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Martin Anthony
and
James Abdey
This exam assesses all concepts, methods and techniques introduced across the four courses within the LSE MicroBachelors program in Mathematics and Statistics Fundamentals:
Mathematics 1: Differential calculus
Mathematics 1: Integral calculus, algebra, and applications
Statistics 1: Introductory statistics, probability and estimation ****
Statistics 1: Statistical methods ****
It is two hours in duration and must be sat under online proctored conditions.
Read more
This exam assesses all concepts, methods and techniques introduced across the four courses within the LSE MicroBachelors program in Mathematics and Statistics Fundamentals:
Mathematics 1: Differential calculus
Mathematics 1: Integral calculus, algebra, and applications
Statistics 1: Introductory statistics, probability and estimation ****
Statistics 1: Statistical methods ****
It is two hours in duration and must be sat under online proctored conditions.
Read more
This exam assesses all concepts, methods and techniques introduced across the four courses within the LSE MicroBachelors program in Mathematics and Statistics Fundamentals:
Mathematics 1: Differential calculus
Mathematics 1: Integral calculus, algebra, and applications
Statistics 1: Introductory statistics, probability and estimation ****
Statistics 1: Statistical methods ****
It is two hours in duration and must be sat under online proctored conditions.
It is the final step towards completing the LSE MicroBachelors program in Statistics Fundamentals and you must pass with a mark of 60% or higher to gain your certificate.
Register for this course and see more details by visiting:
OpenCourser.com/course/w9bc9h/mathematics
What's inside
Learning objective
N/a
N/a
Syllabus
The following topics are assessed within this exam:
Functions and graphs
The derivative
Curve sketching and optimisation
Read more
Syllabus
The following topics are assessed within this exam:
Functions and graphs
The derivative
Curve sketching and optimisation
Read more
Functions of two variables and partial derivatives
Critical points of two-variable functions
Integration
Profit maximisation
Constrained optimisation
Matrices, vectors, and linear equations
Sequences, series, and financial modelling
● Point and interval estimation
● Hypothesis testing I
● Hypothesis testing II
● Contingency tables and the chi-squared test
● Sampling design and some ideas underlying causation
● Correlation and linear regression
● Mathematical revision and the nature of statistics
● Data visualisation and descriptive statistics
● Probability theory
● The normal distribution and ideas of sampling
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides a certificate in Statistics Fundamentals issued by the London School of Economics and Political Science (LSE)
Covers the fundamental principles of mathematics and statistics essential for further study or professional practice
Provides a structured learning path with four foundational courses followed by an online proctored capstone exam
Taught by instructors from the LSE, recognized for their expertise in mathematics and statistics education
Requires learners to pass the capstone exam with a score of 60% or higher to obtain the certificate, ensuring a rigorous assessment of knowledge and skills
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Save Mathematics and Statistics Fundamentals Proctored Exam to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Mathematics and Statistics Fundamentals Proctored Exam with these
activities:
Review basic probability concepts
Show steps
Recall and refresh your understanding of fundamental probability concepts, such as sample spaces, events, and probability distributions, to prepare for more advanced statistical topics.
Browse courses on
Probability
Show steps
-
Review notes or online resources on basic probability.
-
Solve practice problems to reinforce your understanding.
-
Identify areas where you need additional clarification.
-
Seek help from a tutor or instructor if necessary.
Review Introduction to Statistical Learning
Show steps
Review the introductory chapters of this comprehensive textbook to strengthen your foundation in statistical learning concepts and techniques.
View
An Introduction to Statistical Learning: with...
on Amazon
Show steps
-
Obtain a copy of the textbook.
-
Read and understand the introductory chapters.
-
Summarize the key concepts and methods.
-
Complete the practice exercises provided in the book.
-
Discuss the concepts with your peers or an instructor.
Solve practice problems on derivatives
Show steps
Solve a variety of practice problems on derivatives to reinforce your understanding of this fundamental concept.
Show steps
-
Review notes and lecture slides on derivatives.
-
Attempt to solve practice problems on your own.
-
Check your answers against the provided solutions.
-
Identify areas where you need additional practice.
-
Seek help from a tutor or instructor if needed.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Complete practice questions on hypothesis testing
Show steps
Engage in practice questions on hypothesis testing to strengthen your understanding of statistical inference and hypothesis evaluation.
