Statistics and data visualisation with Python /
Rogel-Salazar, Jesus,
Statistics and data visualisation with Python / Jes�us Rogel-Salazar. - First edition. - 1 online resource (xxxviii, 515 pages) : illustrations. - Chapman & Hall/CRC Press the python series . - Chapman & Hall/CRC Press the python series .
"A Chpaman & Hall book" -- title page.
1. Data, Stats and Stories - An Introduction 2. Python Programming Primer 3. Snakes, Bears & Other Numerical Beasts: NumPy, SciPy & Pandas4. The Measure of All Things - Statistics 5. Definitely Maybe: Probability and Distributions 6. Alluring Arguments and Ugly Facts - Statistical Modelling and Hypothesis Testing 7. Delightful Details - Data Visualisation8. Dazzling Data Designs - Creating ChartsA. Variance: Population v SampleB. Sum of First n IntegersC. Sum of Squares of the First n IntegersD. The Binomial CoefficientE. The Hypergeometric DistributionF. The Poisson DistributionG. The Normal DistributionH. Skewness and KurtosisI. Kruskal-Wallis Test - No Ties
"This book is intended to serve as a bridge in statistics for graduates and business practitioners interested in using their skills in the area of data science and analytics as well as statistical analysis in general. On the one hand, the book is intended to be a refresher for readers that have taken some courses in statistics, but who have not necessarily used it in their day-to-day work. On the other hand, the material can be suitable for readers interested in the subject as a first encounter with statistical work in Python. Statistics and Data Visualisation with Python aims to build statistical knowledge from the ground up by enabling the reader to understand the ideas behind inferential statistics, and begin to formulate hypotheses that form the foundations for the applications and algorithms in statistical analysis, business analytics, machine learning and applied machine learning. This book begins with the basics of programming in Python and data analysis, to help construct a solid basis in statistical methods and hypothesis testing, which are useful in many modern applications"--
9781003160359 1003160352 9781000798388 1000798380 9781000798401 1000798402
10.1201/9781003160359 doi
Mathematical statistics--Data processing.
Python (Computer program language)
Information visualization.
QA276.45.P98 / R64 2023
519.50285/5133
Statistics and data visualisation with Python / Jes�us Rogel-Salazar. - First edition. - 1 online resource (xxxviii, 515 pages) : illustrations. - Chapman & Hall/CRC Press the python series . - Chapman & Hall/CRC Press the python series .
"A Chpaman & Hall book" -- title page.
1. Data, Stats and Stories - An Introduction 2. Python Programming Primer 3. Snakes, Bears & Other Numerical Beasts: NumPy, SciPy & Pandas4. The Measure of All Things - Statistics 5. Definitely Maybe: Probability and Distributions 6. Alluring Arguments and Ugly Facts - Statistical Modelling and Hypothesis Testing 7. Delightful Details - Data Visualisation8. Dazzling Data Designs - Creating ChartsA. Variance: Population v SampleB. Sum of First n IntegersC. Sum of Squares of the First n IntegersD. The Binomial CoefficientE. The Hypergeometric DistributionF. The Poisson DistributionG. The Normal DistributionH. Skewness and KurtosisI. Kruskal-Wallis Test - No Ties
"This book is intended to serve as a bridge in statistics for graduates and business practitioners interested in using their skills in the area of data science and analytics as well as statistical analysis in general. On the one hand, the book is intended to be a refresher for readers that have taken some courses in statistics, but who have not necessarily used it in their day-to-day work. On the other hand, the material can be suitable for readers interested in the subject as a first encounter with statistical work in Python. Statistics and Data Visualisation with Python aims to build statistical knowledge from the ground up by enabling the reader to understand the ideas behind inferential statistics, and begin to formulate hypotheses that form the foundations for the applications and algorithms in statistical analysis, business analytics, machine learning and applied machine learning. This book begins with the basics of programming in Python and data analysis, to help construct a solid basis in statistical methods and hypothesis testing, which are useful in many modern applications"--
9781003160359 1003160352 9781000798388 1000798380 9781000798401 1000798402
10.1201/9781003160359 doi
Mathematical statistics--Data processing.
Python (Computer program language)
Information visualization.
QA276.45.P98 / R64 2023
519.50285/5133