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

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UTSGPSY201H1Ashley Waggoner DentonFall

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

OC5238806 Page
15 Sep 2016
4
Lecture 1 (september 13, 2016): what statistical thinking means. Scientific method (self correcting process: background research, hypothesis, experimen
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UTSGPSY201H1Ashley Waggoner DentonFall

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

OC1863963 Page
18 Apr 2016
16
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
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UTSGPSY201H1Molly MetzFall

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

OC5253174 Page
29 Nov 2018
0
A set of mathematical procedures for organizing, summarizing and interpreting information. Sampe: a set of individual selected from population. Variabl
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UTSGPSY201H1Ashley Waggoner DentonFall

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

OC1863965 Page
18 Apr 2016
11
Goal of central tendency: find the single most representative score of your data. Central tendency: a statistical measure to determine a single score t
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UTSGPSY201H1Christine BurtonFall

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

OC7830332 Page
9 Nov 2016
3
Constructs abstract (something we cannot see, hear or measure using a ruler) Most psychology-based research involved studying constructs (ex; mental pr
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UTSGPSY201H1Gabriela IlieSummer

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

OC4415157 Page
21 Apr 2016
24
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UTSGPSY201H1Ashley Waggoner DentonFall

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

OC1863962 Page
18 Apr 2016
13
Psy201 lecture 5: z-scores location of scores & standardized distributions. = ss /n s = ss /(n 1) The standard normal distribution is a normal distribu
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UTSGPSY201H1Ashley Waggoner DentonFall

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

OC1863963 Page
18 Apr 2016
20
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
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UTSGPSY201H1Ashley Waggoner DentonFall

PSY201H1 Lecture Notes - Lecture 8: Construct Validity, Covariance, Experiment

OC1863965 Page
18 Apr 2016
18
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
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UTSGPSY201H1Gabriela IlieSummer

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

OC44151512 Page
21 Apr 2016
12
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
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UTSGPSY201H1Gillian RoweFall

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

OC227325 Page
29 Jan 2012
35
The entire group of individuals is called the population ex. a researcher may be studying the relationship between class size and academic performance
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UTSGPSY201H1Gabriela IlieSummer

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

OC4415159 Page
21 Apr 2016
18
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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