary data.
2. Explain Primary Data Collection Methods from the perspective of Quantitative and
Quantitative approach.
3. Explain following Quantitative methods of data collection
Time series, Smoothing, Barometer, Econometric Methods [ Covered these types]
4. Qualitative Methods: Survey, Polls, Interview, Delphi technique, Focus group,
Questionnaire [ Covered these types]
5. Methods of Collecting Secondary Sources of Data
Published Printed Sources, Books, Journals/Periodicals, Magazines/Newspapers
Published Electronic Sources, E-journals, General Websites, Weblogs, Diaries, Letters
Government Records, Public Sector Records
6. When sampling is preferred? What are characteristics/advantages of sampling?
7. Explain Probability Sampling types in detail with examples, advantages and disadvantages
1) Simple Random Sampling
2) Systematic Sampling
3) Stratified Random Sample
4) Cluster Sampling
5) Multistage Sampling
[ Covered these types]
8. Explain Non-Probability Sampling types in detail with examples, advantages and
disadvantages
1. Convenience Sampling
2. Purposive/Judgement/Deliberate/Authoritative Sampling
3. Quota Sampling
4. Snowball Sampling
[ Covered these types]
8. Differentiate between
probability and non-probability sampling
Stratified Random Sample & Cluster Sampling
Stratified Random Sample & Quota Sampling
9. Explain subtypes of snowball sampling?
Linear, Exponential Non Discriminative, Exponential Discriminative
