Introduction to Statistics: Analyzing Data
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The sub-discipline of mathematics which is concerned with the collection, interpretation and analysis of data is known as statistics. It is further classified into two sub-branches namely, descriptive statistics and inferential statistics. Descriptive statistics is a form of non-parametric statistics. It makes use of various tools such as measures of central tendency including mean, median, mode, and measures of dispersion. Kurtosis and skewness are also studied within the domain of this subject. Inferential statistics applies the principles underlying distribution of probability. Different ty...
The sub-discipline of mathematics which is concerned with the collection, interpretation and analysis of data is known as statistics. It is further classified into two sub-branches namely, descriptive statistics and inferential statistics. Descriptive statistics is a form of non-parametric statistics. It makes use of various tools such as measures of central tendency including mean, median, mode, and measures of dispersion. Kurtosis and skewness are also studied within the domain of this subject. Inferential statistics applies the principles underlying distribution of probability. Different types of assumption models studied under this discipline are classified into fully parametric, no-parametric and semi-parametric. Statistics finds extensive application in the fields of computer science, economics, biology, machine learning and data mining. This book provides significant information of this discipline to help develop a good understanding of statistics and related fields. It is compiled in such a manner, that it will provide in-depth knowledge about the theory and practice of this field. Coherent flow of topics, student-friendly language and extensive use of examples make this book an invaluable source of knowledge.
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