Mark D. Ward

 

 


 

Mark is an Associate Professor, and Undergraduate Chair at Department of Statistics, Purdue University, and Associate Director for the NSF Center for Science of Information. He received his Ph.D. in Mathematics from Purdue in 2005. Professor Ward has received numerous teaching and research awards, and is a Fellow of the Purdue University Teaching Academy. He is co-author of Introduction to Probability (W.H. Freeman, 2015)

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Oct 10th 2016

Learn about probability distribution models, including normal distribution, and continuous random variables to prepare for a career in information and data science. In this statistics and data analysis course, you will learn about continuous random variables and some of the most frequently used probability distribution models including, exponential distribution, Gamma distribution, Beta distribution, and most importantly, normal distribution.

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Learn fundamental concepts of mathematical probability to prepare for a career in the growing field of information and data science. Our capacity to collect and store data has exponentially increased, but deriving information from data from a scientific perspective requires a foundational knowledge of probability. Are you interested in a career in the emerging data science field, or as an actuarial scientist? Or want better to understand statistical theory and mathematical modeling?

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