Statistics for Data Science and Business Analytics

Master the Fundamentals of Statistics and Bring Your Data Analysis to the Next Level!
Are you looking to lay a strong statistical foundation for data science, analytics, and decision-making? This beginner-to-intermediate level course is designed to simplify even the most complex statistical ideas using practical examples, so you can become confident with data analysis, hypothesis testing, and regression modeling.

What You'll Learn:
Module 1: Introduction to Statistics –
Understand the application of statistics in data science
types of data
major differences between descriptive & inferential statistics.

Module 2: Descriptive Statistics –
Understand measures of central tendency (mean, median, mode)
Measure of dispersion (range, variance, standard deviation)
visualize data using histograms, box plots, and scatter plots.

Module 3: Probability Basics –
Master concepts of probability
conditional probability
Bayes' theorem

Module 4: Probability Distributions –
Understanding Discrete and Continuous Probability distributions
Binomial Distribution
Poisson Distribution
Normal Distribution
Exponential Distribution
Central Limit Theorem(CLT)

Module 5: Inferential Statistics –
Discuss sampling methods
What are confidence intervals
hypothesis testing
Errors of type
t-tests & z-tests
chi-square test understanding

Module 6: Regression & Correlation-
1. Causation and correlation understanding
2. Linear Regression Analysis-coding exercise
3. Understanding the Linear Regression equation
4. Understanding the main summary statistics of Regression
5. Main assumptions and limitations in Simple Linear Regression
6.Multi Linear Regression ( soon to be added)