Course Summary
This course covers the fundamentals of statistics, including descriptive statistics, probability, hypothesis testing, and regression analysis. It is an essential course for any student or professional who needs to work with data.Key Learning Points
- Learn the basics of statistics, including concepts like probability and hypothesis testing
- Understand how to use regression analysis to analyze data
- Apply statistical concepts to real-world problems
Job Positions & Salaries of people who have taken this course might have
- USA: $60,000 - $100,000
- India: ₹400,000 - ₹1,000,000
- Spain: €24,000 - €50,000
- USA: $60,000 - $100,000
- India: ₹400,000 - ₹1,000,000
- Spain: €24,000 - €50,000
- USA: $70,000 - $120,000
- India: ₹500,000 - ₹1,200,000
- Spain: €30,000 - €60,000
- USA: $60,000 - $100,000
- India: ₹400,000 - ₹1,000,000
- Spain: €24,000 - €50,000
- USA: $70,000 - $120,000
- India: ₹500,000 - ₹1,200,000
- Spain: €30,000 - €60,000
- USA: $50,000 - $90,000
- India: ₹300,000 - ₹800,000
- Spain: €20,000 - €40,000
Related Topics for further study
Learning Outcomes
- Understand basic statistical concepts and methods
- Apply statistical methods to analyze data
- Interpret statistical results and draw conclusions
Prerequisites or good to have knowledge before taking this course
- Basic math skills
- Familiarity with spreadsheets (e.g. Excel)
Course Difficulty Level
BeginnerCourse Format
- Online
- Self-paced
Similar Courses
- Introduction to Data Science
- Data Analysis and Interpretation
Related Education Paths
Notable People in This Field
- Nate Silver
- Hans Rosling
Related Books
Description
Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This course will also prepare you for the next course in the specialization - the course Inferential Statistics.
Outline
- Before we get started...
- Welcome to Basic Statistics!
- Hi there!
- How to navigate this course
- How to contribute
- General info - What will I learn in this course?
- Course format - How is this course structured?
- Requirements - What resources do I need?
- Grading - How do I pass this course?
- Team - Who created this course?
- Honor Code - Integrity in this course
- Useful literature and documents
- Research on Feedback
- Use of your data for research
- Exploring Data
- 1.01 Cases, variables and levels of measurement
- 1.02 Data matrix and frequency table
- 1.03 Graphs and shapes of distributions
- 1.04 Mode, median and mean
- 1.05 Range, interquartile range and box plot
- 1.06 Variance and standard deviation
- 1.07 Z-scores
- 1.08 Example
- Data and visualisation
- Measures of central tendency and dispersion
- Z-scores and example
- Transcripts - Exploring data
- About the R labs
- Exploring Data
- Correlation and Regression
- 2.01 Crosstabs and scatterplots
- 2.02 Pearson's r
- 2.03 Regression - Finding the line
- 2.04 Regression - Describing the line
- 2.05 Regression - How good is the line?
- 2.06 Correlation is not causation
- 2.07 Example contingency table
- 2.08 Example Pearson's r and regression
- Correlation
- Regression
- Reference
- Caveats and examples
- Reference
- Transcripts - Correlation and regression
- Correlation and Regression
- Probability
- 3.01 Randomness
- 3.02 Probability
- 3.03 Sample space, event, probability of event and tree diagram
- 3.04 Quantifying probabilities with tree diagram
- 3.05 Basic set-theoretic concepts
- 3.06 Practice with sets
- 3.07 Union
- 3.08 Joint and marginal probabilities
- 3.09 Conditional probability
- 3.10 Independence between random events
- 3.11 More conditional probability, decision trees and Bayes' Law
- Probability & randomness
- Sample space, events & tree diagrams
- Probability & sets
- Conditional probability & independence
- Transcripts - Probability
- Probability
- Probability Distributions
- 4.01 Random variables and probability distributions
- 4.02 Cumulative probability distributions
- 4.03 The mean of a random variable
- 4.04 Variance of a random variable
- 4.05 Functional form of the normal distribution
- 4.06 The normal distribution: probability calculations
- 4.07 The standard normal distribution
- 4.08 The binomial distribution
- Probability distributions
- Mean and variance of a random variable
- The normal distribution
- The binomial distribution
- Transcripts - Probability distributions
- Probability distributions
- Sampling Distributions
- 5.01 Sample and population
- 5.02 Sampling
- 5.03 The sampling distribution
- 5.04 The central limit theorem
- 5.05 Three distributions
- 5.06 Sampling distribution proportion
- 5.07 Example
- Sample and sampling
- Sampling distribution of sample mean and central limit theorem
- Reference
- Sampling distribution of sample proportion and example
- Transcripts - Sampling distributions
- Sampling distributions
- Confidence Intervals
- 6.01 Statistical inference
- 6.02 CI for mean with known population sd
- 6.03 CI for mean with unknown population sd
- 6.04 CI for proportion
- 6.05 Confidence levels
- 6.06 Choosing the sample size
- 6.07 Example
- Inference and confidence interval for mean
- Confidence interval for proportion and confidence levels
- Sample size and example
- Transcripts - Confidence intervals
- Confidence intervals
- Significance Tests
- 7.01 Hypotheses
- 7.02 Test about proportion
- 7.03 Test about mean
- 7.04 Step-by-step plan
- 7.05 Significance test and confidence interval
- 7.06 Type I and Type II errors
- 7.07 Example
- Hypotheses and significance tests
- Step-by-step plan and confidence interval
- Type I and Type II errors and example
- Transcripts - Significance tests
- Significance tests
- Exam time!
- Final Exam
Summary of User Reviews
Learn Basic Statistics on Coursera and improve your data analysis skills. This course is highly recommended by many users and has received positive feedback. One key aspect that many users thought was good is the clear and concise explanations provided by the instructor.Pros from User Reviews
- Clear and concise explanations provided by the instructor
- Well-organized course materials
- Good pacing and structure of the lectures
- Great for beginners and those looking to refresh their knowledge
Cons from User Reviews
- Some users found the quizzes to be too easy
- Limited interaction with the instructor
- Not enough real-world examples provided
Matthijs Rooduijn
4.6 Raiting
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