Course description
Statistics 1 Part 1: Introductory Statistics, Probability and Estimation
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.
Upcoming start dates
Who should attend?
Prerequisites
Statistics 1 Part 1 assumes no prior knowledge of statistics. Essential statistical concepts are introduced and are further built on in Statistics 1 Part 2 (and also in Statistics 2, Parts 1 and 2). It is strongly recommeded to study the LSE statistics courses in order (progressing to Statistics 1, Part 2) given the cumulative nature of the subject matter.
Training content
- 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
Course delivery details
This course is offered through The London School of Economics and Political Science, a partner institute of EdX.
12-15 hours per week
Costs
- Verified Track -$199.2
- Audit Track - Free
Certification / Credits
What you'll learn
By the end of this course, you will:
- be familiar with some key ideas of statistics that are accessible to a student with a moderate mathematical competence
- be able to routinely apply a variety of methods for explaining, summarising and presenting data and interpreting results clearly using appropriate diagrams, titles and labels
- have a grounding in probability theory
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