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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/statistical-analysis-hypothesis-testing-sas
课程评论：没有评论
课程名称：统计分析导论：假设检验 课程概述：该初级课程针对使用SAS软件进行统计分析的用户，重点讲解t检验、方差分析（ANOVA）和线性回归，并简要介绍逻辑回归。 课程大纲： 1. **课程概述与数据准备**： - 在本模块中，你将了解课程内容及所分析的数据，并进行必要的数据设置，以便进行课程中的实践。 2. **概念介绍与复习**： - 本模块将帮助你学习不同类型数据分析所需的模型，以及解释性建模与预测性建模之间的差异。你还将复习一些基本的统计概念，如均值的抽样分布、假设检验、p值和置信区间。在此基础上，将应用单样本和双样本t检验对数据进行分析，以验证或否定先前的假设。 3. **ANOVA与回归分析**： - 在本模块中，你将学会使用图形工具来确定哪些预测变量可能有效或无效。接着，通过相关分析来增强这些图形探索，描述潜在预测变量与响应变量之间的线性关系。确定潜在的预测变量后，利用ANOVA和回归分析评估响应变量与预测变量之间关系的质量。 4. **更复杂的线性模型**： - 本模块将一维ANOVA模型扩展到双因素方差分析，并将简单线性回归扩展到含有两个预测变量的多元回归。了解双向ANOVA和具有两个预测变量的多元线性回归的概念后，你将掌握适合和解释多变量模型的技能。
Name:Course Overview and Data Setup
Description:In this module you learn about the course and the data you analyze in this course. Then you set up the data you need to do the practices in the course.
Name:Introduction and Review of Concepts
Description:In this module you learn about the models required to analyze different types of data and the difference between explanatory vs predictive modeling. Then you review fundamental statistical concepts, such as the sampling distribution of a mean, hypothesis testing, p-values, and confidence intervals. After reviewing these concepts, you apply one-sample and two-sample t tests to data to confirm or reject preconceived hypotheses.
Name:ANOVA and Regression
Description:In this module you learn to use graphical tools that can help determine which predictors are likely or unlikely to be useful. Then you learn to augment these graphical explorations with correlation analyses that describe linear relationships between potential predictors and our response variable. After you determine potential predictors, tools like ANOVA and regression help you assess the quality of the relationship between the response and predictors.
Name:More Complex Linear Models
Description:In this module you expand the one-way ANOVA model to a two-factor analysis of variance and then extend simple linear regression to multiple regression with two predictors. After you understand the concepts of two-way ANOVA and multiple linear regression with two predictors, you'll have the skills to fit and interpret models with many variables.
This introductory course is for SAS software users who perform statistical analyses using SAS/STAT software. The focus is on t tests, ANOVA, and linear regression, and includes a brief introduction to logistic regression.
