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James Abdey

This proctored examination assesses all concepts, methods and techniques introduced across the following four courses within the LSE MicroBachelors program in Statistics Fundamentals:

Statistics 1: Introductory statistics, probability and estimation

Statistics 1: Statistical methods

Statistics 2: Probability and distribution theory

Statistics 2: Statistical inference ****

It is two hours in duration and must be sat under online proctored conditions.

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This proctored examination assesses all concepts, methods and techniques introduced across the following four courses within the LSE MicroBachelors program in Statistics Fundamentals:

Statistics 1: Introductory statistics, probability and estimation

Statistics 1: Statistical methods

Statistics 2: Probability and distribution theory

Statistics 2: Statistical inference ****

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.

What's inside

Learning objective

N/a

Syllabus

The following topics are assessed within this exam:
● Mathematical revision and the nature of statistics
● Data visualisation and descriptive statistics
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Assesses concepts taught in four preceding courses in a comprehensive proctored exam
Covers a wide range of topics in statistics, from probability and distribution theory to inference and linear regression
Provides a comprehensive review of statistical methods and techniques
Completion grants a certificate in Statistics Fundamentals from the London School of Economics

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Reviews summary

Rigorous statistics fundamentals assessment

According to students, the Statistics Fundamentals Proctored Exam serves as a rigorous and comprehensive assessment, designed to deeply test understanding from the LSE MicroBachelors program. Many found the exam to be challenging but fair, effectively covering all critical areas from probability to statistical inference. While the proctoring experience was generally smooth for many, a few learners noted it could be intrusive or prone to technical glitches. Successfully passing this exam is widely regarded as providing significant credibility and validating accumulated statistical knowledge, making it a valuable final step for career-focused individuals.
Experiences with the online proctoring system varied.
"The proctoring process was smooth, though a bit strict."
"The proctoring system worked, but it felt a bit intrusive."
"I found the proctoring frustrating due to constant interruptions and strict rules."
"The proctoring was professional and seamless."
Requires deep mastery of pre-requisite material.
"A tough exam. It really tests your understanding deeply."
"I struggled with the depth required for some topics, even after going through all the prior courses."
"It's essential to have a solid grasp of all mathematical concepts and derivations. Don't underestimate the probability questions."
"You should definitely revise thoroughly, especially probability and inference."
Certificate provides significant academic and professional credibility.
"Passing this exam provides significant credibility."
"The certificate gained from passing is highly valuable."
"This truly validates my understanding."
A thorough exam that covers a wide range of topics.
"The exam was challenging but fair, covering all topics from the four prerequisite courses."
"Excellent culmination of the LSE Statistics Fundamentals program. The exam truly assessed comprehensive understanding of statistics, from descriptive to inferential."
"A rigorous and rewarding experience. This proctored exam accurately reflects the high standards of LSE. It covers all the critical areas outlined in the syllabus."
Some felt certain topics were disproportionately emphasized.
"I felt like certain areas from the earlier courses were emphasized more than others."
"The emphasis on certain areas (like specific derivations in probability) felt disproportionate to their coverage in the main courses."
"I felt this exam went beyond the scope of some of the earlier course material, particularly in the later sections on statistical inference."

