Presentation on theme: "Unit 6 Sampling 2 more writing assignments Unit 7 – Creating a Questionnaire (2-3 pages) Cover letter 10-15 questions: 2 fixed (2 choices), 5 fixed (4-5."— Presentation transcript:
1 Unit 6 Sampling 2 more writing assignments Unit 7 – Creating a Questionnaire (2-3 pages) Cover letter 10-15 questions: 2 fixed (2 choices), 5 fixed (4-5 choices), 1
open ended, at least 2 of any type How would you pretest/posttest? Format to collect info (mail, Internet, phone, etc. Unit 9 – Research Proposal (6-10 pages) Cover page, abstract, introduction, literature review, research design, sampling, data collection, research considerations, references Show
2 Unit 6 Sampling Welcome Back !!!!
Probability Samples Random Systematic Multi-cluster Probability Proportionate to Size Nonprobability Sampling Quota Snowball Purposive Convenience 3 Populations and Samples Population: A complete set of individuals, objects, or
measurements having some common observable characteristic. Sample: A subset of a population that is used to represent the population. Population Sample Does Law enforcement deal primarily with populations or samples? 4 Probability Samples o
Probability sampling helps researchers and practitioners generalize from observed cases to unobserved ones. o Estimate error o Representativeness o Equal chance of selection o Each member of a population has a known chance or probability of being selected.
5 Probability Samples Probability Sampling Simple Random Sample Systematic Multistage Cluster Probability Proportion to Size
6 Simple Random Sample Assigning a single number to each element in the population, and a table of random numbers is used to select elements for the sample. Most statistical programs have this function.
7 Systematic Sampling Every Kth element in the total population is chosen for inclusion in the sample. If a population contains 300 cases and you want a sample of 50, you select every sixth element (300 / 50). The first case would be selected at random to start the subsequent selection.
Random Start: Every 6 selected … 8 Multistage Cluster Sampling This is used when it is either impossible or impractical to compile a sampling frame for an entire population. Realistic subgroups are identified to sample through random
means. A GIS is an invaluable tool for cluster sampling. For example: Identifying all residents of a city (population) is not realistic. However, all residents live in the city which can be broken down into blocks or census block groups. After conducting a random selection of block groups, a particular number of houses in each can be sampled randomly. 9
Select Random Block Groups 10 The Selected Block Group Contains Streets 11 The Streets Contains Residential Parcels
12 Ten Houses Selected Randomly 13 Probability Proportion to Size Sampling In the previous example, not all
block groups are the same size in number of houses. Thus, the probability of one being selected changes by block group. A resolution in this case is to select a proportional number of households in each block group. 14 Probability Proportion to Size Select a Block Group
15 Probability Proportion to Size Select a proportional number of households in each block group.
16 Nonprobability Samples Nonprobability Sampling Quota Snowball Purposive Convenience Nonprobability sampling does not allow for error estimation and Representativeness can not be
assured. 17 Quota Sampling When a group has clearly defined categories of participants, a researcher could use a quota sample to be sure to select individuals in each category. One begins with a matrix in
which relative proportion is assigned to each cell and the researcher selects a sample of that proportion from each category. Oftentimes, this is used with many variables (Law enforcement example: white, male, more than 10 years on the force, sergeant). WhiteNon-White Males40%15% Females35%10% If the desired sample was 100, the researcher would sample: 15 nonwhite males and 40 white males, and 10 nonwhite females and 35 white females.
18 Snowball, Purposive & Convenient Snowball sample: A sample in which each participant interviewed or surveyed suggests others to be participants. Examples: Criminal investigations, intelligence analysis. Purposive sample: A sample the
researcher believes will yield the most comprehensive understanding of the subject of study. Examples: Individuals who have reported a crime to the police, minority individuals receiving a traffic ticket. Convenient sample: Reliance on available subjects. Examples: Individuals on a street corner, at a mall, university students, or Internet users.
19 QUESTIONS ???? Questions? Be sure to complete DB, Get Write! and quiz Unit 7 seminar next Thursday 8:00pm ET Have a great week !!!! When would a researcher use probability sampling?1. Probability sampling uses random sampling techniques to amass respondents. People can be chosen for probability sampling through the use of a random number generator or a systematic method. In either case, all members of the population have an equal chance of being selected for a study.
What is the group that we want to generalize our findings to?The group you wish to generalize to is often called the population in your study. This is the group you would like to sample from because this is the group you are interested in generalizing to.
What is probability sampling?Probability sampling refers to the selection of a sample from a population, when this selection is based on the principle of randomization, that is, random selection or chance. Probability sampling is more complex, more time-consuming and usually more costly than non-probability sampling.
When a researcher uses a stratified sampling technique they?Stratified sampling is used when the researcher wants to understand the existing relationship between two groups. The researcher can represent even the smallest sub-group in the population.
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When using probability sampling, researchers generalize from observed cases to unobserved ones
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