Chapter 7

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# Chapter 7 - PowerPoint PPT Presentation

Chapter 7. The Logic Of Sampling. Chapter Outline. Introduction A Brief History of Sampling Nonprobability Sampling The Theory and Logic of Probability Sampling. Chapter Outline. Populations and Sampling Frames Types of Sampling Designs Multistage Cluster Sampling

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### Chapter 7

The Logic Of Sampling

Chapter Outline
• Introduction
• A Brief History of Sampling
• Nonprobability Sampling
• The Theory and Logic of Probability Sampling
Chapter Outline
• Populations and Sampling Frames
• Types of Sampling Designs
• Multistage Cluster Sampling
• Probability Sampling in Review
Political Polls and Survey Sampling
• In the 2004 Presidential election, pollsters generally agreed that the election was “too close to call”.
• To gather this information, they interviewed fewer than 2,000 people.
Question
• One of the most visible uses of survey sampling lies in _____________.
• political polling
• probability sampling
• core sampling
• One of the most visible uses of survey sampling lies in political polling.
Observation and Sampling
• Polls and other forms of social research rest on observations.
• The task of researchers is to select the key aspects to observe (sample).
• Generalizing from a sample to a larger population is called probability sampling and involves random selection.
Nonprobability Sampling
• Technique in which samples are selected in a way that is not suggested by probability theory.
• Examples include reliance on available subjects as well as purposive (judgmental), quota, and snowball sampling.
Types of Nonprobability Sampling
• Reliance on available subjects:
• Only justified if less risky sampling methods are not possible.
• Researchers must exercise caution in generalizing from their data when this method is used.
Types of Nonprobability Sampling
• Purposive or judgmental sampling
• Selecting a sample based on knowledge of a population, its elements, and the purpose of the study.
• Used when field researchers are interested in studying cases that don’t fit into regular patterns of attitudes and behaviors (非常態的態度與行為)
Types of Nonprobability Sampling
• Snowball sampling
• Appropriate when members of a population are difficult to locate.
• Researcher collects data on members of the target population she can locate, then asks them to help locate other members of that population.
Types of Nonprobability Sampling
• Quota sampling
• Begin with a matrix of the population.
• Data is collected from people with the characteristics of a given cell.
• Each group is assigned a weight appropriate to their portion of the population.
• Data should represent the total population.
Question
• ______________sampling occurs when units are selected on the basis of prespecified characteristics.
• snowball
• quota
• purposive
• probability
• Quota sampling occurs when units are selected on the basis of prespecified characteristics.
Informant
• Someone who is well versed in the social phenomenon that you wish to study and who is willing to tell you what he or she knows about it.
Probability Sampling
• Used when researchers want precise, statistical descriptions of large populations.研究結果要能以精確統計描述母體。
• A sample of individuals from a population must contain the same variations that exist in the population. 樣本的內在變異必須與母體相同。
Populations and Sampling Frames
• Findings based on a sample represent the aggregation of elements that compose the sampling frame. 研究發現代表抽樣架構的元素集合。
• Sampling frames do not always include all the elements their names imply. 遺漏的可能？
• All elements must have equal representation in the frame. 所有元素在架構內具相等的代表性。
A Population of 100 Folks
• Sampling aims to reflect the characteristics and dynamics of large populations.
• Let’s assume our total population only has 100 members.
Types of Sampling Designs
• Simple random sampling (SRS)
• Systematic sampling
• Stratified sampling
Representativeness
• Representativeness - Quality of a sample having the same distribution of characteristics as the population from which it was selected.諸特質在樣本中與母體具同樣分佈。
• EPSEM - Equal probability of selection method. A sample design in which each member of a population has the same chance of being selected into the sample.
Question
• ______________describes a sample whose aggregate characteristics closely approximate the aggregate characteristics of the population.
• exclusion
• probability sampling
• EPSEM
• representativeness
• none of these choices
• Representativeness describes a sample whose aggregate characteristics closely approximate the aggregate characteristics of the population.
Population
• The theoretically specified aggregation of study elements.
• Study population - Aggregation of elements from which the sample is actually selected.
• Element - Unit about which information is collected and that provides the basis of analysis.
Random selection
• Each element has an equal chance of selection independent of any other event in the selection process.
Sampling unit
• Element or set of elements considered for selection in some stage of sampling.
Parameter
• Summary description of a given variable in a population.
