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New PDF release: Practical Statistics for Data Scientists: 50 Essential

By Peter Bruce

ISBN-10: 1491952962

ISBN-13: 9781491952962

A key component to facts technological know-how is information and computer studying, yet just a small percentage of information scientists are literally informed as statisticians. This concise consultant illustrates the way to practice statistical thoughts necessary to facts technology, with recommendation on easy methods to keep away from their misuse.

Many classes and books educate uncomplicated facts, yet hardly ever from a knowledge technology viewpoint. And whereas many facts technology assets comprise statistical equipment, they often lack a deep statistical point of view. This quickly reference e-book bridges that hole in an available, readable format.

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Additional info for Practical Statistics for Data Scientists: 50 Essential Concepts

Example text

Numeric data comes in two forms: continuous, such as wind speed or time duration, and discrete, such as the count of the occurence of an event. Categorical data takes only a fixed set of values, such as a type of TV screen (plasma, LCD, LED, 舰) or a state name (Alabama, Alaska, 舰). Binary data is an important special case of categorical data that takes on only one of two values, such as 0/1, yes/no or true/false. Another useful type of categorical data is ordinal data in which the categories are ordered; an example of this is a numerical rating (1, 2, 3, 4, or 5).

Synonyms case, example, instance, observation, pattern, sample Retangular data is essentially a 2-dimensional matrix with rows indicating records (cases) and columns indicating features (variables). g. text) must be processed and manipulated so that it can be represented as a set of features in the rectangular data (see 舠Elements of Structured Data舡). Data that are in relational databases must be extracted and put into a single table for most data analysis and modeling tasks. g. g. category and currency).

This is taken from data provided by Lending Club, a leader in the peer-to-peer lending business (provide reference here). The grade goes from A (high) to G (low). The outcome is either paid off, current, late or charged off (the balance of the loan is not expected to be collected). This table shows the count and row percentages. High grade loans have a very low late/charge-off percentage as compared with lower grade loans. Contingency tables can look at just counts, or also include column and total precentages.

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Practical Statistics for Data Scientists: 50 Essential Concepts by Peter Bruce


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