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所在平台: Udemy |
课程主页: https://www.udemy.com/course/learn-statistics-biostatistics-data-analysis-from-scratch/
课程评论：没有评论
课程名称：从零开始学习统计学与生物统计学数据分析 课程概述：欢迎参加我们的第四门课程“从零开始学习统计学与生物统计学数据分析”。本课程将从数据的基本概念出发，逐步引导您使用不同的统计工具进行数据分析。在大数据和机器学习主导的时代，统计学是帮助我们理解所收集的大量信息的基石，提供了数据收集、分析、解释和展示的方法论。该课程不仅使您掌握数据语言，还增强了您在商业、科学和技术领域作出明智决策的能力。 您还将学习R编程语言，以便在数据上计算不同的统计指标。R编程是统计学、生物统计学和数据分析领域中最受欢迎的技能之一。凭借其丰富的库和框架，R为数据分析和可视化提供了无与伦比的平台，是统计学家和数据科学家的必备工具。课程将提供R的实践经验，确保您能够在现实场景中有效应用统计方法。 课程共分为八个模块： 1. 数据概述 - 了解数据的基本概念、类型以及如何收集和组织数据。 2. R编程入门 - 深入学习R语言和R-Studio，这是现代数据分析中至关重要的统计计算和图形工具。 3. 描述性统计 - 学习如何总结和描述数值数据的基本特征，进行初步数据探索，并构建数据可视化。 4. 分类数据处理 - 探索有效管理和分析分类变量的技术。 5. 概率 - 理解概率的概念，这是统计推断的基础，涵盖主观概率、经典概率、条件概率等内容。 6. 相关性 - 发现测量两个变量之间关系强度和方向的方法，包括皮尔逊、肯德尔和斯皮尔曼相关系数的解释。 7. 回归分析 - 理解如何建模变量之间的关系并进行预测，学习单变量线性回归、多个线性回归和逻辑回归。 8. 假设检验 - 培养基于数据测试假设和做出决策的能力，学习Z检验、T检验及其类型、F检验、方差分析（ANOVA）及其类型，以及卡方检验及其类型。 本课程是理论与实践的独特结合，您将学习统计概念的理论知识，同时掌握R编程，以运用这些统计概念进行数据分析。希望这一旅程能为您带来启发，完成本课程后，您将能够自信地独立分析数据。
Welcome to our fourth course "Learn Statistics & Biostatistics Data Analysis From Scratch". In this course, you will start from the very fundamentals of Data and slowly move forward to the analysis of the data using different statistical tools. In an era dominated by big data and machine learning, statistics is the cornerstone that allows us to make sense of the vast amounts of information we collect. It provides the methodologies for the collection, analysis, interpretation, and presentation of data. This course not only makes you literate in the language of data but also empowers you to make informed decisions in business, science, and technology.In this course, you will also learn the R-Programming to calculate different statistics on your data. R programming is one of the most sought-after skills in the fields of statistics, biostatistics and data analysis. With its extensive libraries and frameworks, R provides an unparalleled platform for analyzing and visualizing data, making it an indispensable tool for statisticians and data scientists for statistics. This course provides hands-on experience with R, ensuring you can apply statistical methods effectively in real-world scenarios.This course is divided into Eight ModulesWhat is Data? - Understand the basics of data, its types, and how it's collected and organized.Introduction to R Programming - Dive into R and R-studio, a powerful tool for statistical computing and graphics, essential for modern data analysis.Descriptive Statistics - Learn to summarize and describe the essential features of numerical data, crucial for initial data exploration. You will also learn how to build their visualization. Handling Categorical Data - Explore techniques for effectively managing and analyzing categorical variables.Probabilities - Gain insights into the concepts of probability, a foundational pillar for statistical inference. You will understand the subjective, classical, conditional, etc probabilities concepts at the end of this module. Correlation - Discover the methods to measure the strength and direction of a relationship between two variables. We will explain to you the Pearson, Kendall and Spearman correlations.Regression - Understand how to model relationships between variables and make predictions. We will teach you about Simple linear Regression, Multiple Linear Regression, and Logistic Regression. Hypothesis Testing - Develop the ability to test assumptions and make decisions based on data. You will learn the Z-test, T-test and its types, F-test, ANOVA and its types, and Chi-Sq test and its types. This course is a unique blend of theory and practical. You will learn the theory of statistical concepts and along with it you will learn the R-programming to apply those statistical concepts to your data. We hope this journey will be enlightening for you. After having this course, you will be confident to analyze your data by your own.
