Statistical Inference

开始时间: 03/28/2020 持续时间: Unknown

所在平台: Coursera

课程类别: 计算机科学

大学或机构: CourseraNew

   

课程主页: https://www.coursera.org/learn/statistical-inference

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Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance. This course presents the fundamentals of inference in a practical approach for getting things done. After taking this course, students will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data.

统计推断:统计推断是从数据得出有关种群或科学真理的结论的过程。执行推理的方式有很多,包括统计建模,面向数据的策略以及设计的明确使用和分析中的随机化。此外,有广泛的理论(常识,贝叶斯,似然,基于设计等)和众多复杂性(缺少数据,观察到的和未观察到的混杂,偏见)来进行推理。从业人员常常会陷入使技术,哲学和细微差别令人失望的迷宫中。本课程以一种实用的方法介绍推理的基础,以帮助您完成工作。学习完本课程后,学生将了解统计推断的广泛方向,并使用此信息在分析数据时做出明智的选择。

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课程简介

Statistical inference is the process of drawing conclusions about populations or scientific truths f

课程标签

数据科学专项 数据科学 统计 统计推断 数据分析

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