Mathematics and Statistics Fundamentals Exam
This course is part of Mathematics and Statistics Fundamentals.
This two-hour proctored examination serves as the final assessment for the LSE MicroBachelors program in Mathematics and Statistics Fundamentals. The exam comprehensively tests students' understanding of differential and integral calculus, probability theory, statistical methods, and various mathematical applications. Candidates must demonstrate mastery of concepts ranging from basic functions and derivatives to advanced statistical analysis and hypothesis testing.
Instructors:
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What you'll learn
Master functions graphs and derivatives in single and multiple variables
Apply integration techniques and optimization methods
Understand matrices vectors and linear equations
Implement statistical estimation and hypothesis testing
Analyze data using correlation and regression methods
Apply probability theory and normal distribution concepts
Skills you'll gain
This course includes:
PreRecorded video
Proctored Final Exam
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 5 modules in this course
The exam evaluates comprehensive understanding of mathematics and statistics fundamentals. Topics include functions and graphs, derivatives, curve sketching, integration, matrices, probability theory, statistical estimation, hypothesis testing, and regression analysis. Students must demonstrate practical application abilities across all covered concepts.
Functions and Calculus
Module 1
Integration and Applications
Module 2
Linear Algebra and Sequences
Module 3
Statistical Testing and Estimation
Module 4
Probability and Data Analysis
Module 5
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: Mathematics and Statistics Fundamentals
Instructors
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
8 Courses
Distinguished Mathematics Professor and Machine Learning Theory Expert
Martin Anthony serves as Professor of Mathematics and Director of the Data Science Institute at the London School of Economics and Political Science (LSE), where he has been a faculty member since 1990. Originally from Paisley, Scotland, his academic journey includes a BSc in Mathematics from the University of Glasgow (1988), a Ph.D. in Mathematics from the University of London (1991), and an MA in Higher and Professional Education from the Institute of Education (2002). His research focuses on the mathematical foundations of machine learning, data science, and Boolean functions, with recent work exploring algorithmic fairness and privacy in data science. His teaching excellence has been recognized with multiple awards, including the inaugural 2014 LSE Students' Union Teaching Excellence Award and LSE Education Excellence Awards in 2016 and 2017. Throughout his career at LSE, he has held several leadership positions, including Head of Department, Academic Governor, and Vice-Chair of the Academic Board. His contributions to mathematical education include authoring three research monographs and two successful undergraduate textbooks, establishing him as a leading figure in mathematical theory and education.
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