About this Course

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Learner Career Outcomes

41%

started a new career after completing these courses

30%

got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Beginner Level
Approx. 27 hours to complete
English

Skills you will gain

StatisticsConfidence IntervalStatistical Hypothesis TestingR Programming

Learner Career Outcomes

41%

started a new career after completing these courses

30%

got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Beginner Level
Approx. 27 hours to complete
English

Offered by

Placeholder

University of Amsterdam

Syllabus - What you will learn from this course

Content RatingThumbs Up96%(41,589 ratings)Info
Week
1

Week 1

2 hours to complete

Before we get started...

2 hours to complete
1 video (Total 4 min), 11 readings, 1 quiz
11 readings
Hi there!10m
How to navigate this course10m
How to contribute10m
General info - What will I learn in this course?10m
Course format - How is this course structured?10m
Requirements - What resources do I need?10m
Grading - How do I pass this course?10m
Team - Who created this course?10m
Honor Code - Integrity in this course10m
Useful literature and documents10m
Research on Feedback10m
1 practice exercise
Use of your data for research30m
5 hours to complete

Exploring Data

5 hours to complete
8 videos (Total 53 min), 5 readings, 4 quizzes
8 videos
1.02 Data matrix and frequency table6m
1.03 Graphs and shapes of distributions7m
1.04 Mode, median and mean6m
1.05 Range, interquartile range and box plot7m
1.06 Variance and standard deviation5m
1.07 Z-scores4m
1.08 Example6m
5 readings
Data and visualisation10m
Measures of central tendency and dispersion10m
Z-scores and example10m
Transcripts - Exploring data10m
About the R labs10m
1 practice exercise
Exploring Data30m
Week
2

Week 2

3 hours to complete

Correlation and Regression

3 hours to complete
8 videos (Total 49 min), 6 readings, 2 quizzes
8 videos
2.02 Pearson's r7m
2.03 Regression - Finding the line3m
2.04 Regression - Describing the line7m
2.05 Regression - How good is the line?5m
2.06 Correlation is not causation5m
2.07 Example contingency table3m
2.08 Example Pearson's r and regression8m
6 readings
Correlation10m
Regression10m
Reference10m
Caveats and examples10m
Reference10m
Transcripts - Correlation and regression10m
1 practice exercise
Correlation and Regression30m
Week
3

Week 3

3 hours to complete

Probability

3 hours to complete
11 videos (Total 64 min), 5 readings, 2 quizzes
11 videos
3.02 Probability4m
3.03 Sample space, event, probability of event and tree diagram5m
3.04 Quantifying probabilities with tree diagram5m
3.05 Basic set-theoretic concepts5m
3.06 Practice with sets7m
3.07 Union5m
3.08 Joint and marginal probabilities6m
3.09 Conditional probability4m
3.10 Independence between random events5m
3.11 More conditional probability, decision trees and Bayes' Law8m
5 readings
Probability & randomness10m
Sample space, events & tree diagrams10m
Probability & sets10m
Conditional probability & independence10m
Transcripts - Probability10m
1 practice exercise
Probability30m
Week
4

Week 4

3 hours to complete

Probability Distributions

3 hours to complete
8 videos (Total 52 min), 5 readings, 2 quizzes
8 videos
4.02 Cumulative probability distributions5m
4.03 The mean of a random variable4m
4.04 Variance of a random variable6m
4.05 Functional form of the normal distribution6m
4.06 The normal distribution: probability calculations5m
4.07 The standard normal distribution8m
4.08 The binomial distribution8m
5 readings
Probability distributions10m
Mean and variance of a random variable10m
The normal distribution10m
The binomial distribution10m
Transcripts - Probability distributions10m
1 practice exercise
Probability distributions30m

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About the Methods and Statistics in Social Sciences Specialization

Methods and Statistics in Social Sciences

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