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Statistical Inference for Estimation in Data Science
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Statistical Inference for Estimation in Data Science

This course is part of Data Science Foundations: Statistical Inference.

Course Cost

Free course

Intermediate

Skill Level

26 Hours

Self-paced lessons

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Data Science Foundations: Statistical Inference Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

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4.1

6,832 Enrolled

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Jem Corcoran

Jem Corcoran

English

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olive-leaves-logo

4.1

6,832 Enrolled

olive-leaves-logo

English

Jem Corcoran

Jem Corcoran

What you'll learn

  • Identify and evaluate characteristics of good estimators

  • Construct maximum likelihood estimators

  • Develop method of moments estimators

  • Create confidence intervals for various parameters

  • Understand sampling distributions

  • Implement statistical inference techniques in R

Skills you'll gain

Statistical Inference
Maximum Likelihood Estimation
Confidence Intervals
Parameter Estimation
Statistical Theory
R Programming
Sampling Distributions
Probability Theory
Data Analysis
Statistical Modeling

This course includes:

8.1 Hours PreRecorded video

12 quizzes

Access on Mobile, Tablet, Desktop

FullTime access

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There are 6 modules in this course

This comprehensive course covers advanced statistical inference and estimation techniques essential for data science applications. Students learn theoretical foundations and practical implementations of parameter estimation, including method of moments and maximum likelihood estimation. The curriculum includes construction and interpretation of confidence intervals, sampling distributions, and asymptotic properties of estimators. Special emphasis is placed on both mathematical rigor and practical application using R programming.

Start Here!

Module 1 · 1 Hours to complete

Point Estimation

Module 2 · 7 Hours to complete

Maximum Likelihood Estimation

Module 3 · 4 Hours to complete

Large Sample Properties of Maximum Likelihood Estimators

Module 4 · 5 Hours to complete

Confidence Intervals Involving the Normal Distribution

Module 5 · 5 Hours to complete

Beyond Normality: Confidence Intervals Unleashed!

Module 6 · 4 Hours to complete

Fee Structure

Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Data Science Foundations: Statistical Inference

Reviews

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Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

Jem Corcoran
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4.7

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73

Reviews

32,517

Students

6

Courses

Jem Corcoran is an Associate Professor in the Department of Applied Mathematics at the University of Colorado Boulder, where he specializes in probability theory and statistical inference. He holds a Ph.D. in Applied Mathematics from Colorado State University and has been instrumental in developing courses that bridge theoretical concepts with practical applications in data science. His teaching includes "Probability Theory: Foundation for Data Science," "Statistical Inference and Hypothesis Testing in Data Science Applications," and "Statistical Inference for Estimation in Data Science."Dr. Corcoran's research focuses on advanced statistical methods and their applications, particularly in the context of data analysis and modeling. He has contributed significantly to the field through numerous publications and is recognized for his expertise in applied probability and Monte Carlo methods. As a dedicated educator, he aims to enhance student understanding of complex statistical concepts, preparing them for successful careers in data science and related fields. Through his work, Jem Corcoran continues to influence the next generation of mathematicians and data scientists at CU Boulder.
Statistical Inference for Estimation in Data Science

Intermediate

Skill Level

26 Hours

Self-paced lessons

Course Cost

Free course

Completion

CERTIFICATE

Frequently asked Questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.