Statistics Fundamentals

London School of Economics and Political Science via edX Microbachelors

Overview

This comprehensive MicroBachelors program in Statistics Fundamentals introduces students to the essential statistical concepts, methods and techniques which they can use to grow their skills in quantitative careers, or as a step towards further study at undergraduate level or in specialised subjects.

 Spanning four individual courses, all of which are self-paced and asynchronous, this programme provides students with maximum flexibility to learn with a world-leading institution from anywhere in the world in a way that fits their schedule. Students will first be introduced to core statistical concepts and gain essential skills to analyse, summarise, and present data, before progressing to probability, distribution theory and statistical inference.

  These courses are based on service-level statistics courses offered as part of the University of London degree programmes in Economics, Management, Finance and the Social Sciences (EMFSS), with academic direction from the London School of Economics and Political Science (LSE). They equip students with the fundamental statistical knowledge and tools to set them up for success in second and third-year courses in subjects such as economics, finance, data science, mathematics, statistics, business analytics and programming.

 Those that complete this MicroBachelors program may wish to go on to apply to the University of London's academically rigorous EMFSS degree programmes that give learners the opportunity to earn a BSc from a top London university wherever they are in the world.

 Should you wish, you may elect to just study some of the individual courses within the MicroBachelors program, perhaps to build or refresh quantitative skills for career advancement.

 No prior statistics knowledge is required for this programme.

Statistics 1a: Introductory statistics, probability and estimation

Mathematical revision and the nature of statistics
Data visualisation and descriptive statistics
Probability theory
The normal distribution and ideas of sampling
Point and interval estimation

Statistics 1b: Statistical methods

Hypothesis testing I
Hypothesis testing II
Contingency tables and the chi-squared test
Sampling design and some ideas underlying causation
Correlation and linear regression

Statistics 2a: Probability and distribution theory

Probability theory I
Probability theory II
Random variables
Common distributions of random variables
Multivariate random variables

Statistics 2b: Statistical inference

Sampling distributions of statistics
Point estimation I
Point estimation II and interval estimation
Hypothesis testing
Analysis of variance (ANOVA)

Syllabus

Courses under this program:
Course 1: Statistics 1 Part 1: Introductory statistics, probability and estimation

The first in a series of four courses which help you to master statistics fundamentals and build your quantitative skillset for progression in high-growth careers, or to use as step towards further study at undergraduate level.

Course 2: Statistics 1 Part 2: Statistical Methods

The second in a series of four courses which help you to master statistics fundamentals and build your quantitative skillset for progression in high-growth careers, or to use as step towards further study at undergraduate level.

Course 3: Statistics 2 Part 1: Probability and Distribution Theory

The third in a series of four courses which help you to master statistics fundamentals and build your quantitative skillset for progression in high-growth careers, or to use as step towards further study at undergraduate level.

Course 4: Statistics 2 Part 2: Statistical Inference

The final part in a series of four courses which help you to master statistics fundamentals and build your quantitative skillset for progression in high-growth careers, or to use as step towards further study at undergraduate level.

Course 5: Statistics Fundamentals Proctored Exam

Test your knowledge and ability to apply the concepts and methods from the four courses included in the LSE MicroBachelors program in Statistics Fundamentals and take your first step towards further study at undergraduate level or upskill in high-growth careers.

Courses

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5 weeks, 12-15 hours a week, 12-15 hours a week
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Statistics 2 Part 2 is a self-paced course from LSE which aims to develop your knowledge of elementary statistical theory, particularly relating to the concepts, methods and techniques of measurement and hypothesis testing that were introduced in Statistics 1 and Statistics 2, Part 1. This course can be taken alone or as part of the LSE MicroBachelors program in Statistics Fundamentals.

Part 2, Statistical Inference, covers the following topics:

● Sampling distributions of statistics

● Point estimation I

● Point estimation II and interval estimation

● Hypothesis testing

● Analysis of variance (ANOVA)

There is an emphasis on topics that relate to econometrics, finance and quantitative social science. Concepts and methods that provide the foundations for more specialised courses in statistics and econometrics are introduced.
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5 weeks, 12-15 hours a week, 12-15 hours a week
View details

Statistics 1 Part 1 is a self-paced course from LSE which aims to introduce you to and develop your understanding of essential statistical concepts, methods and techniques, emphasising the applications of these methods. This course can be taken alone or as part of the LSE MicroBachelors program in Statistics Fundamentals or the LSE MicroBachelors program in Mathematics and Statistics Fundamentals.

Part 1, Introductory Statistics, Probability and Estimation, covers the following topics:

● Mathematical revision and the nature of statistics

● Data visualisation and descriptive statistics

● Probability theory

● The normal distribution and ideas of sampling

● Point and interval estimation

Statistics 1 Part 1 forms part of a series of courses which focuses on the application of statistical methods in management, economics and the social sciences. During this course, you will focus on the interpretation of tables and results, and how to approach statistical problems effectively.
0 reviews
5 weeks, 12-15 hours a week, 12-15 hours a week
View details

Statistics 2 Part 1 is a self-paced course from LSE which aims to develop your knowledge of elementary statistical theory, particularly relating to the concepts, methods and techniques of measurement and hypothesis testing that were introduced in Statistics 1, Parts 1 and 2. This course can be taken alone or as part of the LSE MicroBachelors program in Statistics Fundamentals.

Part 1, Probability and Distribution Theory, covers the following topics:

● Probability theory I

● Probability theory II

● Random variables

● Common distributions of random variables

● Multivariate random variables

There is an emphasis on topics that relate to econometrics, finance and quantitative social science. Concepts and methods that provide the foundations for more specialised undergraduate-level courses in statistics and econometrics are introduced.
0 reviews
5 weeks, 12-15 hours a week, 12-15 hours a week
View details

Statistics 1 Part 2 is a self-paced course from LSE which aims to introduce you to and develop your understanding of essential statistical concepts, methods and techniques, emphasising the applications of these methods. This course can be taken alone or as part of the LSE MicroBachelors program in Statistics Fundamentals or the LSE MicroBachelors program in Mathematics and Statistics Fundamentals.

Part 2, Statistical Methods, covers the following topics:

● Hypothesis testing I

● Hypothesis testing II

● Contingency tables and the chi-squared test

● Sampling design and some ideas underlying causation

● Correlation and linear regression

Statistics 1 Part 2 forms part of a series of courses which focuses on the application of statistical methods in management, economics and the social sciences. Attention will focus on how to approach statistical problems, as well as the interpretation of tables and results.