Measures of Dispersion
- Offered byGreat Learning
Measures of Dispersion at Great Learning Overview
Measures of Dispersion
at Great Learning
Duration | 1 hour |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course |
Credential | Certificate |
Measures of Dispersion at Great Learning Highlights
Measures of Dispersion
at Great Learning
- Earn a certificate of completion
Gain expertise on widely used skills like Measures of Dispersion, Statistics
Measures of Dispersion at Great Learning Course details
Measures of Dispersion
at Great Learning
What are the course deliverables?
- Measures of Dispersion
- Statistics
More about this course
- In this course, you will acquire skills in Measures of Dispersion
- You will start this course by learning what statistics is and its data collection
- Then we will jump to different types of statistical analysis such as predictive, descriptive and inferential
- Then we will see analytics in excel and descriptive statistics in which you will be knowing about central tendency, dispersion and shape
- Then, moving to next you will know about measures of location such as mean, median and mode
- Lastly, you will be seeing the measures of dispersion by knowing the range of the data, variance and Standard deviation
Measures of Dispersion at Great Learning Curriculum
Measures of Dispersion
at Great Learning
Descriptive statistics
Measures of Dispersion
Introduction to Statistics
What is Statistics?
Data Collection for Statistics
Types of Statistical Analysis
Analytics with Excel
Measures of Location
Variance and Standard Deviation
Measures of Dispersion at Great Learning Faculty details
Measures of Dispersion
at Great Learning
Dr. Abhinanda Sarkar
Designation : Faculty Director, Great Learning
Description : Dr. Abhinanda Sarkar is the Academic Director at Great Learning for Data Science and Machine Learning Programs. Dr. Sarkar received his B.Stat. and M.Stat. degrees from the Indian Statistical Institute (ISI) and a Ph.D. in Statistics from Stanford University. He has taught applied mathematics at the Massachusetts Institute of Technology (MIT); been on the research staff at IBM; led Quality, Engineering Development, and Analytics functions at General Electric (GE); served as Associate Dean at the MYRA School of Business; and co-founded OmiX Labs.
Dr. Sarkar’s publications, patents, and technical leadership have been in applying probabilistic models, statistical data analysis, and machine learning to diverse areas such as experimental physics, computer vision, text mining, wireless networks, e-commerce, credit risk, retail finance, engineering reliability, renewable energy, and infectious diseases, His teaching has mostly been on statistical theory, methods, and algorithms; together with application topics such as financial modeling, quality management, and data mining.
Dr. Sarkar is a certified Master Black Belt in Lean Six Sigma and Design for Six Sigma. He has been visiting faculty at Stanford and ISI and continues to teach at the Indian Institute of Management (IIM-Bangalore) and the Indian Institute of Science (IISc). Over the years, he has designed and conducted numerous corporate training sessions for
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