About this Book

Here you are going to get an overview of the field of big data, with a focus on the statistical methods used. It also provides a look at several key applications of big data. Big data is a broad topic; it includes quantitative subjects such as math, statistics, computer science, and data science. Big data also covers many applications, such as weather forecasting, financial modeling, political polling methods, and so forth.

The intentions behind this project is specifically included in the following: Provide an overview of the field of big data.

Introduce many useful applications of big data. Show how data may be organized and checked for bad or missing information.

Show how to handle outliers in a dataset. Explain how to identify assumptions that are made when analyzing data.

Provide a detailed explanation of how data may be analyzed with graphical techniques. Cover several key univariate (involving only one variable) statistical techniques for analyzing data.

Explain widely used multivariate (involving more than one variable) statistical techniques. Provide an overview of modeling techniques such as regression analysis. Explain the techniques that are commonly used to analyze time series data. Cover techniques used to forecast the future values of a dataset.

Provide a brief overview of software packages and how they can be used to analyze statistical data. Because this is focussed to people who has little or no idea about Statistics in general, the chapters are written so you can pick and choose whichever topics that interest you the most and dive right in.

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