Probability and Statistics
( 25 Modules )

Module #1
Introduction to Probability and Statistics
Overview of the importance and applications of probability and statistics in real-world scenarios

Module #2
Basic Concepts of Probability
Understanding probability, sample spaces, events, and the concept of randomness

Module #3
Types of Probability
Exploring theoretical, experimental, and subjective probability

Module #4
Rules of Probability
Learning the addition, multiplication, and complement rules of probability

Module #5
Conditional Probability
Understanding conditional probability, independence, and Bayes theorem

Module #6
Random Variables
Introduction to discrete and continuous random variables

Module #7
Probability Distributions
Exploring Bernoulli, Binomial, Poisson, and Uniform distributions

Module #8
Normal Distribution
Understanding the normal distribution, its properties, and applications

Module #9
Statistical Measures
Calculating mean, median, mode, variance, and standard deviation

Module #10
Data Visualization
Understanding the importance of data visualization and different types of plots

Module #11
Descriptive Statistics
Summarizing and describing data using statistics and data visualization

Module #12
Inferential Statistics
Introduction to making inferences about populations based on sample data

Module #13
Sampling Distributions
Understanding sampling distributions and the central limit theorem

Module #14
Hypothesis Testing
Formulating and testing hypotheses using statistical methods

Module #15
Confidence Intervals
Constructing and interpreting confidence intervals for population parameters

Module #16
Regression Analysis
Introduction to simple and multiple linear regression

Module #17
Correlation Analysis
Understanding correlation coefficients and their interpretation

Module #18
Chi-Square Tests
Using chi-square tests for goodness of fit and independence

Module #19
Non-Parametric Tests
Introduction to non-parametric tests for nominal and ordinal data

Module #20
ANOVA and F-Tests
Using ANOVA and F-tests for comparing means and variances

Module #21
Experimental Design
Designing experiments and understanding blocking, randomization, and replication

Module #22
Survey Research Methods
Understanding survey research methods, including questionnaire design and sampling

Module #23
Big Data and Data Mining
Introduction to big data and data mining techniques

Module #24
R and Python for Probability and Statistics
Using R and Python for probability and statistical analysis

Module #25
Course Wrap-Up & Conclusion
Planning next steps in Probability and Statistics career

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Probability and Statistics ( 25 Modules )

Probability and Statistics
( 25 Modules )