Course Overview: This comprehensive course offers an in-depth introduction to the fundamental concepts of probability and statistics. Designed for learners seeking to build a strong foundation in these subjects, the course covers essential topics such as descriptive statistics, probability distributions, sampling methods, estimation techniques, and regression analysis. Through a series of 13 engaging video lectures, students will gain the knowledge and skills necessary to apply statistical methods to real-world problems.
Course Outline:
- Introduction to Statistics
- Understanding the role of statistics in various fields
- Differentiating between descriptive and inferential statistics
- Exploring types of data and measurement scales
- Descriptive Statistics
- Summarizing and visualizing data using graphs and charts
- Calculating measures of central tendency (mean, median, mode)
- Assessing data dispersion with range, variance, and standard deviation
- Probability Fundamentals
- Defining probability and its axioms
- Exploring sample spaces and events
- Applying conditional probability and Bayes' theorem
- Discrete Probability Distributions
- Understanding random variables and probability mass functions
- Examining binomial, Poisson, and geometric distributions
- Calculating expected values and variances
- Continuous Probability Distributions
- Introducing probability density functions
- Analyzing normal, exponential, and uniform distributions
- Applying the Central Limit Theorem
- Sampling and Estimation
- Discussing sampling methods and techniques
- Constructing confidence intervals for population parameters
- Understanding the concepts of point and interval estimation
- Regression Analysis
- Introduction to regression models
- Conducting simple linear regression analysis
- Assessing the goodness-of-fit and making predictions
Prerequisites of This Course
-
Basic Calculus.
-
Basic Permutation Combination
