Statistical Methods: Essential Concepts and Applications
Develop advanced statistics skills from hypothesis testing to regression analysis. Build quantitative expertise essential for professional advancement.
Develop advanced statistics skills from hypothesis testing to regression analysis. Build quantitative expertise essential for professional advancement.
This comprehensive statistics course from LSE introduces essential statistical concepts, methods, and techniques with emphasis on practical applications. Students will learn key statistical methods including hypothesis testing, contingency tables, chi-squared tests, sampling design, correlation, and linear regression. The course focuses on developing practical skills in approaching statistical problems and interpreting results, particularly relevant to management, economics, and social sciences. As part of LSE's statistics series, this course builds foundational knowledge while preparing students for more advanced statistical concepts.
3.6
(8 ratings)
Instructors:
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What you'll learn
Master key statistical concepts and methods for data analysis
Perform hypothesis testing and interpret results with confidence
Analyze contingency tables using chi-squared tests
Understand sampling design and principles of causation
Apply correlation and linear regression techniques effectively
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, Exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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There are 5 modules in this course
This comprehensive course covers essential statistical methods and their applications. The curriculum progresses through hypothesis testing, contingency tables and chi-squared tests, sampling design and causation concepts, and culminates with correlation and linear regression analysis. Students learn both theoretical foundations and practical applications, with emphasis on problem-solving approaches and clear result interpretation. The course is designed to build quantitative skills applicable to management, economics, and social sciences.
Hypothesis Testing I
Module 1
Hypothesis Testing II
Module 2
Contingency Tables and Chi-squared Test
Module 3
Sampling Design and Causation
Module 4
Correlation and Linear Regression
Module 5
Fee Structure
Instructor
12 Courses
Distinguished Statistics Lecturer and Forensic Statistics Expert
James Abdey serves as an Associate Professorial Lecturer in Statistics at the London School of Economics and Political Science (LSE), where he earned his Ph.D. in 2010 with his innovative thesis "To p, or not to p?: Quantifying inferential decision errors to assess whether significance truly is significant." His expertise spans mathematical statistics, quantitative methods, and market research, with particular focus on forensic statistics and the intersection of statistics with law. His academic contributions include teaching core undergraduate courses and developing specialized electives in market research techniques. Beyond academia, he has established himself as a respected consultant, working on quantitative projects for organizations including the World Gold Council and the art market. His research has significantly influenced statistical methodology, particularly in hypothesis testing and inferential decision-making. Through his involvement with LSE's Summer School and the University of London International Programmes, he has played a crucial role in advancing statistical education and making complex statistical concepts accessible to diverse audiences
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3.6 course rating
8 ratings
Frequently asked questions
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