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所在平台: Udemy |
课程主页: https://www.udemy.com/course/statistics-and-probability-for-data-analytics-data-science/
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课程名称：数据分析与数据科学的统计学与概率论 课程概述：在信息时代，数据成为新的石油，推动决策的核心。掌握统计学和概率论的基础概念对于任何希望在数据分析、商业分析或数据科学领域中脱颖而出的人至关重要。我们的课程“数据分析与数据科学的统计学与概率论”将帮助您掌握这些必要技能，为未来的职业发展铺平道路。 本课程包含45章内容，将系统地构建您在统计学和概率论领域的基础，以便做出数据驱动的决策。课程通过简洁而全面的视频讲解每个概念，并附有练习题和解决方案，以测试您的理解程度。 课程内容包括： - 统计学基础 - 描述性统计的深入分析，包括单变量数据分析、测量水平、集中趋势的测量、变异程度及分布形状 - 使用箱线图法进行五点摘要和异常值检测 - 双变量数据分析，如偏差系数、协方差、相关性（皮尔逊相关和斯皮尔曼等级相关）、散点图等 - 排列与组合及其各种案例 - 概率及其各类概念，如集合运算、依赖事件、全概率及贝叶斯定理 - 理解离散和连续变量的概率分布，包括累积分布 - 不同类型的离散与随机变量的概率分布，例如均匀分布、伯努利分布、二项分布、泊松分布、正态分布、Student's T 分布、卡方分布和F分布，以及各分布的应用案例 - 样本均值的抽样分布、误差范围、点估计、置信区间及其各种案例 - 推论统计，包括假设检验、单尾和双尾检验、不同均值检验、卡方检验和ANOVA检验 - 单尾和双尾检验的实际应用 - 1型错误和2型错误的实际案例分析以提高理解 欢迎立即报名，掌握统计学与概率论的核心概念，为您的数据分析与数据科学之路打下坚实基础！
Unlock the power of data with our comprehensive course: Statistics and Probability for Data Analytics & Data Science. In an era where data is the new oil and data drives decision-making, mastering these foundational concepts is of core importance for anyone looking to excel in the field of data analytics, business analytics or data science.So, anyone who want to acquire these necessary skills for a bright career prospect in these fields, then, you've come to the right place my friend!This 45 chapters course will help you to master your foundations in the field of statistics and probability which will help you to take data driven decisions appropriately. The course provides crisp yet comprehensive and detailed videos for every concept in the field of statistics and probability followed by quizzes with solutions to test the clarity of your concepts.So, below is the overview of what we will be covering in this course:Fundamentals of statisticsDeep dive into descriptive statistics including univariate data analysis with the help of levels of measurement, measures of central tendency, measures of variability and shape of distribution for proper data analysisFive-point summary and Outlier detection using box plot methodBi variate data analysis such as coefficient of deviation, covariance, correlation (including both Pearson correlation and spearman rank correlation), scatter plots, etc.Permutation and combination along with their various cases and examplesProbability and its various concepts such as its set operations, dependent events, total probability and Bayes theoremUnderstanding discrete and continuous variable probability distributions including cumulative probability distributionsDifferent probability distributions for both discrete and random variable such as Uniform, Bernoulli, Binomial, Poisson, Normal, Students T, Chi square and F.Use cases and examples of each probability distributionsSampling distributions of mean, margin of error, point estimate, confidence interval and its various cases for one sample and two sampleInferential statistics including hypothesis testing, one tailed and two tailed test, different test of mean, chi square and ANOVA testingPractical applications of one tailed and two tailed testReal life scenarios of type 1 and type 2 error for better claritySo, enroll today guys and master your concepts in statistics and probability.
