Dates and time: 21, 24, and 31 October + 5, 8, and 12 November 2024 from 9:30 to 15:00

HUM DataLab offers a PhD course that covers basic concepts of inferential statistics. The focus will be on both conceptual and practical issues with short presentations and hands-on exercises. Inferential statistics is about generalizing from a sample to a population and we will talk about avoiding common mistakes when making inferences from data. The course will also introduce you to R programming language for exploring and analyzing data. During the hands-on exercises, you will have a chance to experiment with R and apply what you learned throughout the course. The instructor, data specialist Selda Eren, has a PhD in Cognitive Science and taught statistics at Ohio University. The course does not assume any prior knowledge about programming or statistics. 

Attention: The course will involve a fair amount of mathematical concepts and techniques. Participants are encouraged to have a familiarity with basic algebra and a general understanding of graphical data representation.

Academic aim:
 – understand key concepts and methods of inquiry in elementary statistics including descriptive and inferential statistics
 – perform inferential testing including z-test, t-test, analysis of variance (ANOVA), correlation, regression, and chi-square using R
 – formulate hypotheses and apply appropriate statistical procedures to real-world problems
 – read and understand articles with statistical content

Course Work:
 – Reading assignments
 – Weekly questions and R exercises for practice (not graded but emailed to the instructor)
– Presentation: Participants will select one statistical method covered in the course to analyze either a dataset from their own research or one supplied by the instructor. On the sixth day of the course, students will present a 10-minute overview of their project in progress, to get constructive feedback from both the instructor and their peers.
 – Project Report: To fulfil the course requirements and receive credit, students must submit a detailed 4-page report on their project within two weeks following the course’s conclusion.

Target Group: This course is specifically designed for students in the Humanities. All examples and data used will be directly applicable to and focused on research within the Humanities field.

Course organiser:  Selda Eren (selda.kanat@hum.ku.dk), Data Specialist, Faculty Service, Research and Impact, Faculty of Humanities, University of Copenhagen. 

Course dates: 
21 October 2024
24 October 2024
31 October 2024
5 November 2024
8 November 2024
12 November 2024

Programme:

Day 1
09:30 (With 10 minute breaks every 50 minutes)
Introduction
Program, objectives
Basic Concepts
Descriptive Statistics
Visualization
Basic Probability

12:30 Lunch

13:00 (With 10 minute breaks every 50 minutes)
Introduction to R and Rstudio, Exercises

15:00 End

Day 2
09:30 (With 10 minute breaks every 50 minutes)
Introduction to Statistical Analysis
The normal distribution
Population vs Sample
Percentiles
Probability Distribution
Hypothesis Testing
Sampling Distribution of the Mean
Central Limit Theorem

12:30 Lunch

13:00 Exercises (With 10 minute breaks every 50 minutes)

15:00 End

Day 3
9.30 (With 10 minute breaks every 50 minutes)
z-test
Independent Samples t-test
Confidence Intervals
Type 1 and Type 2 errors

12.30 Lunch

13.00 Exercises (With 10 minute breaks every 50 minutes)

15:00 End

Day 4
09:30 (With 10 minute breaks every 50 minutes)
Related samples t-test
ANOVA
Chi-Square

12:30 Lunch

13:00 Exercises

14:00 Invited talk: A research case

15:00 End

Day 5
9:30 (With 10 minute breaks every 50 minutes)
Correlation
Regression
Statistical Power
Effect Size

12:30: Lunch

13:00
Exercises
Writing a Statistical Report
Discussion of project requirements
Description of the dataset

15:00 End

Day 6
9:30 (With 10 minute breaks every 50 minutes)
Exercises
Student Presentations

12:30: Lunch

13:00
Student Presentations
Conclusion and feedback about the course

15:00 End

ECTS: 4.5

Max. number of participants: 15

Course fee: The PhD School at the Faculty of Humanities is part of the national network regarding PhD courses. Courses offered as part of this network are usually free of charge for PhD students from participating universities. Copenhagen Business School (CBS) is not part of the network. Thus, PhD students from CBS is charged a course fee for participation in the course (1.200 per ECTS).

Registration: Please register via the link in the box no later than 2 October 2024. 

Further information: For more information, please contact the PhD Administration (phd@hrsc.ku.dk) or the course organiser.

Literature:
Howell, David C. Fundamental Statistics for the Behavioral Sciences. Ninth edition, student edition. Boston, MA: Cengage Learning, 2016.
Akinkunmi, Mustapha, and Steven G Krantz. Introduction to Statistics Using R. 1st ed. Vol. 11. San Rafael: Morgan & Claypool Publishers, 2019.
Loftus, Stephen C. Basic Statistics with R: Reaching Decisions with Data. Academic Press, 2021.
Kronthaler, Franz, and Silke Zöllner. Data Analysis with RStudio. Springer: Berlin/Heidelberg, Germany, 2021.
Elbro, C., & Poulsen, M. (2015). Hold i virkeligheden. Statistik og evidens i uddannelse. København: Hans Reitzels forlag.

Disclaimer:
DDSA has explicit permission from Arcanic and the owners of the https://phdcourses.dk/ website to display the courses on ddsa.dk.