KRIGOLSON TEACHING
  • NEUROSCIENCE
    • NEUROSCIENCE 100 >
      • NEURO 100 INTRODUCTION
      • NEURO 101 ADVANCED
      • NEURO 102 AGING
      • NEURO 103 MEMORY
      • NEURO 104 DECISION MAKING
      • NEURO 105 LEARNING
      • Research Statistics
    • NRSC 500B / MEDS 470
  • Kinesiology
    • EPHE 245 >
      • LABORATORY
      • PRACTICUM
    • EPHE 357
  • STATISTICS
    • LECTURE >
      • INTRODUCTION TO R
      • DESCRIPTIVE STATISTICS
      • VISUALIZING DATA
      • Correlation and Regression
      • MULTIPLE REGRESSION
      • LOGIC OF NHST
      • T TESTS
      • ANOVA
      • POST HOC ANALYSIS
      • NON PARAMETRIC STATISTICS
      • FACTORIAL ANOVA
      • Repeated Measures ANOVA
      • Mixed ANOVA
      • MULTIVARIATE ANOVA
      • THE NEW STATISTICS
      • Bayesian Methods
    • ASSIGNMENTS >
      • Introduction to R >
        • INTRODUCTION TO R
        • LOADING DATA
        • DATA TABLES
      • Descriptive Statistics >
        • Mean, Median, and Mode
        • VARIANCE
        • CONFIDENCE INTERVALS
        • SHORTCUTS
      • Visualizing Data >
        • PLOTTING BASICS
        • BAR GRAPHS
        • BOXPLOTS
        • HISTOGRAMS
        • USING GGPLOT I
        • USING GGPLOT II
        • USING GGPLOT III
      • Correlation and Regression >
        • CORRELATION
        • REGRESSION
      • MULTIPLE REGRESSION >
        • MULTIPLE REGRESSION
      • Logic of NHST >
        • Sample Size and Variance
        • DISTRIBUTIONS
        • TESTING DISTRIBUTIONS
      • T-Tests >
        • Single Sample TTests
        • Paired Sample TTests
        • Independent Sample TTests
      • ANOVA >
        • ANOVA ASSUMPTIONS
        • ANOVA
      • POST HOC ANALYSIS >
        • POSTHOC ANALYSIS
      • NON PARAMETRIC STATISTICS >
        • WILCOXON TEST
        • WILCOXON SIGNED TEST
        • MULTIPLE GROUPS
      • FACTORIAL ANOVA
      • REPEATED MEASURES ANOVA >
        • RM ANOVA
        • TREND ANALYSIS
      • MIXED ANOVA
      • MULTIVARIATE ANOVA
      • THE NEW STATISTICS
      • BAYESIAN TTESTS
    • RESOURCES
    • R TIPS
  • Directed Studies
    • Advanced Topics in Motor Control A
    • Advanced Topics in Motor Control B
    • An Introduction to EEG
    • Advanced EEG and ERP Methods
    • Neural Correlates of Human Reward Processing
    • Independent Research Project
  • MATLAB
    • THE BASICS >
      • Hello World
      • BASIC MATHEMATICS
      • VARIABLES
      • Matrices
      • Writing Scripts
      • PATHS AND DIRECTORIES
      • USER INPUT
      • FOR LOOPS
      • WHILE LOOPS
      • IF STATEMENTS
      • RANDOM NUMBERS
    • STATISTICS >
      • LOADING DATA
      • DESCRIPTIVE STATISTICS
      • MAKING FUNCTIONS
      • BAR GRAPHS
      • LINE GRAPHS
      • TTESTS
    • EXPERIMENTS: THE BASICS >
      • DRAWING A CIRCLE
      • DRAWING MULTIPLE OBJECTS
      • DRAWING TEXT
      • DRAWING AN IMAGE
      • PLAYING A TONE
      • KEYBOARD INPUT
      • BUILDING A TRIAL
      • BUILDING TRIALS
      • NESTED LOOPS
      • RIGHT OR WRONG
      • SAVING DATA
    • EXPERIMENTS: ADVANCED >
      • STROOP
      • N BACK
      • Oddball
      • Animation
      • VIDEO
    • EEG and ERP Analysis >
      • ERP Analysis
  • RESOURCES
    • EXCEL
    • HOW TO READ A RESEARCH PAPER
    • HOW TO WRITE A RESEARCH PAPER
  • Workshops
    • Iowa State EEG Workshop 2018
  • Python
    • The Basics >
      • Setting Up Python
      • Hello, world!
      • Basic Math & Using Import
      • Variables
      • Matrices
      • Scripts
      • User Input
      • For Loops
EPHE 357
Course Material

