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Data Science Fundamentals Part 2: Unit 2

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Data Science Fundamentals Part 2: Unit 2

This course is part of Data Science Fundamentals, Part 2 Specialization

Instructors: Pearson

Included with

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1 module

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

6 hours to complete

Flexible schedule

Learn at your own pace

1 module

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.

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

1 assignment

Taught in English

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Build your subject-matter expertise

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 videos Total 340 minutes

Topics 1 minute
What Problem Is Statistics the Answer To?--Part 1 19 minutes
What Problem Is Statistics the Answer To?--Part 2 19 minutes
The Statistical Framework: Descriptive, Inferential, and Predictive 23 minutes
Non-Parametric Estimation--The Bootstrap 48 minutes
Quantifying Uncertainty--Confidence Intervals, Part 1 11 minutes
Quantifying Uncertainty--Confidence Intervals, Part 2 24 minutes
Correlation versus Causation, Part 1 25 minutes
Correlation versus Causation, Part 2 23 minutes
Correlation versus Causation, Part 3 12 minutes
Evaluating Hypotheses--Significance Testing, Part 1 19 minutes
Evaluating Hypotheses--Significance Testing, Part 2 13 minutes
Evaluating Hypotheses--Significance Testing, Part 3 19 minutes
Evaluating Hypotheses--Significance Testing, Part 4 30 minutes
Evaluating Hypotheses--Significance Testing, Part 5 11 minutes
Experimental Design--Assumptions and Caveats 26 minutes
Review--Which Approach to Choose 17 minutes

1 assignment Total 30 minutes

Making Inferences: Statistical Estimation and Evaluation Quiz 30 minutes

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Instructors

Pearson

268 Courses 49,150 learners

Offered by

Pearson

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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.