3 Why use a sample? Cost Speed Sufficiently accurate (decreasing precision but maintaining accuracy)More accurate than a census (?)Destruction of test units
4 Stages in the Selection of a Sample Step 7: ConductFieldworkStep 2: SelectThe SamplingFrameStep 3: ProbabilityOR Non-probability?Step 1: Define thethe target populationStep 6: SelectSampling unitsStep 5: DetermineSample SizeStep 4: PlanSelection ofsamplingunits
5 Step 1: Target Population The specific, complete group relevant to the research projectWho really has the information/data you needHow do you define your target population
6 Bases for defining the population of interest include: GeographyDemographicsUseAwareness
7 Operational Definition A definition that gives meaning to a concept by specifying the activities necessary to measure it.“The population of interest is defined as all women in the City of Lethbridge who hold the most senior position in their organization.”What variables need further definition?
8 Step 2: Sampling FrameThe list of elements from which a sample may be drawn.Also known as: working population.Examples?
9 Sampling Frame Error:error that occurs when certain sample elements are not listed or available and are not represented in the sampling frame.
10 Sampling Units:A single element or group of elements subject to selection in the sample.Primary sampling unitSecondary sampling unit
11 Error: Less than perfectly. representative samples. Random sampling error.Difference between the result of a sample and the result of a census conducted using identical procedures; a statistical fluctuation that occurs because of chance variation in the selection of the sample.
12 …Error Systematic or non-sampling error. Results from some imperfect aspect of the research design that causes response error or from a mistake in the execution of the researchExamples: Sample bias, mistakes in recording responses, non-responses, mortality etc,.
13 …Error Non-response error. The statistical difference between a survey that includes only those who responded and a survey that also includes those that failed to respond.
14 Step 3: Choice! Probability Sample: A sampling technique in which every member of the population will have a known, nonzero probability of being selected
15 Step 3: Choice! Non-Probability Sample: Units of the sample are chosen on the basis of personal judgment or convenienceThere are no statistical techniques for measuring random sampling error in a non-probability sample. Therefore, generalizability is never statistically appropriate.
16 Classification of Sampling Methods ProbabilitySamplesNon-probabilitySystematicStratifiedConvenienceSnowballClusterSimpleRandomJudgmentQuota
17 Probability Sampling Methods Simple Random Samplingthe purest form of probability sampling.Assures each element in the population has an equal chance of being included in the sampleRandom number generatorsSample SizeProbability of Selection =Population Size
18 Advantages Disadvantages minimal knowledge of population needed External validity high; internal validity high; statistical estimation of errorEasy to analyze dataDisadvantagesHigh cost; low frequency of useRequires sampling frameDoes not use researchers’ expertiseLarger risk of random error than stratified
19 Systematic SamplingAn initial starting point is selected by a random process, and then every nth number on the list is selectedn=sampling intervalThe number of population elements between the units selected for the sampleError: periodicity- the original list has a systematic pattern?? Is the list of elements randomized??
20 Advantages Disadvantages Moderate cost; moderate usage External validity high; internal validity high; statistical estimation of errorSimple to draw sample; easy to verifyDisadvantagesPeriodic orderingRequires sampling frame
21 Stratified SamplingSub-samples are randomly drawn from samples within different strata that are more or less equal on some characteristicWhy?Can reduce random errorMore accurately reflect the population by more proportional representation
22 How?1.Identify variable(s) as an efficient basis for stratification. Must be known to be related to dependent variable. Usually a categorical variable2.Complete list of population elements must be obtained3.Use randomization to take a simple random sample from each stratum
23 Types of Stratified Samples Proportional Stratified Sample: The number of sampling units drawn from each stratum is in proportion to the relative population size of that stratumDisproportional Stratified Sample:The number of sampling units drawn from each stratum is allocated according to analytical considerations e.g. as variability increases sample size of stratum should increase
24 Types of Stratified Samples… Optimal allocation stratified sample: The number of sampling units drawn from each stratum is determined on the basis of both size and variation.Calculated statistically
25 Advantages Disadvantages Assures representation of all groups in sample population neededCharacteristics of each stratum can be estimated and comparisons madeReduces variability from systematicDisadvantagesRequires accurate information on proportions of each stratumStratified lists costly to prepare
26 Cluster SamplingThe primary sampling unit is not the individual element, but a large cluster of elements. Either the cluster is randomly selected or the elements within are randomly selectedWhy?Frequently used when no list of population available or because of costAsk: is the cluster as heterogeneous as the population? Can we assume it is representative?
27 Cluster Sampling example You are asked to create a sample of all Management students who are working in Lethbridge during the summer termThere is no such list availableUsing stratified sampling, compile a list of businesses in Lethbridge to identify clustersIndividual workers within these clusters are selected to take part in study
28 Types of Cluster Samples Area sample: Primary sampling unit is a geographical areaMultistage area sample:Involves a combination of two or more types of probability sampling techniques. Typically, progressively smaller geographical areas are randomly selected in a series of steps
29 Advantages Disadvantages Low cost/high frequency of use Requires list of all clusters, but only of individuals within chosen clustersCan estimate characteristics of both cluster and populationFor multistage, has strengths of used methodsDisadvantagesLarger error for comparable size than other probability methodsMultistage very expensive and validity depends on other methods used
30 Classification of Sampling Methods ProbabilitySamplesNon-probabilitySystematicStratifiedConvenienceSnowballClusterSimpleRandomJudgmentQuota
31 Non-Probability Sampling Methods Convenience SampleThe sampling procedure used to obtain those units or people most conveniently availableWhy: speed and costExternal validity?Internal validityIs it ever justified?
32 Advantages Disadvantages Very low cost Extensively used/understood No need for list of population elementsDisadvantagesVariability and bias cannot be measured or controlledProjecting data beyond sample not justified.
33 Judgment or Purposive Sample The sampling procedure in which an experienced research selects the sample based on some appropriate characteristic of sample members… to serve a purpose
34 Advantages Disadvantages Moderate cost Commonly used/understood Sample will meet a specific objectiveDisadvantagesBias!Projecting data beyond sample not justified.
35 Quota SampleThe sampling procedure that ensure that a certain characteristic of a population sample will be represented to the exact extent that the investigator desires
36 Advantages Disadvantages moderate cost Very extensively used/understoodNo need for list of population elementsIntroduces some elements of stratificationDisadvantagesVariability and bias cannot be measured or controlled (classification of subjects0Projecting data beyond sample not justified.
37 Snowball samplingThe sampling procedure in which the initial respondents are chosen by probability or non-probability methods, and then additional respondents are obtained by information provided by the initial respondents
38 Advantages Disadvantages low cost Useful in specific circumstances Useful for locating rare populationsDisadvantagesBias because sampling units not independentProjecting data beyond sample not justified.