The Sampling Distribution of Samples of 1
• In this example, the mean amount of money these people have is \$4.50 (\$45/10).
• If we picked 10 different samples of 1 person each, our “estimates” of the mean would range all across the board.
Range of Possible Sample Study Results
• Shifting to a more realistic example, let’s assume that we want to sample student attitudes concerning a proposed conduct code. (如學生行為守則)
• Let’s assume 50% of the student body approves and 50% disapproves - though the researcher doesn’t know that.
Results Produced by Three Hypothetical Studies
• Assuming a large student body, let’s suppose we selected three different samples, each of substantial size.(例如，三個樣本數都是80位學生)
• We would not expect those samples to perfectly reflect attitudes in the whole student body, but they should come close.(平均值應該都相當接近)
Statistic
• Summary description of a variable in a sample.
• Parameter: Summary description of a given variable in a population.
Sampling Error
• The degree of error to be expected of a given sample design.
• 樣本統計偏離母群體母數的程度。
Confidence Level
• The estimated probability that a population parameter lies within a given confidence interval.
• Thus, we might be 95% confident(±1.96se) that between 35 and 45% of all voters favor Candidate A.
• Confidence interval - The range of values within which a population parameter is estimated to lie.
Sampling Frame
• That list or quasi list of units composing a population from which a sample is selected.
• If the sample is to be representative of the population, it is essential that the sampling frame include all (or nearly all) members of the population.
The Sampling Distribution
• If we were to select a large number of good samples, we would expect them to cluster around the true value (50%), but given enough such samples, a few would fall far from the mark.
Review of Populations and Sampling Frames: Guidelines
• Findings based on a sample represent only the aggregation of elements that compose the sampling frame.
• Sampling frames do not include all the elements their names might imply. Omissions are inevitable.
• To be generalized, all elements must have equal representation in the frame.
Question
• A _______________ is the list or quasi list of elements from which a probability sample is selected.
• confidence level
• confidence interval
• sampling frame
• systematic sample
• none of these choices
• A sampling frame is the list or quasi list of elements from which a probability sample is selected.
Simple Random Sampling
• Feasible only with the simplest sampling frame.
• Not the most accurate method available.
Systematic Sampling
• Slightly more accurate than simple random sampling.
• Arrangement of elements in the list can result in a biased sample.
Sampling ratio
• Proportion of elements in the population that are selected.
Stratification
• Grouping of units composing a population into homogenous groups before sampling.抽樣前，將研究母群依據某分層的標準區分成同質的組別，如依據性別、年級將母體先分成同性別與同年級的組別。 (母體愈同質，抽樣誤差愈小)
• This procedure, which may be used in conjunction with simple random, systematic, or cluster sampling, improves the representativeness of a sample, at least in terms of the stratification variables.
Stratified Sampling
• Rather than selecting sample for population at large, researcher draws from homogenous subsets of the population. 然後，依各同質的組別在母體中的比例，從中隨機抽出同比例的樣本。
• Results in a greater degree of representativeness by decreasing the probable sampling error.
Cluster Sampling
• A multistage sampling in which natural groups (如村、里) are sampled initially with the members of each selected group being subsampled afterward.
Multistage Cluster Sampling
• Used when it‘s not possible or practical to create a list of all the elements that compose the target population.沒有所有樣本個體的名冊，但可以取得次群體的名冊；抽取次群體之後，可以取得次群體中的個體樣本名冊。
• Involves repetition of two basic steps: listing and sampling.
• Highly efficient but less accurate.
Probability Proportionate to Size (PPS) Sampling
• Sophisticated form of cluster sampling.
• Used in many large scale survey sampling projects.
Weighting
• Giving some cases more weight than others.
Probability Sampling
• Most effective method for selection of study elements.
• Avoids researchers biases in element selection.
• Permits estimates of sampling error.

### Quick Quiz

1. Political polling rests on _____________.
• subtle innuendos
• field research
• observations
• none of these choices
• Political polling rests on observations.
2. _____________ sampling is often employed in field research whereby each person interviewed may be asked to suggest additional people for interviewing.
• snowball
• quota
• purposive
• probability
• Snowball sampling is often employed in field research whereby each person interviewed may be asked to suggest additional people for interviewing.
3. ______________ is the general term for samples selected in accord with probability theory.
• nonprobability analyses
• correlation coefficients
• probability sampling
• none of these choices
• Probability sampling is the general term for samples selected in accord with probability theory.
4. A____________ population is that aggregation of elements from which a sample is actually selected.
• theoretical
• small
• large
• concept
• study