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Sampling (Sampling is defined as the statistical process of selecting a…

- - - - The sampling process comprises of several stage. The first stage is defining the target population. The second step in the sampling process is to choose a sampling frame. This is an accessible section of the target population (usually a list with contact information) from where a sample can be drawn.
        
        Sampling frames may not entirely be representative of the population at large, and if so, inferences derived by such a sample may not be generalizable to the population
- - - - The sampling frame is ordered according to some criteria and elements are selected at regular intervals through that ordered list. This is referred to as systemic sampling.
        
        In stratified sampling, the sampling frame is divided into homogeneous and non-overlapping subgroups and a simple random sample is drawn within each subgroup.
        
        Cluster sampling divides the population into “clusters”, randomly sample a few clusters, and measure all units within that cluster.
        
        Match paired sampling compares two subgroups within one population based on a specific criterion.
        
        The probability sampling techniques described previously are all examples of single-stage sampling techniques is referred to as multi stage sampling.
        
        All probability sampling have two attributes in common: (1) every unit in the population has a known non-zero probability of being sampled, and (2) the sampling procedure involves random selection at some point.
- - - - In quota sampling technique, the population is segmented into mutually- exclusive subgroups, and then a non-random set of observations is chosen from each subgroup to meet a predefined quota.
        
        In expert sampling respondents are chosen in a non-random manner based on their expertise on the phenomenon being studied.
        
        In snowball sampling, you start by identifying a few respondents that match the criteria for inclusion in your study, and then ask them to recommend others they know who also meet your selection criteria
- - - - Sample statistics a “statistic” is a value that is estimated from observed data.
        
        Sample statistics may differ from population parameters if the sample is not perfectly representative of the population; the difference between the two is called sampling error.
        
        Just like a frequency distribution, the sampling distribution will also tend to have more sample statistics clustered around them, with fewer values scattered around the mean.
        
        Confidence interval is the estimated probability that a population parameter lies within a specific interval of sample statistic values.