# Class Notes for PSY201H1 at University of Toronto St. George (UTSG)

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## PSY201H1 Lecture Notes - Lecture 1: Nominal Level, Descriptive Statistics, Telephone Directory

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Lecture 1 (september 13, 2016): what statistical thinking means. Scientific method (self correcting process: background research, hypothesis, experimen

View Document## PSY201H1 Lecture Notes - Lecture 3: Misleading Graph, Percentile Rank, Level Of Measurement

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Frequency distributions: tell you how many scores are located in each category of measurements; can be in any time of scale. May be structured as eithe

View Document## PSY201H1 Lecture Notes - Lecture 2: Sampling Error, Operationalization, Data Analysis

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A set of mathematical procedures for organizing, summarizing and interpreting information. Sampe: a set of individual selected from population. Variabl

View Document## PSY201H1 Lecture Notes - Lecture 4: Xg Technology, Squared Deviations From The Mean, Variance

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Goal of central tendency: find the single most representative score of your data. Central tendency: a statistical measure to determine a single score t

View Document## PSY201H1 Lecture Notes - Lecture 1: Jelly Bean, Kosovo Force, Statistical Parameter

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Constructs abstract (something we cannot see, hear or measure using a ruler) Most psychology-based research involved studying constructs (ex; mental pr

View Document## PSY201H1 Lecture Notes - Lecture 10: Statistical Hypothesis Testing, Null Hypothesis, Effect Size

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## PSY201H1 Lecture Notes - Lecture 5: Standard Deviation, Standard Score, Normal Distribution

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Psy201 lecture 5: z-scores location of scores & standardized distributions. = ss /n s = ss /(n 1) The standard normal distribution is a normal distribu

View Document## PSY201H1 Lecture Notes - Lecture 2: Divisor, Observer-Expectancy Effect, Convergent Validity

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In order for us to go out and test a hypothesis between variables we have to be able to measure/manipulate those variables. Some variables are easily d

View Document## PSY201H1 Lecture Notes - Lecture 8: Construct Validity, Covariance, Experiment

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The problem with hypothesis testing with z-scores is that the z-score formula requires that we know the value of the population standard deviation (or

View Document## PSY201H1 Lecture Notes - Lecture 8: Statistical Significance, Technology In Revelation Space, Statistical Hypothesis Testing

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The general goal of a hypothesis test is to rule out chance (sampling error, random, unsystematic factors) as a plausible explanation for the results f

View Document## PSY201H1 Lecture Notes - Statistic, Statistical Parameter, Dependent And Independent Variables

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The entire group of individuals is called the population ex. a researcher may be studying the relationship between class size and academic performance

View Document## PSY201H1 Lecture Notes - Lecture 11: Null Hypothesis, Effect Size, Statistical Hypothesis Testing

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Chapter 11: the t test for 2 related samples. Understand the structure of a research study that produces data appropriate for a repeated measures t hyp

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