Browse courses on
Hypothesis Testing
Show steps
-
Review lecture materials and notes on hypothesis testing.
-
Attempt to solve practice questions independently.
-
Compare your answers to provided solutions.
-
Identify areas where you need additional practice.
-
Seek clarification from a tutor or instructor if needed.
Follow tutorials on solving optimization problems
Show steps
Follow online tutorials or guided exercises on solving optimization problems to enhance your problem-solving skills in this area.
Browse courses on
Optimization
Show steps
-
Search for tutorials on optimization problems.
-
Choose a tutorial that aligns with your skill level.
-
Follow the steps outlined in the tutorial.
-
Complete the practice exercises provided.
-
Apply the techniques to solve your own optimization problems.
Participate in a study group for statistics
Show steps
Join a study group with peers to discuss course material, work on practice problems together, and reinforce your understanding of statistical concepts.
Browse courses on
Statistics
Show steps
-
Find or form a study group with other students in the course.
-
Choose a regular meeting time and place.
-
Prepare for each meeting by reviewing the assigned material.
-
Actively participate in discussions and problem-solving activities.
-
Seek support and clarification from your peers.
Create a data visualization of statistical data
Show steps
Create a data visualization to represent statistical data, such as a graph, chart, or infographic. This will help you develop your data analysis and communication skills.
Browse courses on
Data Visualization
Show steps
-
Gather and clean the data you want to visualize.
-
Choose an appropriate data visualization format.
-
Create the visualization using a data visualization tool.
-
Interpret the visualization and draw conclusions from the data.
-
Present your visualization to others.
Attend a workshop on data analysis techniques
Show steps
Participate in a workshop led by experts to gain practical experience in applying data analysis techniques, enhancing your proficiency in data handling and interpretation.
Browse courses on
Data Analysis
Show steps
-
Identify relevant data analysis workshops.
-
Register for a workshop that aligns with your interests.
-
Attend the workshop and actively participate in activities.
-
Apply the techniques learned to your own data analysis projects.
-
Follow up with the workshop organizers or instructors if you have questions.
Review basic probability concepts
Show steps
Recall and refresh your understanding of fundamental probability concepts, such as sample spaces, events, and probability distributions, to prepare for more advanced statistical topics.
Browse courses on
Probability
Show steps
Show steps
Show steps
- Review notes or online resources on basic probability.
- Solve practice problems to reinforce your understanding.
- Identify areas where you need additional clarification.
- Seek help from a tutor or instructor if necessary.
Review Introduction to Statistical Learning
Show steps
Review the introductory chapters of this comprehensive textbook to strengthen your foundation in statistical learning concepts and techniques.
View
An Introduction to Statistical Learning: with...
on Amazon
Show steps
Show steps
Show steps
- Obtain a copy of the textbook.
- Read and understand the introductory chapters.
- Summarize the key concepts and methods.
- Complete the practice exercises provided in the book.
- Discuss the concepts with your peers or an instructor.
Solve practice problems on derivatives
Show steps
Solve a variety of practice problems on derivatives to reinforce your understanding of this fundamental concept.
Show steps
Show steps
Show steps
- Review notes and lecture slides on derivatives.
- Attempt to solve practice problems on your own.
- Check your answers against the provided solutions.
- Identify areas where you need additional practice.
- Seek help from a tutor or instructor if needed.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Complete practice questions on hypothesis testing
Show steps
Engage in practice questions on hypothesis testing to strengthen your understanding of statistical inference and hypothesis evaluation.
Browse courses on
Hypothesis Testing
Show steps
Show steps
Show steps
- Review lecture materials and notes on hypothesis testing.
- Attempt to solve practice questions independently.
- Compare your answers to provided solutions.
- Identify areas where you need additional practice.
- Seek clarification from a tutor or instructor if needed.
Follow tutorials on solving optimization problems
Show steps
Follow online tutorials or guided exercises on solving optimization problems to enhance your problem-solving skills in this area.
Browse courses on
Optimization
Show steps
Show steps
Show steps
- Search for tutorials on optimization problems.
- Choose a tutorial that aligns with your skill level.
- Follow the steps outlined in the tutorial.
