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⇱ Data Science Fundamentals Part 2: Unit 2 | Coursera


Data Science Fundamentals Part 2: Unit 2

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Data Science Fundamentals Part 2: Unit 2

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Gain insight into a topic and learn the fundamentals.
Beginner level

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6 hours to complete
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

6 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • 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.

Details to know

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Assessments

1 assignment

Taught in English

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This course is part of the Data Science Fundamentals, Part 2 Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There is 1 module in this course

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.

What's included

17 videos1 assignment

17 videosTotal 340 minutes
  • Topics1 minute
  • What Problem Is Statistics the Answer To?--Part 119 minutes
  • What Problem Is Statistics the Answer To?--Part 219 minutes
  • The Statistical Framework: Descriptive, Inferential, and Predictive23 minutes
  • Non-Parametric Estimation--The Bootstrap48 minutes
  • Quantifying Uncertainty--Confidence Intervals, Part 111 minutes
  • Quantifying Uncertainty--Confidence Intervals, Part 224 minutes
  • Correlation versus Causation, Part 125 minutes
  • Correlation versus Causation, Part 223 minutes
  • Correlation versus Causation, Part 312 minutes
  • Evaluating Hypotheses--Significance Testing, Part 119 minutes
  • Evaluating Hypotheses--Significance Testing, Part 213 minutes
  • Evaluating Hypotheses--Significance Testing, Part 319 minutes
  • Evaluating Hypotheses--Significance Testing, Part 430 minutes
  • Evaluating Hypotheses--Significance Testing, Part 511 minutes
  • Experimental Design--Assumptions and Caveats26 minutes
  • Review--Which Approach to Choose17 minutes
1 assignmentTotal 30 minutes
  • Making Inferences: Statistical Estimation and Evaluation Quiz30 minutes

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Instructors

Pearson
268 Courses65,339 learners

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Frequently asked questions

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.

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.

This course is currently available only to learners who have paid or received financial aid, when available.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,