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
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 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 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
View Document
View all (1+)

Trending

Frequently-seen exam questions from 2014 - 2018.
YORKWinter

49 Page
22 Feb 2020
View Document
YORKWinter

53 Page
22 Feb 2020
View Document
YORKWinter

62 Page
22 Feb 2020
View Document
YORKWinter

52 Page
22 Feb 2020
View Document
YORKWinter

51 Page
22 Feb 2020
View Document
YORKWinter

52 Page
22 Feb 2020
View Document
YORKWinter

59 Page
22 Feb 2020
View Document
YORKWinter

59 Page
22 Feb 2020
View Document
YORKFall

44 Page
22 Oct 2019
View Document
YORKFall

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

47 Page
22 Oct 2019
View Document
View all professors (2+)
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
View all (5+)

Most Popular

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

Most Recent

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

All Materials (1,800,000)
CA (980,000)
York (70,000)
PSYC (10,000)
PSYC 3031 (6)