- Complete the practice exercises provided.
- Apply the techniques to solve your own optimization problems.
Participate in a study group for statistics
Show steps
Join a study group with peers to discuss course material, work on practice problems together, and reinforce your understanding of statistical concepts.
Browse courses on
Statistics
Show steps
Show steps
Show steps
- Find or form a study group with other students in the course.
- Choose a regular meeting time and place.
- Prepare for each meeting by reviewing the assigned material.
- Actively participate in discussions and problem-solving activities.
- Seek support and clarification from your peers.
Create a data visualization of statistical data
Show steps
Create a data visualization to represent statistical data, such as a graph, chart, or infographic. This will help you develop your data analysis and communication skills.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Gather and clean the data you want to visualize.
- Choose an appropriate data visualization format.
- Create the visualization using a data visualization tool.
- Interpret the visualization and draw conclusions from the data.
- Present your visualization to others.
Attend a workshop on data analysis techniques
Show steps
Participate in a workshop led by experts to gain practical experience in applying data analysis techniques, enhancing your proficiency in data handling and interpretation.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Identify relevant data analysis workshops.
- Register for a workshop that aligns with your interests.
- Attend the workshop and actively participate in activities.
- Apply the techniques learned to your own data analysis projects.
- Follow up with the workshop organizers or instructors if you have questions.
Career center
Learners who complete Mathematics and Statistics Fundamentals Proctored Exam will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
A Data Analyst uses mathematics, statistics, and other analytical methods to analyze and interpret data. They use this information to help businesses and organizations make informed decisions about a wide range of issues. This course may be useful for aspiring Data Analysts because it provides a strong foundation in mathematics and statistics, which are essential for this role.
Statistician
Statistician
A Statistician uses mathematics and statistics to collect, analyze, and interpret data. They use this information to help businesses and organizations make informed decisions about a wide range of issues. This course may be useful for aspiring Statisticians because it provides a strong foundation in mathematics and statistics, which are essential for this role.
Market Research Analyst
Market Research Analyst
A Market Research Analyst uses statistics and other research methods to study market trends and consumer behavior. They use this information to help businesses make informed decisions about product development, marketing, and sales. This course may be useful for aspiring Market Research Analysts because it provides a strong foundation in statistics, which is essential for this role.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematics, statistics, and financial modeling to analyze and make recommendations on investments. They use this information to help hedge funds, investment banks, and other financial institutions make informed decisions about how to allocate their capital. This course may be useful for aspiring Quantitative Analysts because it provides a strong foundation in mathematics and statistics, which are essential for this role.
Actuary
Actuary
An Actuary uses mathematics and statistics to assess and manage risk. They use this information to help insurance companies, pension funds, and other financial institutions make informed decisions about how to price their products and manage their investments. This course may be useful for aspiring Actuaries because it provides a strong foundation in mathematics and statistics, which are essential for this role.
Financial Analyst
Financial Analyst
A Financial Analyst uses mathematics, statistics, and financial modeling to analyze and make recommendations on investments. They use this information to help businesses make informed decisions about how to allocate their capital. This course may be useful for aspiring Financial Analysts because it provides a solid foundation in mathematics and statistics, which are essential for this role.
Data Scientist
Data Scientist
A Data Scientist uses mathematics, statistics, and computer science to analyze data. They use this data to solve problems and make recommendations. This course may be useful for aspiring Data Scientists because it provides a solid foundation in mathematics and statistics, which are essential for this role.
Business Analyst
Business Analyst
A Business Analyst uses mathematics, statistics, and other analytical methods to help businesses and organizations improve their operations. They use this information to help businesses make informed decisions about how to allocate their resources, improve their processes, and reduce their costs. This course may be useful for aspiring Business Analysts because it provides a strong foundation in mathematics and statistics, which are essential for this role.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses mathematics, statistics, and other analytical methods to help businesses and organizations improve their operations. They use this information to help businesses make informed decisions about how to allocate their resources, improve their processes, and reduce their costs. This course may be useful for aspiring Operations Research Analysts because it provides a strong foundation in mathematics and statistics, which are essential for this role.
Data Architect
Data Architect
A Data Architect designs and manages data systems. They use mathematics, statistics, and other analytical methods to ensure that data is stored, processed, and accessed in a way that meets the needs of the business. This course may be useful for aspiring Data Architects because it provides a strong foundation in mathematics and statistics, which are essential for this role.
