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Course Schedule

Introduction

Week 1  Jan 27-Feb 3

The Basics of Quantitative Data and Why do I need to learn R?!
Lab: Getting started in R Studio

1) Lab 1 and Lab 2 on Intro to Data Analysis:

https://www.kaggle.com/code/sevdenurkoru/lab-1-introduction-to-data-analysis-using-r/edit/run/73367529

a. For PS #1 and 2

UNIT 1: Foundational Concepts

Week 2 Feb 5-10

Quantitative Measures Tables, bar graphs, and histograms  

Lab: Introduction to Graphing in R Studio (Same lab as first week)

Chapter 1: Why do We Learn Statistics Chapter 3: Getting Started With R; Chapter 4: Further R Concepts Downloading RStudio, Signing up for Kaggle

Chapter 2.2: Scales of Measurement. Chapter 6.1, 6.3, 6.7: Drawing Graphs 

PS 1 Introduction

https://www.kaggle.com/code/sevdenurkoru/problem-set-1

Week 3 Feb 18-19

Descriptive statistics for continuous distributions (Central Tendency, Variance, Skewness, Kurtosis, Box Plots)
Lab: Summary statistics in R Studio

Chapter 5.1-5.3: Descriptive Statistics

Problem Set 2

PS 2 on Measurement

https://www.kaggle.com/code/sevdenurkoru/problem-set-no-2

Week 4 Feb 24-26

Research design (validity, statistical inference, and types of research)  Lab: Manipulating data in R Studio. Chapters 7: Pragmatic Matters; Chapter 8: Basic Programming Problem Set #3

PS 3 on Summation Equation and Summary Statistics

https://www.kaggle.com/sevdenurkoru/problem-set-no-3

Week 5 Mar-3-5

Statistical inference for one variable, Part I (random sampling, probability introduction)
Lab: Review Sampling and Probability Chapters 9;10.1: Introduction to Probability; Samples and Sampling Problem Set #4

PS 4 on Data Manipulation

https://www.kaggle.com/sevdenurkoru/problem-set-4

Week 6 Mar 6

Statistical inference for one variable, Part II (z-scores, central limit theorem, and confidence intervals)  Lab: Calculating Confidence Intervals in R Studio Chapters 10.2-10.6; Estimating unknown quantities from a sample
Chapter 5.6: Standard Scores Exam #1 Review Sheet (Problem Set #5)

PS 5 is a review sheet

Week 7 Mar 10-12

Review March 10 and Exam  No Lab 
Exam #1 (March 12)

Week 8 Mar 17-19

Describing relationships between two variables (crosstabulations, scatterplots, line graphs, multiple boxplots)  Lab: Describing bivariate relationships in R StudioLab: Final Assignment First Step & Data Sources for Final Project Chapter 6.5.3; 6.6; 7.1. Drawing multiple boxplots; Tabulating and cross-tabulating data  Problem Set #6

PS 6 on Confidence Intervals and Group Project

https://www.kaggle.com/sevdenurkoru/problem-set-6

UNIT 2: Correlation, Causation, and Statistical Inference

Week 9 Mar 24-26

Correlation versus Causation (causal inference, research design redux, hypothesis testing, comparing two means: t-test and Cohen’s d)  Lab: Comparing two means in R Studio. Chapters 2: A Brief Intro to Research Design : A B(again!); 11: Hypothesis Testing; 13: Comparing Two Means Problem Set #7

PS 7 on Relationship between two variables Visualization

https://www.kaggle.com/code/sevdenurkoru/problem-set-7

Week 10 Apr 2-9

Hypothesis testing with crosstabulations (conditional probabilities, chi-square, and Cramer’s V)  

Lab: Hypothesis testing with crosstabulations in R Studio. Chapter 12-12.4: Categorical data analysis. Problem Set #8 

PS 8 on Hypothesis testing for Comparison of Groups

https://www.kaggle.com/code/sevdenurkoru/problem-set-8

SPRING BREAK (April 12-20)

Week 11 April 21-23

Hypothesis testing with two continuous variables, Part I (Introduction to Linear Regression)  

Chapter 15-15.2: Linear Regression Model 

Lab 9 on Crosstables

https://www.kaggle.com/code/sevdenurkoru/lab-9-on-crosstables

a. For PS #9

Problem Set #9

PS 9 on Crosstables

https://www.kaggle.com/code/sevdenurkoru/problem-set-9

Week 12 Apr 28-30

Hypothesis testing with two continuous variables, Part II (tests for coefficients, multiple regression, model fit) 

Chapter 15.3-1.5 Interpreting the Estimated Model 

Problem Set #10

PS 10 on Hypothesis Testing with Two Continuous Variables

https://www.kaggle.com/code/sevdenurkoru/problem-set-10

Week 13 May 5-7

Qualitative Research Methods Overview     

Lab: Final Research Project Presentations
Exam #2 Review Sheet (PS #11)   

Final Project Presentations (May 5)

Week 14 May 12-14

Exam #2 Review May 12 and Exam 2
Exam #2 (May14)

Final Exam TBA

3) Lab 3 on Central Tendency Measures and Intro to Data Visualization

https://www.kaggle.com/code/sevdenurkoru/lab-3-central-tendency-measures-and-data-visualiz

a. For PS #3

4) Lab 4 on Review and Data Manipulation

https://www.kaggle.com/code/sevdenurkoru/lab-4-review-and-data-manipulation-in-r

Lab 4 on Statistical Inference Part I

https://www.kaggle.com/code/sevdenurkoru/lab-4-statistical-inference-part-i

a. Both for PS #4

5) Lab 5 on confidence intervals

https://www.kaggle.com/code/sevdenurkoru/lab-5-calculating-confidence-intervals

a. For PS #6

6) Lab 6 on Group Project

https://www.kaggle.com/code/sevdenurkoru/gss-overview

a. For Group project and all PS asking for the group project

7) Lab 7 on Relationships between two variables

https://www.kaggle.com/code/sevdenurkoru/lab-7-relationship-between-two-variables-vis

a. For PS #7

8) Lab 8 on Hypothesis Testing and Causal Relations

https://www.kaggle.com/code/sevdenurkoru/lab-8-on-causal-inference-and-hypothesis-testing

a. For PS#8

9) Lab 9 on Crosstables

https://www.kaggle.com/code/sevdenurkoru/lab-9-on-crosstables

a. For PS #9

10) Lab 10 on Hypothesis testing with two continuous variables, Part I

https://www.kaggle.com/code/sevdenurkoru/lab-10-hypothesis-test-w-2-continuous-varspart-i

a. For PS #10

11) Lab 11 on Hypothesis testing with two continuous variables, Part II – Multiple regression

https://www.kaggle.com/code/sevdenurkoru/lab-11-multiple-regression

a. Again for PS #10