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an extremely important part of research because without it, we cannot answer research questions, we cannot test hypothesis, and we cannot draw conclusions/recommendations based on the study
data collection
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Key factors about data collection process
- 1. kind of data to be collected
- 2. method of data collection
- 3. scoring of data to enable analysis
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Reasons for drawing a sample
- 1. less time consuming than census
- 2. less costly to administer than census
- 3. less cumbersome and more practical than census
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2 types of sampling techniques
- 1. probability sampling (or random)
- 2. non-probability sampling (or non-random)
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refers to the selection of a sample from a population, when this selection is based on the principle of randomization, that is, random selection or chance
Probability Sampling
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-Every individual or item from the frame has an equal chance of being selected.
-Selection may be with/without replacement.
-Samples obtained from table or random numbers or computer random number generators.
-Random samples are unbiased, and on average, representative of the population.
Simple Random Sampling
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the random sampling method that requires selecting samples based on a system of intervals in a numbered population
Systematic Random Sampling
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Benefits of systematic sampling
- -provides some control over the process
- -low risk
- -resistant to bias
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a probability sampling technique in which the total population is divided into homogenous groups (strata) to complete the sampling process
Stratified Random Sampling (aka proportional random sampling and quota random sampling)
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How do you do stratified random sampling?
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advantage of stratified random sampling
gives a systematic way of gaining a populations ample that takes into account the demographic make-up of the population
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disadvantage of stratified random sampling
Researchers may hold prior knowledge of the population's shared characteristics beforehand, which increases the risk for selection bias when strata are defined.
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a sampling method where the researcher divides the entire population into separate groups or clusters, then a random sample of these clusters is selected
Cluster Sampling
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a type of cluster sampling where each unit of the chosen clusters is sampled
single-stage cluster sampling
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In this type of cluster sampling, researchers will only collect data from a random subsample of individual units within each of the selected clusters to use as the sample.
double-stage cluster sampling
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In this type of cluster sampling, researchers will continue to randomly sample elements from within the clusters until they reach a manageable sample size.
Multi-stage cluster sampling
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___________ has no pattern whatsoever in acquiring respondents - they may be recruited merely by asking people who are present in the street, in a public building, or in a workplace, for example.
Convenience sampling
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In this method, respondents are chosen based on the judgement or opinion of the researcher upon the advice of certain experts.
Purposive/Judgement Sampling
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_________ is like stratified sampling but without randomization.
Quota Sampling
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In ____________, a few initial samples are taken by SRS and then expanded through referrals.
snowball sampling (also called network sampling)
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Enumerate the probability sampling methods.
- 1. Simple Random Sampling
- 2. Cluster Sampling
- 3. Systematic Sampling
- 4. Stratified Random Sampling
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Enumerate the non-probability sampling methods.
- 1. Convenience Sampling
- 2. Judgemental or Purposive Sampling
- 3. Snowball Sampling
- 4. Quota Sampling
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