Database Administrator
Database Administrator
A Database Administrator manages and maintains databases. They use mathematics, statistics, and other analytical methods to ensure that data is stored, processed, and accessed in a way that meets the needs of the business. This course may be useful for aspiring Database Administrators because it provides a strong foundation in mathematics and statistics, which are essential for this role.
Risk Manager
Risk Manager
A Risk Manager uses mathematics, statistics, and financial modeling to assess and manage risk. They use this information to help businesses and organizations make informed decisions about how to protect themselves from financial and other risks. This course may be useful for aspiring Risk Managers because it provides a strong foundation in mathematics and statistics, which are essential for this role.
Systems Analyst
Systems Analyst
A Systems Analyst analyzes and designs computer systems. They use mathematics, statistics, and other analytical methods to ensure that systems are efficient, reliable, and user-friendly. This course may be useful for aspiring Systems Analysts because it provides a strong foundation in mathematics and statistics, which are essential for this role.
Software Engineer
Software Engineer
A Software Engineer uses mathematics, statistics, and other analytical methods to design, develop, and test software applications. They use this information to help businesses and organizations create software that is efficient, reliable, and user-friendly. This course may be useful for aspiring Software Engineers because it provides a strong foundation in mathematics and statistics, which are essential for this role.
Computer Scientist
Computer Scientist
A Computer Scientist designs and develops computer systems. They use mathematics, statistics, and other analytical methods to ensure that systems are efficient, reliable, and user-friendly. This course may be useful for aspiring Computer Scientists because it provides a strong foundation in mathematics and statistics, which are essential for this role.
For more career information including salaries, visit:
OpenCourser.com/course/w9bc9h/mathematics
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Mathematics and Statistics Fundamentals Proctored Exam.
This classic textbook provides a comprehensive overview of calculus, including differential and integral calculus, and multivariate calculus. It good resource for students who want to review or supplement the material covered in the course.
This classic textbook provides a comprehensive overview of linear algebra, including vector spaces, matrices, and linear transformations. It good resource for students who want to review or supplement the material covered in the course.
This textbook provides a comprehensive overview of mathematical statistics, including probability theory, random variables, and statistical inference. It good resource for students who want to review or supplement the material covered in the course.
Save
This textbook provides a comprehensive overview of econometrics, including regression analysis, time series analysis, and panel data analysis. It good resource for students who want to review or supplement the material covered in the course.
This textbook provides a comprehensive overview of statistical learning methods, including supervised learning, unsupervised learning, and ensemble methods. It good resource for students who want to review or supplement the material covered in the course.
This textbook provides a comprehensive overview of probability theory, including probability spaces, random variables, and conditional probability. It good resource for students who want to review or supplement the material covered in the course.
This textbook provides a comprehensive overview of mathematical statistics, including probability theory, random variables, and statistical inference. It good resource for students who want to review or supplement the material covered in the course.
This textbook provides a comprehensive overview of statistics, including probability theory, random variables, and statistical inference. It good resource for students who want to review or supplement the material covered in the course.
This textbook provides a comprehensive overview of statistical modeling, including Bayesian modeling and frequentist modeling. It good resource for students who want to review or supplement the material covered in the course.
Save
This textbook provides a comprehensive overview of deep learning, including convolutional neural networks, recurrent neural networks, and generative adversarial networks. It good resource for students who want to review or supplement the material covered in the course.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/w9bc9h/mathematics
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Effort
1 to 2 hours per week for 1 week
Level
Intermediate
Via
edX
Institution
The London School of Economics and Political Science
Instructors
Martin Anthony
James Abdey
Language
English
Transcript
English
Good to know
Provides a certificate in Statistics Fundamentals issued by the London School of Economics and Political Science (LSE)
Covers the fundamental principles of mathematics and statistics essential for further study or professional practice
Provides a structured learning path with four foundational courses followed by an online proctored capstone exam
Taught by instructors from the LSE, recognized for their expertise in mathematics and statistics education
Requires learners to pass the capstone exam with a score of 60% or higher to obtain the certificate, ensuring a rigorous assessment of knowledge and skills
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