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Unformatted text preview: PSYC 310 - Chapter 5 Selecting Research Participants Sampling
In order to decide who to recruit for your study (sample), you need to first determine who your population is. Population: a group sharing some common characteristic(s). Sample: a subset of this group. Sampling Population: a whole pie Sample: a slice of that pie Target population: entire set of individuals sharing the characteristic of interest. Accessible population: portion of TP that can be recruited to participate. Sample: individuals selected to be in your study. Representativeness
You want to be sure that the people in your sample are a true representation of those in the population of interest. The more representative the sample, the more confidence we have that the results can be generalized to the population. Biased Sample
When participants in your sample differ from your population on a given characteristic, you have a biased sample. Can be the result of the manner in which participants were selected (selection or sampling bias). Sample Bias
Obvious bias: Low return rate of surveys. Subtle bias: Researcher avoids higher floors of a building while doing a door to door survey. More subtle bias: highly motivated subjects, large financial compensation for participation. Sampling
Why not just include everyone in the population? Not always possible Population too large Too costly Time-consuming Unwieldy Not necessary Law of Large Numbers
The bigger the sample size, the more accurately it will represent the population up to a certain point. Based on mathematical probability.
10 Avg. distance between 5 sample & pop. mean 0 1 4 9 16 25 36 49 64 81 100 Number of scores in the sample Law of Large Numbers
In practical terms, this means that you don't need large numbers of participants to ensure representativeness. A minimum of 10 participants per treatment condition is required, however, for statistical purposes. Law of Large Numbers
E.g.: the effectiveness of Ritalin in treating symptoms of children with ADD
Ritalin 10 No Ritalin 10 Ritalin 10 Ritalin 10 No Ritalin 10 No Ritalin 10 Placebo 10 Strattera 10 Placebo 10 Sampling Procedures
Probability Sampling: based on random sampling: each member of a particular population has an equal chance of being selected. Nonprobability Sampling: not randomly selected: each member of a particular population does not have equal chance of being selected. Probability Sampling Simple random sampling Systematic random sampling Stratified random sampling Proportionate Stratified random sampling Multistage random sampling Cluster random sampling Simple Random Sampling Entire population is represented Draw names out of a hat Use a random numbers table With or without replacement Systematic Sampling Entire population is represented Every nth person How to figure out n:
Step 1: Pop. size / sample size needed = n interval 500 / 50 = 10 Step 2: Randomly pick a number from 1-10 Step 3: Pick every 10th person on your list after that number Systematic Sampling Stratified Sampling Used to represent key subgroups in your pop. Participants chosen by taking a simple random sample in each subgroup. Select equal numbers from within each subgroup. Stratified Sampling Stratified Sampling Ensures all subgroups are equally represented in your sample. Useful when your goal is to make comparisons among subgroups. BUT - does not adequately represent proportions found in population. 50 10 10 10 Proportionate Stratified Sampling Sample mirrors proportions found in population. Determine correct proportions & randomly select from within that subgroup. pop = 60% men; 40% women sample = 60 men, 40 women pop = 10% men; 90% women sample = 10 men, 90 women Multistage Sampling Random sampling at several stages Start wide and narrow down at each level Example: Canadian university professors' opinions on student literacy. Multistage Sampling
Stage 1: Randomly select universities across Canada Stage 2: Randomly select departments within universities Stage 3: Randomly select professors within departments Cluster Sampling Randomly select groups rather than individuals. Example: Children's adjustment to daycare. Probability Sampling
Random sampling is sometimes unrealistic, especially in psychological research. too much time and effort, may not be practical or possible, need a list of all members of population representativeness is not always necessary Non -Probability Sampling Convenience sampling Purposive sampling Quota sampling Snowball sampling Convenience Sampling Also called accidental sampling Grab whomever you can "Man on the street" type interviews Setting up a booth in school cafeteria Representativeness? Bias? Volunteer characteristics? Easy / less costly / more timely Purposive Sampling
Purposely select participants with characteristics relevant to the research question. Example: post-partum depression, suicide, addiction Quota Sampling
Reflect proportions in population, but not randomly selected. pop = 60% men; 40% women sample = 60 men, 40 women Snowball Sampling
Begin with someone who meets the criteria for inclusion in your study. Then ask them to recommend others who they may know who also meet the criteria. Sometimes the only way to get in. Journal Articles
Standard Format: American Psychological Association (APA) has developed a set of guidelines on how to organize and format a journal article. Abstract or summary Introduction Research Method Results Discussion Journal Articles
Abstract: Single paragraph giving you an overview of the article. You can quickly decide of this is an article that is relevant to your topic. the purpose of the research the main method used to collect data the main finding of the research the main conclusion Journal Articles
Introduction: Explains why the researcher is doing what he/ she is doing the logic behind the study. Outlines the importance of the study & it's potential contribution. what the research is about why the research matters what we know & don't know the main hypothesis/research question Journal Articles
Research Method: Explains exactly how the study was carried out and how information was gathered. Very detailed (transparency & replication). methods used to collect data identifies IVs and DVs states operational definitions Literature Review
Process: Summarize and organize. For each abstract/article you read, write a summary of the main points. Organize your summaries according to the particular aspect of the topic the article addresses. Organizing puzzle pieces. Journal Articles
Results: Main findings of the study: lots of statistics, graphs, figures, tables. Journal Articles
Discussion: Evaluate findings: explain why you got what you did, and discuss the significance of the findings in relation to what is already known. major findings relevance to other findings study strengths & weaknesses conclusions about findings directions for future research Internet Searches
Domain Types: The last three letters of the web address (URL suffix) are a clue as to who sponsors the site.
Commercial (.com) Educational (.edu) Governmental (.gov) Military (.mil) Network (.net) Non-profit org. (.org) Country (.ca) Internet Guidelines
1. Who is the author? Credentials? 2. What is the domain type? 3. Is the site current? Recently revised? 4. Website design does it appear too commercial? Many pop-ups? 5. Quality of information scientific or opinion? 6. Are there links? To what sites? Literature Review
Purpose: Summarize the research that is relevant to your study Critically analyze the research Compare the studies to one another Discuss how they relate to what your going to do Literature Review
Writing it up: Go from broad to specific. Start with a broad statement about the topic in general. Work you way down (upside pyramid) to more specific statements. Literature Review
Writing it up: Each statement should be a logical extension of the previous one. You need to link your ideas so that there is a smooth flow from one paragraph to the next. ...
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This note was uploaded on 04/29/2010 for the course PSYCH 310 taught by Professor T.bianco during the Winter '10 term at Concordia Canada.
- Winter '10