Statistics 1 Part 1

Course Description

Welcome to Statistics 1 Part 1, an engaging and comprehensive course offered by the prestigious London School of Economics and Political Science (LSE). This self-paced course is designed to introduce you to the fascinating world of statistics, providing you with a solid foundation in essential concepts, methods, and techniques. What sets this course apart is its emphasis on practical applications, making it especially valuable for those interested in management, economics, and social sciences.

What Students Will Learn

• A strong familiarity with key statistical ideas, accessible to students with moderate mathematical competence.
• The ability to routinely apply various methods for explaining, summarizing, and presenting data.
• Skills in interpreting results clearly using appropriate diagrams, titles, and labels.
• A solid grounding in probability theory, which is crucial for advanced statistical analysis.

Prerequisites

The beauty of Statistics 1 Part 1 is that it assumes no prior knowledge of statistics. However, a moderate level of mathematical competence will be beneficial. It's strongly recommended to progress to Statistics 1 Part 2 after completing this course, given the cumulative nature of the subject matter.

Course Content

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

Who This Course Is For

• Students seeking a strong foundation in statistics
• Professionals in management, economics, or social sciences looking to enhance their analytical skills
• Anyone interested in understanding and applying statistical methods in real-world scenarios
• Learners pursuing the LSE MicroBachelors program in Statistics Fundamentals or Mathematics and Statistics Fundamentals

Real-World Applications

The skills acquired in this course have wide-ranging applications in the real world. You'll be able to:

• Analyze and interpret complex data sets in various professional settings
• Make informed decisions based on statistical evidence
• Enhance your research capabilities in academic or professional contexts
• Improve your understanding of economic and social trends through statistical analysis
• Contribute more effectively to data-driven projects in your workplace

Syllabus

1. Mathematical revision and the nature of statistics
2. Data visualization and descriptive statistics
3. Probability theory
4. The normal distribution and ideas of sampling
5. Point and interval estimation