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所在平台: Udemy |
课程主页: https://www.udemy.com/course/applied-statistics-with-r/
课程评论：没有评论
Coursera 课程：R 语言应用统计及数据处理 **为什么要学习数据分析和数据科学？** * **提升解决问题能力：** 培养分析性思维，为工作和生活提供解决问题的方法。 * **高需求行业：** 数据分析师和数据科学家是热门职业，随着数据应用的普及，需求量将持续增长。 * **数据无处不在：** 各行各业都需要从数据中挖掘洞察，以优化流程。 * **重要性日益增加：** 海量数据为企业决策提供了前所未有的机会，数据分析师的价值和职业前景愈发广阔。 * **技能多元化：** 该领域融合了计算机科学、商业和数学等多个学科，同时要求良好的沟通能力。 **课程内容概述：** 本课程是学习 R 语言应用统计的基础性课程，涵盖了 CRISP-DM 数据挖掘过程中的“数据理解”和“数据准备”阶段。 **主要学习内容：** * **R 语言基础（通过“Create Your Calculator: Learn R Programming Basics Fast”课程学习）** * **数据挖掘流程** * **数据收集与导入** * **描述性统计：** 均值、中位数、众数、极差、四分位数、方差、标准差、正态分布、偏度和峰度等。 * **R 语言统计函数：** `summary()` 和 `str()` 的使用。 * **相关性分析：** 相关系数和协方差。 * **推断性统计检验：** * 单样本 t 检验 * 两样本非配对 t 检验（方差相等与不等） * 两样本配对 t 检验 * 卡方检验 * 单因素方差分析 (ANOVA) * 双因素方差分析 (ANOVA) * 多因素方差分析 (MANOVA) * **回归分析：** * 简单线性回归 * 多元线性回归 * **数据处理技术：** * 变量选择 * 数据排序 * 数据筛选 * 处理缺失值 * 去除重复值 **证书：** 完成本课程并通过 EMHAcademy 的考试，可获得 SVBook Certified Data Miner using the R 证书。 **先修课程推荐：** “Create Your Calculator: Learn R Programming Basics Fast” (R 语言基础) **进一步学习方向：** * “Advanced Data Visualizations using R with Data Processing”（未来新增） * “Machine Learning with R”（建模与评估） **课程参考：** 本课程内容基于作者出版的 Apress 书籍 "Learn R for Applied Statistics"。
Why learn Data Analysis and Data Science?According to SAS, the five reasons are1. Gain problem-solving skillsThe ability to think analytically and approach problems in the right way is a skill that is very useful in the professional world and everyday life. 2. High demandData Analysts and Data Scientists are valuable. With a looming skill shortage as more and more businesses and sectors work on data, the value is going to increase. 3. Analytics is everywhereData is everywhere. All company has data and need to get insights from the data. Many organizations want to capitalize on data to improve their processes. It's a hugely exciting time to start a career in analytics.4. It's only becoming more importantWith the abundance of data available for all of us today, the opportunity to find and get insights from data for companies to make decisions has never been greater. The value of data analysts will go up, creating even better job opportunities. 5. A range of related skillsThe great thing about being an analyst is that the field encompasses many fields such as computer science, business, and maths. Data analysts and Data Scientists also need to know how to communicate complex information to those without expertise.The Internet of Things is Data Science + Engineering. By learning data science, you can also go into the Internet of Things and Smart Cities. This is the bite-size course to learn R Programming for Applied Statistics. In CRISP-DM data mining process, Applied Statistics is at the Data Understanding stage. This course also covers Data processing, which is at the Data Preparation Stage. You will need to know some R programming, and you can learn R programming from my "Create Your Calculator: Learn R Programming Basics Fast" course. You will learn R Programming for applied statistics and you will be able You can take the course as follows, and you can take an exam at EMHAcademy to get SVBook Certified Data Miner using the R certificate: - Create Your Calculator: Learn R Programming Basics Fast (R Basics)- Applied Statistics using R with Data Processing (Data Understanding and Data Preparation)- Advanced Data Visualizations using R with Data Processing (Data Understanding and Data Preparation, in the future)- Machine Learning with R (Modeling and Evaluation)ContentGetting StartedGetting Started 2Getting Started 3Data Mining ProcessDownload Data setRead Data setModeMedianMeanRangeRange 2Range 3IQRQuantilePopulation VarianceSample VarianceVarianceStandard DeviationNormal DistributionSkewness and KurtosisSummary() and Str()CorrelationCovarianceInferential Statistics TestsOne Sample T TestTwo Sample Unpaired T TestTwo Sample Unpaired T-Test (Variance not Equal)Two Sample Paired T TestChi-Square TestOne Way ANOVATwo Way ANOVAMANOVASimple Linear RegressionMultiple Linear RegressionData Processing: Select VariablesData Processing: Sort DataData Processing: Filter DataData Processing: Remove Missing Values and Remove DuplicatesReferences: This course is actually based on the Learn R for Applied Statistics book I have published at Apress.