Course Outline

Research Project Overview

​Sample Research Project Paper

TCPS Core 2 Link
Introduction
Wednesday, September 8th
Reading: Chapter One
Introduction to Research
​Tuesday, September 14th
Quiz Questions

1. What is a research question?
  Reading: Pages 37-40
  Watch: What is a research question?

2. What are qualitative, quantitative, and mixed research designs?
  Reading: Pages 4-8
  Watch: What are quantitative, qualitative, and mixed research designs?

3. What are independent and dependent variables?
  Reading: Pages 31-32
  Watch: What are independent and dependent variables?
​

4. What is a hypothesis?

  Reading: Pages 37-40
  Watch: What is a hypothesis?

Reading: Chapter Two
Designing a Research Study
Wednesday, September 15th
Literature Review
Tuesday, September 21st
Quiz Questions

1. What is a scientific literature review?
  Reading: Pages 26-29
  Watch: What is a scientific literature review?

2. What is the difference between primary research articles, review papers, and other forms of dissemination?
  Reading: Pages 26-29
  Watch: Research articles, review papers, and everything else

3. How do you assess journal quality?
  Reading: Impact Factors
  Watch: How do you assess journal quality?

4. How do you assess article quality?
  Reading: Citation Counts
  Watch: How do you assess article quality?

Reading: Chapters One and Two
Interpreting Research
Wednesday, September 22nd
Watch: Martin Chalfie
​Watch: Brian Kobilka
Research Ethics
Tuesday, September 28th
Quiz Questions

1. What are three of the research ethics guidelines established following the Nuremberg Trials?
  Reading: Chapter Three
  Watch: YouTube

2. What are two ethical guidelines that changed between the Nuremberg mandate and Helsinki?
  Reading: Chapter Three
  Watch: YouTube

3. What are the three overall principles that guide research in Canada?
  Reading: Chapter Three
  Watch: YouTube
​
4. What is informed consent and why it is important?

  Reading: Chapter Three
  Watch: YouTube

Reading: Chapter Three
TCPS Core 2
​Wednesday, September 29th
Complete the TCPS2: Core module at the link below and send a copy of your certificate to Dr. Krigolson.

TCPS2: Core
The Scientific Process
Tuesday, October 5th
Quiz Questions

1. Outline the scientific process.
  Watch: YouTube

2. What happens in the selection of sample, selection of variables, and data collection phases of the scientific process?
  Watch: YouTube

3. What happens during data analysis?
  Watch: YouTube
​
4. What is knowledge translation?

  Watch: YouTube

Reading: Text, Chapters One and Two
Qualitative Research Methods
​Tuesday, October 12th
Quiz Question
What are the four methods of collecting qualitative data?


1. Qualitative Methods: Interviews
  Watch: YouTube

2. Qualitative Methods: Observation
  Watch: YouTube

3. Qualitative Methods: Written Documents
  Watch: YouTube
​
4. Qualitative Methods: Imagery

  Watch: YouTube

Reading: Text, Chapters Seven and Eight
Quantitative Research Methods
​Tuesday, October 19th
Quiz Questions

1. What do we mean by internal and external validity?
  Watch: YouTube

2. What is the difference between a between or within subjects research design?
  Watch: YouTube

3. What are discrete and continuous data types?
  Watch: YouTube
​
4. What are five different ways you can get samples?

  Watch: YouTube

Reading: Chapters Four, Five, and Six
Descriptive Statistics
​Tuesday, October 26th
Quiz Questions

1. What are the mean, median, and mode?
  Watch: YouTube

2. What is the standard deviation?
  Watch: YouTube

3. What is a 95% confidence interval?
  Watch: YouTube
​
4. What is a box plot?

  Watch: YouTube

Lecture Video
Lecture Slides
Descriptive Statistics
Wednesday, October 27th
Learning Outcomes
1. Be able to compute a mean in EXCEL / Sheets
2. Be able to compute a standard deviation in EXCEL / Sheets
3. Be able to compute a 95% confidence interval in EXCEL / Sheets
4. Be able to make a simple bar graph with error bars in EXCEL / Sheets

