Basic Statistics by Coursera
Skills you will learn!
Curriculum
13 Topics
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
17 Topics
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
R lab - Exploring data
R lab - Getting started (part 1)
R lab - Getting started (part 2)
16 Topics
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
R lab - Correlation and Regression
18 Topics
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
R lab - Probability
15 Topics
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
R lab - Probability distributions
14 Topics
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
R lab - Sampling distributions
13 Topics
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
R lab - Confidence intervals
13 Topics
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
R lab - Significance tests
1 Topic
Final Exam
Basic Statistics
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