Planning and Conducting
Surveys
• Characteristics of a well designed and well
conducted survey.
• Populations, samples and random
selection.
• Sources of ...
Populations, Samples, and Random Selection
The population in a statistical study is the entire group
of individuals, score...
Sources of Bias in Sampling and Surveys
Convenience Samples use a selection of individuals that are
easiest to reach, and ...
Sources of Bias in Sampling and Surveys (cont.)
Why would more accurate results be gathered in an
English or History class...
Design Your Own Bad Sample
The school administration wants to gather
student opinion about parking on campus. It is
not pr...
A sample chosen by chance allows neither favoritism by the
sampler nor self-selection by respondents. All individuals have...
Other sampling methods include Stratified Random Sampling,
and Cluster Sampling. Both involve the formation of subgroups
b...
Identify which type of sampling is used: random, systematic,
convenience, stratified, or cluster.
1. A policy sobriety che...
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Planning and conducting surveys

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Planning and conducting surveys

  1. 1. Planning and Conducting Surveys
  2. 2. • Characteristics of a well designed and well conducted survey. • Populations, samples and random selection. • Sources of bias in sampling and surveys. • Sampling methods, including simple random sampling, stratified random sampling and cluster sampling.
  3. 3. Populations, Samples, and Random Selection The population in a statistical study is the entire group of individuals, scores, measurements, etc. about which we want information. A sample is the part of the population from which we actually collect information and is used to draw conclusions about the whole. Random Selection is a process of gathering a representative sample for a particular study. Random means the people are chosen by chance, each person has the same probability of being chosen. When you have a truly random sample, you reduce the chance that the results are due to factors of the participants in the study.
  4. 4. Sources of Bias in Sampling and Surveys Convenience Samples use a selection of individuals that are easiest to reach, and Voluntary Response Samples where respondents decide if they want to be included, are common methods of data collection that will usually produce biased results. These sampling methods will usually favor one part of a population over another. If the High School guidance office wanted to know if students are interested in an AP Statistics elective, would the district get accurate information if the counselors asked the Calculus teachers to survey their students?
  5. 5. Sources of Bias in Sampling and Surveys (cont.) Why would more accurate results be gathered in an English or History class? Would asking students to stop by the office at the end of the day to fill out a questionnaire regarding testing policies in the district yield valid results? What could be changed to make this a more valid sample?
  6. 6. Design Your Own Bad Sample The school administration wants to gather student opinion about parking on campus. It is not practical to contact every student. 1.Give an example of a way to choose a sample of students that is poor practice because it depends on voluntary response. 2.Give an example of a way to choose a sample of students that is poor practice that does not depend on voluntary response.
  7. 7. A sample chosen by chance allows neither favoritism by the sampler nor self-selection by respondents. All individuals have an equal chance to be chosen. A Simple Random Sample allows all members of a population an equal chance of being selected, avoiding bias. Drawing names from a hat works for small populations (students in a classroom) but would not be practical when conducting a national survey. Computer-generated Random Digits can be used when working with large populations. A Table of Random Digits is a long string of the digits 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, where each entry in the table is equally likely to be any of the 10 digits and the entries are independent of each other. Systematic Sampling selects a starting point and then selects every kth (such as 50th) element in the population.
  8. 8. Other sampling methods include Stratified Random Sampling, and Cluster Sampling. Both involve the formation of subgroups before collecting data. Stratified Random Sampling subdivides the population into at least two different subgroups (strata) so that subjects within the same subgroup share the same characteristics (gender, age) then draw a sample from each. Ex. The Orange County DMV plans to test an on line registration system by using a sample consisting of 20 randomly selected men and 20 randomly selected women. Cluster Sampling divides the population into sections (clusters), randomly select some of those clusters, and then chooses all members of the selected clusters. Ex. Pre-election polls randomly select 30 precincts from a large number of precincts, then survey all members from each of the selected precincts.
  9. 9. Identify which type of sampling is used: random, systematic, convenience, stratified, or cluster. 1. A policy sobriety checkpoint stops and interviews every 5th driver. 2. An exit poll randomly selects specific polling stations and all voters are surveyed as they leave the premises. 3. An engineering student measures the strength of fingers used to push buttons by testing family members. 4. An IRS researcher investigates cheating on income taxes by surveying all waiters and waitresses at 20 randomly selected restaurants. 5. A marketing expert for MTV is planning a survey in which 500 people will be randomly selected from each age group of 10-19, 2029, … 6. A teacher surveyed all of his students to obtain a sample consisting of the number of credit cards students possess. 7. A poll of 1550 adults, subjects were selected by using a computer to randomly generate phone numbers that were called.

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