SAMPLE DATA
Z-Scores and T-Tests
Tuesday, November 2nd
Quiz Questions

1. What is a Z-Score?
     YouTube

2. What is a single sample T-Test?
     YouTube

3. What is an independent samples T-Test?
     YouTube

4. What is a dependent samples T-Test?
     YouTube

NB, for questions 2, 3, and 4 you do not need to know how to the math! In the video (it's the same for all three, start at 5:22 to get the definitions. Watch the rest for understanding. We will discuss all this in the lecture on Tuesday to understand how it all works. You just need to know the broad definitions for these four questions.

LECTURE SLIDES
Z-Scores and T-Tests: Practical
​Wednesday, November 3rd
Download JASP HERE

Data Set 1
Data Set 2

Practical Assignment
Q1. You collect the data below from a sample of babies. The data reflects the mean age at which they walk. Does your sample mean differ from the population mean of 14? 
​Assignment Data 1
Q2. You take caloric data from a group of undergraduates below and after a month of intermittent fasting. Did the intermittent fasting reduce caloric intake?
Assignment Data 2
Q3. You take reaction time data from a group of people from BC and a group of people from Alberta. Did the reaction time differ between groups? How? NB, there is a trick to this question.
Assignment Data 3
For each question, report the appropriate tests of assumptions, the means, the confidence intervals, and the results of your statistical test.
Correlation and Regression
Tuesday, November 16th
Quiz Questions

1. Explain what correlation is.
     YouTube

2. Explain what regression is.
     YouTube

3. How would you predict a value using regression?
     YouTube

4. What is multiple regression.
     YouTube

NB, as with t-tests, the point of these questions is to understand the techniques, not know all of the underlying math.

Lecture Slides
Correlation and Regression: Practical
​Wednesday, November 17th
Practice Data Set 1
Practice Data Set 2

Practical Assignment
Q1. Does income predict happiness? Download the sample data set HERE. What is the correlation between income and happiness? What is the 95% confidence interval of this correlation? Is the correlation significant.
Q2. Do you think there are any outliers in this data? Why? Why not? If so, remove the outliers and rerun the correlation. Does this improve the model?
Q3. What is the regression model for this data? As in, write out the y = mx + b format. Is the regression model significant. What similarities do you notice with the correlation results?
Q4. You find a new person outside of the data set with an income of $84000.00. What would you predict their happiness score to be using the regression model from Q3?
Analysis of Variance (ANOVA)
​Tuesday, November 23rd
Quiz Questions

1. What is a ANOVA?
     YouTube

2. What is a Post Hoc Test and why would you use it?
     YouTube

3. What are the assumptions of ANOVA?
     YouTube

4. What is a repeated measures ANOVA?
     YouTube

NB, as with t-tests, the point of these questions is to understand the techniques, not know all of the underlying math.

Lecture Slides
Analysis of Variance (ANOVA): Practical
​Wednesday, November 24th
PracticeData
AssignmentData

Q1. Your assignment data is from three groups (young = 1, middle aged = 2, and elderly = 3) and reflects their caloric intake per day. Do these groups differ in terms of caloric intake? Report the results of the ANOVA.
Q2. Were the statistical assumptions of ANOVA met?
Q3. Choose a post-hoc test to further interpret the data. Report the results of this test.
Knowledge Translation
Tuesday, November 30th
Knowledge Translation: Practical
​Wednesday, December 1st
Read the following PAPER.

