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Basic Statistics and Data Mining for Data Science

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Basic Statistics and Data Mining for Data Science
Basic Statistics and Data Mining for Data Science
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 3 Hours | 1.31 GB
Genre: eLearning | Language: English

Data science is an ever-evolving field, with exponentially growing popularity. Data science includes techniques and theories extracted from the fields of statistics, computer science, and most importantly machine learning, databases, and visualization.

This video course consists of step-by-step introductions to analyze data and the basics of statistics. The first chapter focuses on the steps to analyze data and which summary statistics are relevant given the type of data you are summarizing. The second chapter continues by focusing on summarizing individual variables and specifically some of the reasons users need to summarize variables. This chapter also illustrates several procedures, such as how to run and interpret frequencies and how to create various graphs. The third chapter introduces the idea of inferential statistics, probability, and hypothesis testing.

The rest of the chapters show you how to perform and interpret the results of basic statistical analyses (chi-square, independent and paired sample t-tests, one-way ANOVA, post-hoc tests, and bivariate correlations) and graphical displays (clustered bar charts, error bar charts, and scatterplots). You will also learn when to use different statistical techniques, how to set up different analyses, and how to interpret the results.

Basic Statistics and Data Mining for Data Science

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网友最新评论 (2)

  1. 您们是怎么找到收集这些资料的,真希望成为这样的资料收集专业户。 😛
    fireghost20008个月前 (12-13)
  2. 基础统计学和用于数据科学的数据挖掘 数据科学是一个不断在进化的领域,有着爆炸性的增长流行度。数据科学包含着从统计学、计算机科学和最重要的机器学习、数据库以及可视化领域中所提炼的技术和理论。 本教程包含了一步步的分析数据和基本统计学的指导。第一章主要是分析数据以及哪种统计类型与要分析的数据相关;第二章继续集中于归纳个别变量以及针对一些用户需要归纳变量的原因。本章还会讲到几种过程,诸如如何运行和解析频度和如何创建各种图。第三章会讲到推论统计、概率和假设测试。 其余的章节会为你讲解如何执行和解释基本的统计分析的结果以及图像分析。你还会学习到何时使用不同的统计技术,如何建立不同的分析以及如何解释这些结果。
    wilde(特殊组-翻译)8个月前 (12-12)