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All Educational Materials for PSYC 3031 at York University (YORKU)


YORKPSYC 3031Alyssa CounsellWinter

PSYC 3031 Study Guide - Final Guide: Multiple Comparisons Problem, Linear Regression, Homoscedasticity

6 Page
31 Mar 2016
False discovery rate: fraction of statistically significant results that are actually false positives (related to type 1 error) Base rate fallacy: the
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YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 3: Local Regression, Diminishing Returns

2 Page
10 May 2017
Look at data before analyzing, stats methods can only tell you very specific things. Only by looking at it visually, you become very familiar with it +
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YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 7: Noncentrality Parameter, Null Hypothesis, Type I And Type Ii Errors

2 Page
10 May 2017
Always have to protect against both kinds of error. Example: group of 25 people, mean iq is 100 + pop sd of 15. With just one sample: cohens d * square
View Document
YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 2: Kurtosis, Skewness, Descriptive Statistics

7 Page
20 Jan 2017
Population group that your conclusions apply to. Sample group you study to estimate/generalize to your population. Polls today are more accurate than e
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YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 5: Bernoulli Trial, Null Hypothesis, Binomial Distribution

2 Page
10 May 2017
Classical (analytic) only for well-understood, regular objects. Frequentists (frequencies, mostly psychologists use) enables one to use irregular objec
View Document
YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 6: Standard Deviation, Sampling Distribution, Confidence Interval

2 Page
10 May 2017
Z = x population / standard deviation. If we assume population is normal, we can determine proportions of the population above/below each of these scor
View Document
YORKPSYC 3031Alyssa CounsellWinter

PSYC 3031 Study Guide - Final Guide: Multiple Comparisons Problem, Linear Regression, Homoscedasticity

6 Page
31 Mar 2016
False discovery rate: fraction of statistically significant results that are actually false positives (related to type 1 error) Base rate fallacy: the
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YORKWinter

PSYC 1010 Quiz: Copy of Chapter_15_Psychological_Disorders

49 Page
22 Feb 2020
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YORKWinter

PSYC 1010 Quiz: Copy of Chapter_12_Personality_Theory_Research_and_Assessment

53 Page
22 Feb 2020
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YORKWinter

PSYC 1010 Quiz: Copy of Chapter_13_Social_Behaviour

62 Page
22 Feb 2020
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YORKWinter

PSYC 1010 Quiz: Copy of Chapter_10_

52 Page
22 Feb 2020
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YORKWinter

PSYC 1010 Quiz: Copy of Chapter_14_Stress_Coping_and_Health

51 Page
22 Feb 2020
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YORKWinter

PSYC 1010 Quiz: Copy of Chapter_10_

52 Page
22 Feb 2020
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YORKWinter

PSYC 1010 Quiz: Copy of Chapter_11_Human_Development_across_the_Life_Span

59 Page
22 Feb 2020
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YORKWinter

PSYC 1010 Quiz: Copy of Chapter_11_Human_Development_across_the_Life_Span

59 Page
22 Feb 2020
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YORKFall

PSYC 1010 Study Guide - Midterm Guide: Absolute Threshold, Taste Bud, Sensory Memory

44 Page
22 Oct 2019
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YORKFall

PSYC 1010 Study Guide - Midterm Guide: Confounding, Psychological Testing, Meta-Analysis

47 Page
22 Oct 2019
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YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 7: Noncentrality Parameter, Null Hypothesis, Type I And Type Ii Errors

2 Page
10 May 2017
Always have to protect against both kinds of error. Example: group of 25 people, mean iq is 100 + pop sd of 15. With just one sample: cohens d * square
View Document
YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 2: Kurtosis, Skewness, Descriptive Statistics

7 Page
20 Jan 2017
Population group that your conclusions apply to. Sample group you study to estimate/generalize to your population. Polls today are more accurate than e
View Document
YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 3: Local Regression, Diminishing Returns

2 Page
10 May 2017
Look at data before analyzing, stats methods can only tell you very specific things. Only by looking at it visually, you become very familiar with it +
View Document
YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 6: Standard Deviation, Sampling Distribution, Confidence Interval

2 Page
10 May 2017
Z = x population / standard deviation. If we assume population is normal, we can determine proportions of the population above/below each of these scor
View Document
YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 5: Bernoulli Trial, Null Hypothesis, Binomial Distribution

2 Page
10 May 2017
Classical (analytic) only for well-understood, regular objects. Frequentists (frequencies, mostly psychologists use) enables one to use irregular objec
View Document
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YORKPSYC 3031Alyssa CounsellWinter

PSYC 3031 Study Guide - Final Guide: Multiple Comparisons Problem, Linear Regression, Homoscedasticity

6 Page
31 Mar 2016
False discovery rate: fraction of statistically significant results that are actually false positives (related to type 1 error) Base rate fallacy: the
View Document
YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 7: Noncentrality Parameter, Null Hypothesis, Type I And Type Ii Errors

2 Page
10 May 2017
Always have to protect against both kinds of error. Example: group of 25 people, mean iq is 100 + pop sd of 15. With just one sample: cohens d * square
View Document
YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 2: Kurtosis, Skewness, Descriptive Statistics

7 Page
20 Jan 2017
Population group that your conclusions apply to. Sample group you study to estimate/generalize to your population. Polls today are more accurate than e
View Document
YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 3: Local Regression, Diminishing Returns

2 Page
10 May 2017
Look at data before analyzing, stats methods can only tell you very specific things. Only by looking at it visually, you become very familiar with it +
View Document
YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 6: Standard Deviation, Sampling Distribution, Confidence Interval

2 Page
10 May 2017
Z = x population / standard deviation. If we assume population is normal, we can determine proportions of the population above/below each of these scor
View Document
YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 5: Bernoulli Trial, Null Hypothesis, Binomial Distribution

2 Page
10 May 2017
Classical (analytic) only for well-understood, regular objects. Frequentists (frequencies, mostly psychologists use) enables one to use irregular objec
View Document

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YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 6: Standard Deviation, Sampling Distribution, Confidence Interval

2 Page
10 May 2017
Z = x population / standard deviation. If we assume population is normal, we can determine proportions of the population above/below each of these scor
View Document
YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 3: Local Regression, Diminishing Returns

2 Page
10 May 2017
Look at data before analyzing, stats methods can only tell you very specific things. Only by looking at it visually, you become very familiar with it +
View Document
YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 7: Noncentrality Parameter, Null Hypothesis, Type I And Type Ii Errors

2 Page
10 May 2017
Always have to protect against both kinds of error. Example: group of 25 people, mean iq is 100 + pop sd of 15. With just one sample: cohens d * square
View Document
YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 5: Bernoulli Trial, Null Hypothesis, Binomial Distribution

2 Page
10 May 2017
Classical (analytic) only for well-understood, regular objects. Frequentists (frequencies, mostly psychologists use) enables one to use irregular objec
View Document
YORKPSYC 3031Christopher GreenWinter

PSYC 3031 Lecture Notes - Lecture 2: Kurtosis, Skewness, Descriptive Statistics

7 Page
20 Jan 2017
Population group that your conclusions apply to. Sample group you study to estimate/generalize to your population. Polls today are more accurate than e
View Document
YORKPSYC 3031Alyssa CounsellWinter

PSYC 3031 Study Guide - Final Guide: Multiple Comparisons Problem, Linear Regression, Homoscedasticity

6 Page
31 Mar 2016
False discovery rate: fraction of statistically significant results that are actually false positives (related to type 1 error) Base rate fallacy: the
View Document

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