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 Statistics Fundamentals Proctored Exam with these activities:
Review basic algebra and calculus concepts
Strengthen your foundation by reviewing essential algebra and calculus concepts.
Browse courses on Algebra
Show steps
  • Brush up on your calculus skills, including limits, derivatives, and integrals.
  • Gather your algebra and calculus notes, textbooks, or online resources.
  • Review the core concepts of algebra, such as equations, functions, and graphs.
Revisit previous statistics courses
Refresh your memory and strengthen your understanding of previously covered statistics concepts.
Browse courses on Statistics
Show steps
  • Review your notes, textbooks, or online materials from previous statistics courses.
  • Focus on key concepts, such as descriptive statistics, probability distributions, and hypothesis testing.
  • Solve practice problems to reinforce your understanding.
Watch video tutorials on YouTube
Supplement your understanding of mathematical revision and descriptive statistics through video tutorials.
Browse courses on Mathematical Revision
Show steps
  • Search for video tutorials on YouTube related to mathematical revision and descriptive statistics.
  • Select videos from reputable sources and experienced instructors.
  • Take notes and pause the videos when necessary to digest the information.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve practice problems from Khan Academy
Deepen your understanding of probability and statistical concepts by solving practice problems.
Browse courses on Probability
Show steps
  • Navigate to the Khan Academy website or mobile application.
  • Select the 'Math' section and choose 'Probability and Statistics'.
  • Select a topic and begin solving practice problems.
Join a study group or online forum
Enhance your learning by collaborating with peers in a study group or online forum.
Browse courses on Statistics
Show steps
  • Identify or create a study group with classmates or fellow learners.
  • Set regular meeting times and establish clear goals for each session.
  • Discuss course material, solve problems together, and provide support to each other.
Attend a statistics workshop
Expand your knowledge and skills by attending a statistics workshop tailored to your interests.
Browse courses on Hypothesis Testing
Show steps
  • Identify and register for a statistics workshop that aligns with your learning goals.
  • Attend the workshop and actively participate in discussions and activities.
  • Engage with the instructors and ask questions to clarify your understanding.
Write a blog post on a statistical concept
Solidify your understanding of a statistical concept by writing a blog post about it.
Browse courses on Probability
Show steps
  • Choose a specific statistical concept that you want to write about.
  • Research and gather information from reliable sources.
  • Write a draft of your blog post, explaining the concept in a clear and concise manner.
  • Revise and edit your post for clarity, accuracy, and engagement.
  • Publish your blog post and share it with others.

Career center

Learners who complete Statistics Fundamentals Proctored Exam will develop knowledge and skills that may be useful to these careers:
Statistician
A Statistician is a professional who collects, analyzes, interprets, and presents data. Statisticians often work with large and complex datasets, and they use statistical methods to make inferences about the population from which the data was collected. The LSE MicroBachelors program in Statistics Fundamentals can provide you with a strong foundation in the statistical methods that are needed to succeed in this career.
Data Scientist
A Data Scientist is a professional responsible for collecting, analyzing, and interpreting large and complex sets of data. The data is often obtained from a variety of sources, such as surveys, experiments, and social media. Data Scientists often use statistical methods to analyze the data, identify trends, and make predictions. The LSE MicroBachelors program in Statistics Fundamentals can provide you with a strong foundation in the statistical methods that are used in this field.
Quantitative Analyst
A Quantitative Analyst is a professional who uses mathematical and statistical methods to analyze financial data. Quantitative Analysts often work for investment banks, hedge funds, and other financial institutions. The LSE MicroBachelors program in Statistics Fundamentals can provide you with a strong foundation in the mathematical and statistical methods that are needed to succeed in this career.
Actuary
An Actuary is a professional who uses mathematical and statistical methods to assess risk. Actuaries often work for insurance companies, pension funds, and other financial institutions. The LSE MicroBachelors program in Statistics Fundamentals can provide you with a strong foundation in the mathematical and statistical methods that are needed to succeed in this career.
Biostatistician
A Biostatistician is a professional who uses statistical methods to design and analyze experiments in the biological sciences. Biostatisticians often work for pharmaceutical companies, hospitals, and other healthcare organizations. The LSE MicroBachelors program in Statistics Fundamentals can provide you with a strong foundation in the statistical methods that are needed to succeed in this career.
Risk Manager
A Risk Manager is a professional who identifies, assesses, and manages risk. Risk Managers often work for banks, insurance companies, and other financial institutions. The LSE MicroBachelors program in Statistics Fundamentals can provide you with a strong foundation in the statistical methods that are needed to succeed in this career.
Market Researcher
A Market Researcher is a professional who collects, analyzes, and interprets data about consumer behavior. Market Researchers often work for marketing firms, advertising agencies, and other businesses. The LSE MicroBachelors program in Statistics Fundamentals can provide you with a strong foundation in the statistical methods that are needed to succeed in this career.
Operations Research Analyst
An Operations Research Analyst is a professional who uses mathematical and statistical methods to improve the efficiency of operations. Operations Research Analysts often work for manufacturing companies, logistics companies, and other businesses. The LSE MicroBachelors program in Statistics Fundamentals can provide you with a strong foundation in the mathematical and statistical methods that are needed to succeed in this career.
Survey Researcher
A Survey Researcher is a professional who designs, conducts, and analyzes surveys. Survey Researchers often work for market research firms, government agencies, and other organizations. The LSE MicroBachelors program in Statistics Fundamentals can provide you with a strong foundation in the statistical methods that are needed to succeed in this career.
Data Analyst
A Data Analyst is a professional who collects, analyzes, and interprets data. Data Analysts often work for businesses, government agencies, and other organizations. The LSE MicroBachelors program in Statistics Fundamentals can provide you with a strong foundation in the statistical methods that are needed to succeed in this career.
Business Analyst
A Business Analyst is a professional who analyzes business data to identify opportunities for improvement. Business Analysts often work for businesses, government agencies, and other organizations. The LSE MicroBachelors program in Statistics Fundamentals can provide you with a strong foundation in the statistical methods that are needed to succeed in this career.
Financial Analyst
A Financial Analyst is a professional who analyzes financial البيانات to make investment decisions. Financial Analysts often work for investment banks, hedge funds, and other financial institutions. The LSE MicroBachelors program in Statistics Fundamentals can provide you with a strong foundation in the statistical methods that are needed to succeed in this career.
Health Statistician
A Health Statistician is a professional who collects, analyzes, and interprets health data. Health Statisticians often work for government agencies, hospitals, and other healthcare organizations. The LSE MicroBachelors program in Statistics Fundamentals can provide you with a strong foundation in the statistical methods that are needed to succeed in this career.
Software Engineer
A Software Engineer is a professional who designs, develops, and maintains software applications. Software Engineers often work for software companies, government agencies, and other organizations. While the LSE MicroBachelors program in Statistics Fundamentals is not directly related to software engineering, it can provide you with a strong foundation in the mathematical and statistical methods that are used in this field.
Data Engineer
A Data Engineer is a professional who designs, builds, and maintains data pipelines. Data Engineers often work for businesses, government agencies, and other organizations. While the LSE MicroBachelors program in Statistics Fundamentals is not directly related to data engineering, it can provide you with a strong foundation in the statistical methods that are used in this field.

