Statistics and Mathematics for Analytics involves the study of statistical methods and mathematical concepts used in data analysis, interpretation, and modeling within the field of analytics. It includes a range of mathematical and statistical techniques applied to extract meaningful insights from data, make predictions, and aid in decision-making.

** Note:** Please note that the course comes with online e-learning (videos) only. No hard copy will be provided.

Statistical and mathematical models form the foundation of predictive analytics, enabling organizations to forecast trends, behaviors, and outcomes. Proficiency in mathematics and statistics is crucial for developing and improving machine learning algorithms and AI models.

Vskills Certificate in Statistics and Mathematics for Analytics provides a hands-on approach to understand the nuances of statistics and mathematics for analytics.

Data Analysts, Data Scientists, Business Analysts and Decision-Makers will benefit immensely by opting for Vskills Certificate in Statistics and Mathematics for Analytics to gain an edge in the Statistics and Mathematics for Analytics and be noticeable amongst their colleagues as well as make progress in their respective careers.

Students taking the certification also gain by showcasing their understanding of Statistics and Mathematics for Analytics and are able to increase their job opportunities.

https://www.vskills.in/certification/statistics-and-mathematics-for-analytics-certification-table-of-contents

https://www.vskills.in/practice/statistics-and-mathematics-for-analytics-practice-questions

https://www.vskills.in/interview-questions/statistics-and-mathematics-for-analytics-interview-questions

Consulting firms, financial institutions, tech companies and startups are constantly hiring skilled professionals in statistics and mathematics for analytics. IT companies, MNCs hire Statistics and Mathematics for Analytics professionals for analytics testing related tasks. Companies employing Statistics and Mathematics for Analytics professionals include Google, TCS, Accenture, IBM, Tech Mahindra, GE, Amex, Deloitte, Wipro, etc.

**Statistics and Mathematics for Analytics Related Blogs**

Checkout the latest online blogs on Statistics and Mathematics for Analytics Professional.

**Statistics and Mathematics for Analytics Jobs**

Checkout the various job openings for Statistics and Mathematics for Analytics Professional, click here..

**Statistics and Mathematics for Analytics Internships**

Vskills runs its flagship internship program where bright interns work with academic council, click to know more details..

We accept Visa/Master/Amex cards and all Indian Banks Debit Cards. There is no need to fill the application form in case you are paying online.

Please click **Buy Now** to proceed with online payments.

- Welcome!
- What Will You Learn in This Course?
- How Can You Get the Most Out of It?

- Introduction
- Mean
- Median
- Mode
- Mean or Median?
- Skewness
- Practice: Skewness
- Solution: Skewness
- Range and IQR
- Sample Versus Population
- Variance and Standard Deviation
- Impact of Scaling and Shifting
- Statistical Moments

- What Is Distribution?
- Normal Distribution
- Z-Scores
- Practice: Normal Distribution
- Solution: Normal Distribution

- Introduction
- Probability Basics
- Calculating Simple Probabilities
- Practice: Simple Probabilities
- Quick Solution: Simple Probabilities
- Detailed Solution: Simple Probabilities
- Rule of Addition
- Practice: Rule of Addition
- Quick Solution: Rule of Addition
- Detailed Solution: Rule of Addition
- Rule of Multiplication
- Practice: Rule of Multiplication
- Solution: Rule of Multiplication
- Bayes Theorem
- Bayes Theorem - Practical Example
- Expected Value
- Practice: Expected Value
- Solution: Expected Value
- Law of Large Numbers
- Central Limit Theorem - Theory
- Central Limit Theorem - Intuition
- Central Limit Theorem - Challenge
- Central Limit Theorem - Exercise
- Central Limit Theorem - Solution
- Binomial Distribution
- Poisson Distribution
- Real-Life Problems

- Introduction
- What Is a Hypothesis?
- Significance Level and P-Value
- Type I and Type II Errors
- Confidence Intervals and Margin of Error
- Excursion: Calculating Sample Size and Power
- Performing the Hypothesis Test
- Practice: Hypothesis Test
- Solution: Hypothesis Test
- t-test and t-distribution
- Proportion Testing
- Important p-z Pairs

- Introduction
- Linear Regression
- Correlation Coefficient
- Practice: Correlation
- Solution: Correlation
- Practice: Linear Regression
- Solution: Linear Regression
- Residual, MSE, and MAE
- Practice: MSE and MAE
- Solution: MSE and MAE
- Coefficient of Determination
- Root Mean Square Error
- Practice: RMSE
- Solution: RMSE

- Multiple Linear Regression
- Overfitting
- Polynomial Regression
- Logistic Regression
- Decision Trees
- Regression Trees
- Random Forests
- Dealing with Missing Data

- ANOVA - Basics and Assumptions
- One-Way ANOVA
- F-Distribution
- Two-Way ANOVA – Sum of Squares
- Two-Way ANOVA – F-Ratio and Conclusions