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Lecture

5 Selection of research participants.docx
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Department
Psychology
Course
PSYC 2001
Professor
Guy Lacroix
Semester
Fall

Description
39.39 66.67 39.39 N = 30 87.88 48.48 54.55 Mean = 65.02 72.73 81.82 45.45 SD = 15.14 75.76 63.64 45.45 30.3 57.58 78.79 66.67 60.61 69.7 15.14 75.76 66.67 72.73 60.61 93.94 75.76 30 75.76 84.85 69.7 66.67 63.64 60.61 Standard error = 2.76 N = 30 Mean = 65.02 SD = 15.14 Selection of research participants The selection of research participants - Who do we measure? - Populations and samples - Sampling techniques - How can we ever know that a sample actually reflects the entire population? • Normally distributed means of sample mean • Standard error Who do we measure? - Empirical research in psychology involves testing individuals. • Who do we measure? • How many participants should we test? Populations - Definition: The set of individuals of interest to a researcher.Aset of entities concerning which statistical inferences are to be drawn - Can be: • The students registered in PSYC 2001 D (Fall 2011) at Carleton University  Easy to get reasonable assumption. If class average is 70%, on the day of the test we knew 70% of the material on average. • Ottawa Senators’Fans  Would have to be specific as “people registered in the fan club”  If you see every senator fan across the world, harder to qualify • Citizens of Canada  Census every 4 years. Even then there is always change. Can’t sample quickly enough. • Humans  Impossible Samples - For multiple reasons, it is not typically possible to test entire populations. Instead, samples are obtained. - Sample: Asubset of a given population. The set of individuals of interest to a researcher. Aset of entities concerning which statistical inferences are to be drawn. - Sampling: The variety of ways of selecting individuals to participate in a research study. How can we ever know that a sample actually reflects the entire population? - One spoonful of soup can accurately represent the taste of the whole pot so long as everything is well-stirred. - Sample representativeness: The extent to which the characteristics of a sample reflect those of the population. • Representative  Sample characteristics = Population characteristics • Biased  Sample characteristics ≠ Population characteristics Dewey defeats Truman! - Unrepresentative sample (telephone users) led to an overestimation of the Republican vote. - Truman shows the newspaper that say that Dewey defeated Truman, but Truman was the one who won - Biased because mostly people in higher class were the ones who answered the phone polls, and the poorer people did not because they did not have phones Probability sampling - Probability sampling: The population is known and each individual has a specifiable probability of being selected. - Random:Asampling process that ensures that each individual in the population has an equal chance of being selected. • Choosing people without any bias (Ex: all names in a hat, stir, and pick out names) • Trying to set it up so there is no bias - Other probability sampling methods include: • Systematic • Proportionate random • Stratified random • Cluster Populations and sample me
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