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PSYC 2510 (86)
Lecture

# Introductory Statistics

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School
York University
Department
Psychology
Course
PSYC 2510
Professor
Agnieszka Kopinska
Semester
Fall

Description
INTRODUCTORY STATISTICS  Statistics – the use of numbers that allows for the collection, classification, and interpretation of facts  Another way of quantifying properties of objects or events of interest  Increase precision of communication/description  Used to go beyond the numbers  Population – all members of a group who are alike on at least one specified characteristic  Sample – any number of cases less than the total number of cases in the population from which it is drawn  Usually the object of studies  Used to make inferences about the characteristics of the larger population as a whole  Must be representative of the population to draw meaningful and accurate inferences  Samples from different populations can be compared in a study  Must be comparable – members of both samples would be expected to perform in the same way when tested in the same conditions  Selection methods matter TYPES OF SAMPLES  Radom Sample – each member of the pool has an equal probability of being selected on any given draw and each possible sample of members has an equal probability of being selected  May not be representative  Random from the whole population  Randomized sample – each member of the sample has an equal chance of being assigned to a given condition of the experiment  Already have your sample, but they are assigned to different parts of the study  Matched sample – yields pairs of observations to produce highly comparable groups  Two participants paired based on similarities in relevant characteristics and each takes part in one of the conditions OR  The same participant takes part in both conditions  Most suitable for experiments in which there are only 2 groups PARAMETERS AND STATISTICS  Population parameters – the properties of populations  E.g. The average number of books read by college graduates last year in North America TYPES OF DATA  Numerical data – data in numbers  Tell us how much of a given property each sample member exhibits  Magnitude data – number indicating the amount of a property that exists along a continuum (“how much”)  Rank-order (ordinal) data – amounts of a property expressed as a rank relative to other individuals (1 , 2 , 3 )d  Categorical/Nominal Data – information that reflects mutually exclusive categories in which participants fall  Either the characteristic is displayed or it isn’t  E.g. male or female, tall or short TYPES OF STATISTICS  Descriptive statistics – used to organize and summarize data  Measures of central tendency – common patterns in data (the mean, median and mode)  Normal distribution – mode, median and mean are all equally distributed  Stability – the mean is usually the most stable across samp
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