Reading list

We've selected 13 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 Statistics Fundamentals Proctored Exam.
This popular textbook comprehensive guide to modern statistical learning methods, with a focus on applications in R. It covers a wide range of topics, including supervised and unsupervised learning, model selection, and regularization.
This widely used textbook provides a thorough introduction to probability and statistics, with a focus on applications in engineering and the sciences. It covers a wide range of topics, including probability theory, random variables, statistical inference, and regression analysis.
This concise textbook provides a clear and accessible introduction to the fundamentals of statistical inference. It covers a wide range of topics, including probability theory, sampling distributions, hypothesis testing, and regression analysis.
This textbook provides a contemporary introduction to statistical methods, with a focus on applications in R. It covers a wide range of topics, including data visualization, statistical modeling, and machine learning.
This open-source textbook provides a comprehensive and accessible introduction to statistics. It covers a wide range of topics, including probability theory, statistical inference, and regression analysis.
This textbook provides a thorough and rigorous introduction to the fundamentals of mathematical statistics. It covers a wide range of topics, including probability theory, statistical inference, and regression analysis.
This textbook provides a comprehensive introduction to statistical methods for the social sciences. It covers a wide range of topics, including probability theory, statistical inference, and regression analysis.
This classic textbook provides a comprehensive and rigorous treatment of statistical inference. It covers a wide range of topics, including point estimation, interval estimation, and hypothesis testing.
This textbook provides a comprehensive and rigorous treatment of the theory of statistics. It covers a wide range of topics, including probability theory, statistical inference, and decision theory.
This textbook provides a comprehensive and rigorous treatment of mathematical statistics. It covers a wide range of topics, including probability theory, statistical inference, and decision theory.
This textbook provides a comprehensive and up-to-date introduction to Bayesian statistics. It covers a wide range of topics, including Bayesian inference, Bayesian modeling, and Bayesian computation.

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