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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/the-power-of-statistics
课程评论：没有评论
课程名称：统计学的力量 概述：这是谷歌高级数据分析证书的七门课程中的第四门。在本课程中，您将了解到数据专业人士如何运用统计学来分析数据并获取重要见解。您将探讨描述性统计和推断性统计、概率、抽样、置信区间和假设检验等关键概念。此外，您会学习如何使用Python进行统计分析，并练习像数据专业人士一样沟通您的发现。 课程大纲： 1. **统计学入门与Python** - 描述：您将探索统计学在数据科学中的作用，识别描述性统计和推断性统计的区别。您将学习如何通过描述性统计快速总结数据集，并测量数据的中心、离散程度和相对位置。 2. **概率** - 描述：您将学习单事件概率计算的基本规则。接下来，您将发现数据专业人士如何使用贝叶斯定理等方法来描述更复杂的事件。最后，您将学习二项分布、泊松分布和正态分布等概率分布，以更好地理解数据的结构。 3. **抽样** - 描述：数据专业人士使用较小的数据样本来对大型数据集得出结论。您将学习他们收集和分析样本数据的不同方法，以及他们如何避免抽样偏差。您还将了解抽样分布如何帮助您做出准确的估计。 4. **置信区间** - 描述：您将探索数据专业人士如何使用置信区间来描述估计的不确定性。您将学习如何构建和解释置信区间，以及如何避免一些常见的误解。 5. **假设检验入门** - 描述：假设检验帮助数据专业人士判断测试或实验的结果是统计显著的还是偶然的。您将学习任何假设检验的基本步骤，以及假设检验如何帮助您得出有意义的结论。 6. **课程结束项目** - 描述：在本课程的结束项目中，您将运用假设检验等统计方法分析一个工作场景数据集。 通过本课程，您将能掌握统计学的基础知识，提升数据分析的能力，帮助您在数据科学的道路上更进一步。
Name:Introduction to statistics with Python
Description:You’ll explore the role of statistics in data science and identify the difference between descriptive and inferential statistics. You’ll learn how descriptive statistics can help you quickly summarize a dataset and measure the center, spread, and relative position of data.
Name:Probability
Description:You’ll learn the basic rules for calculating probability for single events. Next, you’ll discover how data professionals use methods such as Bayes’ theorem to describe more complex events. Finally, you’ll learn how probability distributions such as the binomial, Poisson, and normal distribution can help you better understand the structure of data.
Name:Sampling
Description:Data professionals use smaller samples of data to draw conclusions about large datasets. You’ll learn about the different methods they use to collect and analyze sample data and how they avoid sampling bias. You’ll also learn how sampling distributions can help you make accurate estimates.
Name:Confidence intervals
Description:You’ll explore how data professionals use confidence intervals to describe the uncertainty of their estimates. You'll learn how to construct and interpret confidence intervals, and how to avoid some common misinterpretations.
Name:Introduction to hypothesis testing
Description:Hypothesis testing helps data professionals determine if the results of a test or experiment are statistically significant or due to chance. You’ll learn about the basic steps for any hypothesis test and how hypothesis testing can help you draw meaningful conclusions about data.
Name:Course 4 end-of-course project
Description: In this end-of-course project, you’ll use statistical methods such as hypothesis testing to analyze a workplace scenario dataset.
This is the fourth of seven courses in the Google Advanced Data Analytics Certificate. In this course, you’ll discover how data professionals use statistics to analyze data and gain important insights. You'll explore key concepts such as descriptive and inferential statistics, probability, sampling, confidence intervals, and hypothesis testing. You'll also learn how to use Python for statistical analysis and practice communicating your findings like a data professional. Google employees who cu
