I’ve gotten an enormous amount of positive feedback on the first chapter of my PDF, so I’ve decided to share the second chapter. This chapter is all about statistical inference for data science, and as you’ll see it’s all about how to do statistics on data once you’ve applied your machine learning algorithm. It talks all about common methods of statistical inference like confidence intervals, p-values, t-tests, and chi-square tests, then it shows you how to apply this information in R using some easy examples.
We are living in the era of big data. While businesses accumulate huge amounts of data, they strive to understand the statistical inference techniques that effectively extract relevant information out of it. Statistical Inference for Data Science with Python is an ideal guide for those who want to use Python for statistical inference. Only basic knowledge of Python and statistics is required to get started with this book.
statistical inference pdf
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- Cambridge University Press
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- CRC Press
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Release Date | 2019-01-24T00:00:01Z |
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