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Probability & Statistics courses

Probability and statistics courses explore mathematical concepts for analyzing random events and interpreting data through models and inference. Use tools such as Python, R, Excel and Google Sheets to apply your theoretical knowledge in statistics.

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Recommended for Probability & Statistics beginners

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课程

R 统计学入门

中级技能水平
4.7+
2,099 条评价
4小时
提升统计技能,学习如何收集、分析数据并得出准确结论。

学习路径

统计学家 在 R 中

4.5+
7 条评价
52小时
统计学家收集和分析数据,帮助公司理解定量数据,包括发现趋势和进行预测。

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课程

使用 Python 分析调查数据

中级技能水平
4.6+
53 条评价
4小时
学习如何用Python分析调查数据,并了解何时适合应用描述性和推断性统计工具。

课程

R 中的营销选择建模

高级技能水平
4.8+
42 条评价
4小时
学习如何在 R 中分析和建模客户选择数据。

课程

Forecasting Product Demand in R

中级技能水平
4.7+
30 条评价
4小时
Learn how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of products from a real world example.

课程

Bayesian Modeling with RJAGS

高级技能水平
4.8+
51 条评价
4小时
In this course, youll learn how to implement more advanced Bayesian models using RJAGS.

课程

R 中的混合模型

中级技能水平
4.7+
25 条评价
4小时
学习混合模型:一种用于概率聚类和分类的便捷且正式的统计框架。

课程

R 中的概率谜题

基础技能水平
4.7+
69 条评价
4小时
通过解决各种概率谜题,学习在 R 中回答概率问题的策略。

课程

R 异常检测入门

中级技能水平
4.8+
26 条评价
4小时
学习用于识别异常值的统计检验,以及如何使用复杂的异常评分算法。

课程

在 R 中构建响应模型

中级技能水平
4.8+
30 条评价
4小时
学习构建市场响应的简单模型,提升营销方案的效果。

Probability & Statistics 相关资源

博客

How to Become a Statistician in 2026

Curious about how to become a statistician? Find out what a statistician does, what you need to get started, and what you can expect from this career.
Joleen Bothma's photo

Joleen Bothma

10分钟

教程

An Introduction to Statistical Machine Learning

Discover the powerful fusion of statistics and machine learning. Explore how statistical techniques underpin machine learning models, enabling data-driven decision-making.
Joanne Xiong's photo

Joanne Xiong

11分钟

教程

T-tests in R Tutorial: Learn How to Conduct T-Tests

Determine if there is a significant difference between the means of the two groups using t.test() in R.
Abid Ali Awan's photo

Abid Ali Awan

10分钟


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Frequently asked questions

How does probability and statistics related to data science?

Probability and statistics are foundational to data science, offering the tools and frameworks necessary for analyzing data, making predictions, and deriving meaningful insights. They enable data scientists to understand patterns, assess uncertainties, and make informed decisions based on data analysis.

Why is it important to develop knowledge in probability and statistics?

Developing knowledge in probability and statistics is crucial for effectively interpreting data and making reliable predictions. This understanding forms the basis for designing experiments, analyzing results, and validating conclusions in various fields, ensuring decisions are data-driven and evidence-based.

What careers can I pursue with knowledge in probability and statistics?

With knowledge in probability and statistics, you can pursue a wide array of careers such as data scientist, market researcher, machine learning engineer, statistical analyst, and risk manager. These roles span various industries including finance, healthcare, technology, and government, where interpreting data and making evidence-based decisions are key.

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