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If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

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Data Science Fundamentals Part 2: Unit 2

Data Science Fundamentals Part 2: Unit 2

本课程是 Data Science Fundamentals, Part 2 专项课程的一部分

位教师：Pearson

包含在 Coursera Plus 中

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1个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

6 小时完成

灵活的计划

自行安排学习进度

1个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

6 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Master foundational and modern techniques for statistical inference and data analysis.
Apply computational and sampling-based approaches to real-world data problems.
Conduct hypothesis tests and optimize processes using A/B testing methodologies.
Distinguish between correlation and causation to ensure robust, actionable insights.

您将获得的技能

要了解的详细信息

可分享的证书

添加到您的领英档案

了解顶级公司的员工如何掌握热门技能

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Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Data Science Fundamentals, Part 2 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
通过实践项目培养工作相关技能
获得可共享的职业证书

该课程共有1个模块

Thsi course explores foundational and advanced techniques for making reliable inferences from data, starting with a the history and evolution of statistical analysis. Through hands-on lessons, you’ll learn how to leverage computational and sampling-based methods to draw meaningful conclusions, and gain practical experience with hypothesis testing—a cornerstone skill for optimizing digital experiences, such as through A/B testing. The course emphasizes the importance of understanding and quantifying uncertainty, equipping you with the tools to interpret confidence intervals and make well-informed decisions. You’ll also tackle the critical distinction between correlation and causation, ensuring your analyses are robust and actionable. Whether you’re looking to enhance your analytical toolkit or drive impactful business outcomes, this course teaches essential skills for today’s data-centric world.

This module introduces key concepts in statistical inference, focusing on estimation, hypothesis testing, and evaluation. You’ll explore foundational and modern techniques for drawing conclusions from data, including computational and sampling-based methods. The lessons cover hypothesis tests, confidence intervals, and practical applications like A/B testing for web optimization. Emphasis is placed on understanding uncertainty and distinguishing correlation from causation, equipping you with essential tools for robust data analysis.

涵盖的内容

17个视频1个作业

17个视频总计339分钟

Topics1分钟
What Problem Is Statistics the Answer To?--Part 118分钟
What Problem Is Statistics the Answer To?--Part 219分钟
The Statistical Framework: Descriptive, Inferential, and Predictive22分钟
Non-Parametric Estimation--The Bootstrap47分钟
Quantifying Uncertainty--Confidence Intervals, Part 111分钟
Quantifying Uncertainty--Confidence Intervals, Part 224分钟
Correlation versus Causation, Part 125分钟
Correlation versus Causation, Part 223分钟
Correlation versus Causation, Part 312分钟
Evaluating Hypotheses--Significance Testing, Part 119分钟
Evaluating Hypotheses--Significance Testing, Part 213分钟
Evaluating Hypotheses--Significance Testing, Part 318分钟
Evaluating Hypotheses--Significance Testing, Part 430分钟
Evaluating Hypotheses--Significance Testing, Part 510分钟
Experimental Design--Assumptions and Caveats25分钟
Review--Which Approach to Choose17分钟

1个作业总计30分钟

Making Inferences: Statistical Estimation and Evaluation Quiz30分钟

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

Pearson

268 门课程9,454 名学生

提供方

Pearson

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常见问题

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.