Activity
With a partner, write a knowledge translation piece for this paper for a press release. In no more than 200 words, explain the study using language and wording that anyone could understand - not just people with university degrees, but literally anyone. Email me your submission with both your names on it.
  • NEUROSCIENCE
    • NEUROSCIENCE 100 >
      • NEURO 100 INTRODUCTION
      • NEURO 101 ADVANCED
      • NEURO 102 AGING
      • NEURO 103 MEMORY
      • NEURO 104 DECISION MAKING
      • NEURO 105 LEARNING
      • Research Statistics
    • NRSC 500B / MEDS 470
  • Kinesiology
    • EPHE 245 >
      • LABORATORY
      • PRACTICUM
    • EPHE 357
  • STATISTICS
    • LECTURE >
      • INTRODUCTION TO R
      • DESCRIPTIVE STATISTICS
      • VISUALIZING DATA
      • Correlation and Regression
      • MULTIPLE REGRESSION
      • LOGIC OF NHST
      • T TESTS
      • ANOVA
      • POST HOC ANALYSIS
      • NON PARAMETRIC STATISTICS
      • FACTORIAL ANOVA
      • Repeated Measures ANOVA
      • Mixed ANOVA
      • MULTIVARIATE ANOVA
      • THE NEW STATISTICS
      • Bayesian Methods
    • ASSIGNMENTS >
      • Introduction to R >
        • INTRODUCTION TO R
        • LOADING DATA
        • DATA TABLES
      • Descriptive Statistics >
        • Mean, Median, and Mode
        • VARIANCE
        • CONFIDENCE INTERVALS
        • SHORTCUTS
      • Visualizing Data >
        • PLOTTING BASICS
        • BAR GRAPHS
        • BOXPLOTS
        • HISTOGRAMS
        • USING GGPLOT I
        • USING GGPLOT II
        • USING GGPLOT III
      • Correlation and Regression >
        • CORRELATION
        • REGRESSION
      • MULTIPLE REGRESSION >
        • MULTIPLE REGRESSION
      • Logic of NHST >
        • Sample Size and Variance
        • DISTRIBUTIONS
        • TESTING DISTRIBUTIONS
      • T-Tests >
        • Single Sample TTests
        • Paired Sample TTests
        • Independent Sample TTests
      • ANOVA >
        • ANOVA ASSUMPTIONS
        • ANOVA
      • POST HOC ANALYSIS >
        • POSTHOC ANALYSIS
      • NON PARAMETRIC STATISTICS >
        • WILCOXON TEST
        • WILCOXON SIGNED TEST
        • MULTIPLE GROUPS
      • FACTORIAL ANOVA
      • REPEATED MEASURES ANOVA >
        • RM ANOVA
        • TREND ANALYSIS
      • MIXED ANOVA
      • MULTIVARIATE ANOVA
      • THE NEW STATISTICS
      • BAYESIAN TTESTS
    • RESOURCES
    • R TIPS
  • Directed Studies
    • Advanced Topics in Motor Control A
    • Advanced Topics in Motor Control B
    • An Introduction to EEG
    • Advanced EEG and ERP Methods
    • Neural Correlates of Human Reward Processing
    • Independent Research Project
  • MATLAB
    • THE BASICS >
      • Hello World
      • BASIC MATHEMATICS
      • VARIABLES
      • Matrices
      • Writing Scripts
      • PATHS AND DIRECTORIES
      • USER INPUT
      • FOR LOOPS
      • WHILE LOOPS
      • IF STATEMENTS
      • RANDOM NUMBERS
    • STATISTICS >
      • LOADING DATA
      • DESCRIPTIVE STATISTICS
      • MAKING FUNCTIONS
      • BAR GRAPHS
      • LINE GRAPHS
      • TTESTS
    • EXPERIMENTS: THE BASICS >
      • DRAWING A CIRCLE
      • DRAWING MULTIPLE OBJECTS
      • DRAWING TEXT
      • DRAWING AN IMAGE
      • PLAYING A TONE
      • KEYBOARD INPUT
      • BUILDING A TRIAL
      • BUILDING TRIALS
      • NESTED LOOPS
      • RIGHT OR WRONG
      • SAVING DATA
    • EXPERIMENTS: ADVANCED >
      • STROOP
      • N BACK
      • Oddball
      • Animation
      • VIDEO
    • EEG and ERP Analysis >
      • ERP Analysis
  • RESOURCES
    • EXCEL
    • HOW TO READ A RESEARCH PAPER
    • HOW TO WRITE A RESEARCH PAPER
  • Workshops
    • Iowa State EEG Workshop 2018
  • Python
    • The Basics >
      • Setting Up Python
      • Hello, world!
      • Basic Math & Using Import
      • Variables
      • Matrices
      • Scripts
      • User Input
      • For Loops