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### HEOC 715: Sampling & Participants

How Sampling Affects Research

Collecting Quantitative Data:Probability Sampling: First Step

- Whom will you study? Individuals, entire organizations, both? (i.e., Identify your unit of analysis)
- Which type of people or organizations will you study? (i.e., specify the population and sample)
- How many will you need for your research? (i.e., sample size varies based on statistical procedures):
- ~15 in each group for experimental study
- ~30 for correlational study
- ~350 for a survey

Collecting Quantitative Data:Probability Sampling – Next Step

- Specify population and sample
- Target population (reflects common characteristics related to the study). Ex. All teachers in high schools in one city.
- Sample for study (subgroup of target population), which can be used to generalize about target population . Ex. Sample of high school teachers from target group.

Above illustrates … Probability Sampling, i.e., every member of the population has an equal chance of being selected.

Collecting Quantitative Data:Probability Sampling

- Specify population and sample: Alternative Plan
- Select a sample consisting of only biology teachers in two schools in the same city

Above illustrates nonprobability sampling: i.e., nonrandom procedures are used for selecting individuals in the sample. Process driven by availability, , convenient and compatibility with the study.

Which type of study uses nonprobability sampling (Quantitative or Qualitative) and why?

Collecting Quantitative Data:Probability Sampling

- Probabilistic Sampling vsNonprobabilistic Sampling: Which approach to use??
- The decision is based on such factors as: the type and purpose of the research study; the makeup of the target population; and, the availability of participants.
- Probability Sampling is the most rigorous and enables the researcher to:
- claim that the sample is representative of the population;
- make generalizations about the population at large.

Collecting Quantitative Data:Probability Sampling

- Types of Probability Sampling:
- Simple random sampling : any individual from a population has an equal probability of being selected. Can be unwieldy if the target population is large and not numbered.

Procedure:

- Typically a computer program is utilized, which assigns numbers to each individual in the target population, randomly generates sample numbers and a listing of names associated with a number.
- Drawbacks of simple random sampling
- The technique requires that all individuals in the target population be coded with a number, which confounds the practicality of the method.

Collecting Quantitative Data

Alternative Sampling Methods:

- Systematic Sampling
- Select every nth individual from the total number of members in the population
- Not as precise or rigorous as simple random sampling, but more convenient
- Example of Systematic Sampling:

School District Administrators plans to study parent satisfaction. Selects a % of the parents to study, i.e., 20%. Given 1000 parents, 200 (or 20%) would be studied. The administrator uses intervals of 5 (200/1000, or 1 out of 5 parents) from the target mailing list. Every 5th parent is surveyed.

Collecting Quantitative Data:Probability Sampling

Alternative Sampling Methods:

- Stratified (Random) Sampling
- Population divided by the number of subgroups (strata) being studied (e.g., gender, age, income, etc.)

For ex.: If you are studying opinions on a specific political issue, you would divide the population in subgroups based on what? Why?

- Once the strata is identified, simple random or systematic sampling used to select individuals from each subgroup.
- Major advantage: guarantees representation of defined groups in the population

Collecting Quantitative Data:Probability Sampling

Cluster Sampling

- Challenge of random sampling: listing all members of a target population and selecting a sample from them.

For ex., it’s very difficult to study a sample scattered across the US; or a target population of American high schools students which is too large to list and draw a sample.

- Cluster sampling uses a group of individuals who are together naturally, e.g., school districts, an elementary school, or intact classrooms.
- To minimize sampling error: all members of the cluster must be part of the sample; clusters must be chosen randomly from a population of clusters.

Specific Differences between Quantitative and Qualitative Data Collection

1. a. Quantitative: participants and sites systematically identified with random sampling;

b. Qualitative: participant and site selections based on subjects and places that best inform the phenomena under study;

Specific Differences between Quantitative and Qualitative Data Collection

2.a. Both require permissions to begin a study;

b. Qualitative needs greater access to a site to garner information, observe participants and record data;

c. Quantitative process requires less participation at the site, which varies based on the type of research interests being studied.

Specific Differences between Quantitative and Qualitative Data Collection

3. a. Both collect data, e.g., interviews, observations, documents;

b. Qualitative research relies on general interviews or observations, encourages participants to share their viewpoints, utilizes open-ended quesitons;

c. Quantitative research uses standardized instruments and collects closed-ended, objective information.

Specific Differences between Quantitative and Qualitative Data Collection

4.a. Both approaches record information provided by participants;

b. Qualitative research record information on self-developed protocols, which provide a venue for organizing participants’ responses to each question;

c. Quantitative research uses predesigned instruments with defined procedures and operational standards.

Specific Differences between Quantitative and Qualitative Data Collection

5. a. Qualitative researchers are sensitive to the challenges and ethical issues involved in collecting information face-to-face in a variety of sites, e.g., people’s homes or in the workplace.

b. Quantitative researchers utilize objectives measures that follow a prescribed process and include such tools as anonymous questionnaires and standardized observational checklists designed to ensure reliable results.

Collecting Qualitative Data: Nonprobability Sampling

- Convenience Sampling: uses available individuals for a study;

How would you know that convenience sampling was used in a study?

In what type of research would convenience sampling be most informative?

- Quota Sampling: utilizes nonrandom sampling to identify a group with characteristics of the target population.

Collecting Qualitative Data: Nonprobability Sampling

- Purposeful Sampling: individuals or sites selected to learn or understand the phenomenon under study. Researchers using this type of sampling need to identify the sampling strategy and be able to defend its use.
- Types of Purposeful Sampling
- Typical case
- Extreme case
- Maximum case
- Snowball
- Critical Case

Sampling Activity

How would you select a sample of 40 college students for a morale study from a freshman class of 320?

- Identify the sampling procedure you would use.
- Describe how you will use the technique.
- What are the strengths and weaknesses of the sampling process?

Sampling Activity

A sociologist plans to research the effect of a regimented exercise program on the weight loss of ten people who completed the entire program at a local health club. The researcher plans to interview the participants about their program, and will record responses relative to the amount of weight loss and any additional open-ended testimonials provided.

- Is this a quantitative or qualitative study? Why?
- What type of sampling strategy is used? Explain.
- Explain the pros and cons of the sampling strategy.

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