Sampling Chapter 6 * Introduction Sampling is the process of selecting observations Often not possible to collect information from all units you wish to study Often not necessary to collect data from everyone out there Allows researcher to make a small subset of observations and then generalize to the rest of the population The Logic of Probability Sampling Samples: a group of subjects selected from a population Probability sampling: a method of selection in which each member of a population has a known chance of being selected Enables us to generalize findings from observing cases to a larger unobserved population Because we are not completely homogeneous, our sample must be representative of the variations that exist among us Conscious and Unconscious Sampling Bias Be conscious of bias – when sample is not fully representative of the larger population from which it was selected Sampling bias is not always obvious Use techniques to help avoid bias Representativeness and Probability of SelectionA sample is representative of the population from which it is selected if the aggregate characteristics of the sample closely approximate the same aggregate characteristics in the populationSamples that are representative of the population are often labeled equal probability of section method (EPSEM) samples because all members of the population have an equal chance of being included in the sample Sampling Terminology 1 Sample Element: who or what are we studying (student) Population: whole group (college freshmen) Population Parameter: summary description of a given variable in a population Sample Statistic: summary description of a given variable in a sample; we use sample statistics to make estimates or inferences of population parameters Sampling Terminology 2Sampling distribution: a range of sample statistics we obtain if we select many samples from a populationSampling frame: actual list of units to be selected (our school’s enrollment list)Binomial variable: a variable with only two values Sampling Terminology 3 Standard error: a measure of sampling error; we can estimate the degree to be expected Confidence Levels and Confidence Intervals Two key components of sampling error We express the accuracy of our sample statistics in terms of a level of confidence that the statistics fall within a specified interval from the parameter Sampling Designs 1 Simple Random Sampling: each element in a sampling frame is assigned a number, choices are then made through random number generation as to which elements will be included in your sample Systematic Sampling: elements in the total list are chosen (systematically) for inclusion in the sample List of 10,000 elements, we want a sample of 1,000, select every tenth element Choose first element randomly Sampling Designs 2 Stratification: modification to random and systematic sampling; ensures that appropriate numbers are drawn from homogeneous subsets of that population Dis.