Peter Bruce

Andrew Bruce

Peter Gedeck

Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this practical guide--now including examples in Python as well as R--explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data scientists use statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages, and have had some exposure to statistics but want to learn more, this quick reference bridges the gap in an accessible, readable format. With this updated edition, you'll dive into: Exploratory data analysis Data and sampling distributions Statistical experiments and significance testing Regression and prediction Classification Statistical machine learning Unsupervised learning

50+ Essential Concepts Using R and Python

Practical Statistics for Data Scientists

Bri Bruce, Of

A key component of data science is statistics and machine learning, but only a small proportion of data scientists are actually trained as statisticians. This concise guide illustrates how to apply statistical concepts essential to data science, with advice on how to avoid their misuse. Many courses and books teach basic statistics, but rarely from a data science perspective. And while many data science resources incorporate statistical methods, they typically lack a deep statistical perspective. This quick reference book bridges that gap in an accessible, readable format.

50 Essential Concepts

Statistics for Data Scientists

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data

Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher-quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that "learn" from data Unsupervised learning methods for extracting meaning from unlabeled data

Ken Langdon

It is a fact of business life that most managers are promoted into their first management job with hardly any training. And if they get promoted again, guess what? The same thing happens again. Managers are basically expected to work out how to do a new job by reacting to the pressures the role puts on them. They can ask questions to begin with, of course, but by the time they have been in post for a while they find it difficult to reveal their ignorance or lack of skills to other people.So, they look for a book that:? * Is a one-stop shop, they don't want to buy a book covering each individual aspect of their work, they want it in one place * Is not too academic or clever, you don't need Drucker on Globalisation when you are trying to make a decision whether or not to hire someone in the Paris office * Gives hard practical advice built on experience rather than management theory * Works * Is accessible and easy to use * Is simple and practical to implement tomorrow! 100 Business FAQ's is just that book. It gives step-by-step solutions to sensible questions such as, 'What exactly is in a strategic plan?' and 'How do you do risk assessment?'This book is not a once-only read, it will become your business bible - to be used in anger from day one and referred to throughout the rest of your careerThe book also gives practical answers to important questions such as 'How do I gain influence with my boss's boss without annoying my boss?' Answer:First make sure that your boss thinks that other people believe that your good ideas are his. Then make sure that your boss's boss knows that both your good ideas and your boss's good ideas are really yours. Remember that success has many parents while failure is an orphan.

Answers to the 100 Most Difficult Business Questions of All Time

Business FAQs

This is the direct expulsion of an emotional, physical and mental journey through pornography addiction. If you are a Christian seeking freedom from pornography addiction, it is my hope that this book may find you. Perhaps this book can offer something on your journey of faith in Christ Jesus. Jesus can lead you to freedom.

Andrew Bruce

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