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. 26 hours to complete

English

Subtitles: English, German

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. 26 hours to complete

English

Subtitles: English, German

Offered by

University of Amsterdam logo

University of Amsterdam

Syllabus - What you will learn from this course

Content RatingThumbs Up96%(37,474 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 research2m
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 Data22m
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 Regression20m
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

About the Methods and Statistics in Social Sciences Specialization

Identify interesting questions, analyze data sets, and correctly interpret results to make solid, evidence-based decisions. This Specialization covers research methods, design and statistical analysis for social science research questions. In the final Capstone Project, you’ll apply the skills you learned by developing your own research question, gathering data, and analyzing and reporting on the results using statistical methods....
Methods and Statistics in Social Sciences

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

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