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所在平台: Udemy |
课程主页: https://www.udemy.com/course/correlation-in-data-analytics-business-statistics/
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**课程名称：** 数据分析与商业统计中的相关性 **课程概述：** 本课程深入探讨了相关性这一核心统计概念，以及它在数据分析和商业统计中的重要应用。课程将帮助学员理解两个变量之间关系的强度和方向，并通过“r”值（相关系数）来量化这种关系，相关系数的取值范围在 -1.0 到 +1.0 之间，-1 代表完全负相关，+1 代表完全正相关，0 则表示无相关性。 **课程内容亮点：** * **核心相关性计算方法：** * **卡尔·皮尔逊方法（Karl Pearson's Method）：** 重点讲解了直接法和假定平均数法，使学员能熟练计算皮尔逊相关系数。 * **斯皮尔曼等级差法（Spearman's Rank Difference Method）：** 介绍了处理不同等级和相同等级数据的两种方法，帮助学员理解等级关联。 * **并行偏差法（Method of Concurrent Deviations）：** 详细讲解了此方法，为学员提供了另一种分析变量间关系的方式。 * **扩展应用：** * **分组数据中的相关性：** 涵盖了如何处理分组数据集中的相关性分析。 **学习目标：** 学员将掌握所有主要的**相关性分析工具和技术**，能够准确计算和解释不同类型的相关性，并将其应用于实际的数据分析和商业决策中。通过本课程的学习，学员将获得扎实的统计学基础和实用的分析技能。
Correlation is a process of finding out the degree of relationship between two variables. Correlation is a great statistical technique and a very interesting one. The correlation is one of the easiest descriptive statistics to understand and possibly one of the most widely used. The term correlation refers to the measurement of a relationship between two or more variables. A correlational coefficient is used to represent this relationship and is often abbreviated with the letter ‘r.' A correlational coefficient typically ranges between -1.0 and +1.0 and provides two important pieces of information regarding the relationship: Intensity and Direction. The value -1 indicates a perfect negative correlation, while a +1 indicates a perfect positive correlation. A correlation of zero means there is no relationship between the two variables. When there is a negative correlation between two variables, as the value of one variable increases, the value of the other variable decreases, and vise versa. In other words, for a negative correlation, the variables work opposite each other.This course will give insights on:-Calculation of Coefficient of Correlation using Karl Pearson's method, -Spearman's Rank Difference Method & -Method of Concurrent Deviations. Here , several important techniques like Direct Method and Assumed Mean Method in Karl Pearson have also been discussed in detail. Correlation in Grouped Series has also been explained in detail. In Spearman's Method both approaches having different ranks and cases having same ranks have been explained along with Method of Concurrent deviations.Overall, the students will have a great learning time and will be studying all the major tools and techniques of Correlation Analysis.
