Statistics 1: Introductory Statistics and Probability
Master essential statistical concepts and methods with LSE's comprehensive course covering probability, data visualization, and estimation.
Master essential statistical concepts and methods with LSE's comprehensive course covering probability, data visualization, and estimation.
This foundational statistics course from LSE introduces essential concepts and techniques in statistical analysis. Students develop strong quantitative skills through comprehensive study of probability theory, data visualization, descriptive statistics, normal distribution, and estimation methods. The course emphasizes practical applications in management, economics, and social sciences, focusing on effective interpretation of statistical results and problem-solving approaches.
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What you'll learn
Apply essential statistical methods to analyze and interpret data effectively
Create clear data visualizations and summaries using appropriate techniques
Understand fundamental probability theory and its applications
Master the concepts of normal distribution and sampling methods
Develop skills in point and interval estimation
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, Exams
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 5 modules in this course
This comprehensive course introduces fundamental statistical concepts and methods essential for quantitative analysis. The curriculum covers mathematical foundations, data visualization techniques, probability theory, normal distribution, sampling methods, and estimation techniques. Students learn to interpret statistical results effectively and apply these concepts to real-world scenarios in management, economics, and social sciences.
Mathematical revision and the nature of statistics
Module 1
Data visualisation and descriptive statistics
Module 2
Probability theory
Module 3
The normal distribution and ideas of sampling
Module 4
Point and interval estimation
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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