Statistics 1 Part 2: Statistical Methods from edX

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.

What you'll learn

By the end of this course, you will:

be familiar with some further 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 when required
To explain the fundamentals of statistical inference and perform inference to test the significance of common measures such as means and proportions and conduct chi-squared tests of contingency tables
be able to use simple linear regression and correlation analysis and know when it is appropriate to do so

What's inside

Syllabus

● Hypothesis testing I

● Hypothesis testing II

● Contingency tables and the chi-squared test

● Sampling design and some ideas underlying causation

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Introduces intermediate level statistical concepts for students with moderate mathematical competence

Emphasizes real-world applications of statistical methods in fields such as management, economics, and social sciences

Provides foundational knowledge in statistical inference and hypothesis testing, which are crucial for data analysis

Covers sampling design and causation, essential concepts for understanding data collection and interpretation

Includes linear regression and correlation analysis, widely used techniques for data modeling and prediction

Reviews summary

Lse's applied statistical methods for social sciences

According to students, this course provides a strong theoretical and conceptual foundation in statistical methods, with a particular emphasis on real-world application and interpretation for management, economics, and social sciences. While many found the lectures clear and comprehensive, a significant number of learners highlighted its challenging pace and the need for a solid prior statistical or mathematical background, making it less suitable for absolute beginners. A recurring point of feedback is the limited practical application using statistical software, suggesting it focuses more on 'why' than 'how'. It is largely seen as a valuable continuation of Part 1.

Serves as a strong and natural follow-up to Part 1.

"It built well on Part 1, but I think someone with a strong basic stats understanding could jump in."

"An incredibly well-structured course! The logical progression from Part 1 into advanced topics... was seamless."

"Perfect continuation of Part 1. The focus on interpretation and application is spot on for social sciences."

Emphasizes application in economics and social sciences.

"The lectures were clear and the examples were very relevant to economics. I found the practical applications invaluable."

"The emphasis on interpretation of results rather than just calculations was a huge plus. This is exactly what I needed for my management studies."

"Perfect continuation of Part 1. The focus on interpretation and application is spot on for social sciences."

Builds robust conceptual and theoretical understanding.

"This course provided an excellent foundation in statistical methods, especially hypothesis testing and regression."

"An incredibly well-structured course! The logical progression from Part 1 into advanced topics like hypothesis testing and regression was seamless."

"The explanations are rigorous yet accessible, provided you have a good grasp of the basics (from Part 1)."

Less focus on hands-on application with statistical software.

"It's quite theoretical, and I wished for more hands-on examples using software."

"My main critique is that sometimes the examples were a bit too abstract, and I really craved more practical exercises."

"My only minor gripe is the lack of practical assignments using statistical software – it's mostly theoretical and conceptual..."

"It's geared more towards understanding the 'why' than the 'how' with software."

Requires solid prior statistical or mathematical knowledge.

"Good overview of statistical concepts... sometimes assumed a higher level of prior knowledge."

"I struggled with the pace. If you don't have a solid math background, you'll find this tough."

"Found this course very difficult and frustrating. Definitely not for beginners. I think Part 1 is essential, and maybe even more background."

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 1 Part 2: Statistical Methods with these activities:

Seek guidance from a statistician or data scientist

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Connect with an expert in the field to gain insights and support.

Browse courses on Statistics

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Identify potential mentors from your network or online platforms.
Reach out to mentors and request their guidance.
Meet regularly to discuss your progress and seek advice.

Review basic probability concepts

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Ensure a strong foundation in probability to support your understanding of statistical concepts.

Browse courses on Probability

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Revisit your notes or textbooks on basic probability concepts.
Solve practice problems to test your understanding.
Identify areas where you need additional clarification and seek support from resources or a tutor.

Read "Introduction to Statistical Inference" by Gareth James et al.

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Gain a comprehensive understanding of statistical inference from a highly regarded textbook.

View An Introduction to Statistical Learning on Amazon

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Read each chapter thoroughly and take notes.
Work through the practice problems at the end of each chapter.
Highlight important concepts and make marginal notes for future reference.

Five other activities

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Learn R for statistical analysis

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Become familiar with the R programming language to perform statistical analysis on data sets.

Browse courses on R

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Follow the R tutorial for beginners.
Practice writing R code to perform basic statistical operations.
Explore the R documentation to learn more about specific functions.

Solve practice problems on statistical inference

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Reinforce your understanding of statistical inference by solving practice problems.

Browse courses on Statistical Inference

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Attempt to solve practice problems from the course textbook.
Compare your solutions with the answer key to identify areas for improvement.
Seek clarification from the instructor or a tutor if needed.

Participate in a study group for hypothesis testing

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Collaborate with peers to discuss and understand hypothesis testing concepts.

Browse courses on Hypothesis Testing

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Find a study group or form one with classmates.
Meet regularly to discuss lecture material and practice problems.
Work together to solve challenging problems and explain concepts to each other.

Create a data visualization of a statistical dataset

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Develop your skills in presenting statistical data visually.

Browse courses on Data Visualization

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Choose a dataset and identify the key variables to visualize.
Select an appropriate data visualization technique (e.g., bar chart, scatter plot, histogram).
Use a data visualization tool (e.g., Tableau, Python) to create the visualization.

Contribute to an open-source statistical project

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Gain practical experience and deepen your understanding of statistical techniques by contributing to an open-source project.

Browse courses on Open Source

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Identify an open-source statistical project that aligns with your interests.
Familiarize yourself with the project's codebase and documentation.
Identify a specific issue or feature to work on.

Career center

Learners who complete Statistics 1 Part 2: Statistical Methods will develop knowledge and skills that may be useful to these careers:

Statistician

Statisticians use statistical methods to collect, analyze, interpret, and present data. This course in Statistical Methods will provide you with a solid foundation in the essential concepts and methods used by Statisticians. You will learn about hypothesis testing, contingency tables, sampling design, correlation, and linear regression, which are all core techniques used in statistical analysis. This course will help you develop the skills needed to design and conduct statistical studies, analyze data, and draw valid conclusions, which are essential for a successful career as a Statistician.

See salaries and explore the career path for Statistician

Data Analyst

Data Analysts apply statistical methods to analyze data to extract meaningful insights and identify trends. By taking this course in Statistical Methods, you will learn about essential statistical concepts and methods and develop the skills needed to analyze data effectively. This course covers hypothesis testing, contingency tables, sampling design, correlation, and linear regression, which are all fundamental techniques used by Data Analysts. The knowledge and skills gained from this course will provide you with a strong foundation for a successful career as a Data Analyst.

See salaries and explore the career path for Data Analyst

Market Researcher

Market Researchers use statistical methods to collect, analyze, and interpret data about markets and consumers. This course in Statistical Methods will provide you with the essential statistical concepts and methods needed to be successful in this field. You will learn about hypothesis testing, contingency tables, sampling design, correlation, and linear regression, which are all techniques used by Market Researchers to analyze data and make informed decisions. This course will help you develop the skills needed to design and conduct market research studies, analyze data, and present your findings effectively.

See salaries and explore the career path for Market Researcher

Data Scientist

Data Scientists use statistical methods to extract knowledge from data. This course in Statistical Methods will provide you with the essential statistical concepts and methods needed to be successful in this field. You will learn about hypothesis testing, contingency tables, sampling design, correlation, and linear regression, which are all techniques used by Data Scientists to analyze data and make informed decisions. This course will help you develop the skills needed to extract knowledge from data, identify trends, and make predictions.

See salaries and explore the career path for Data Scientist

Financial Analyst

Financial Analysts use statistical methods to analyze financial data and make investment recommendations. This course in Statistical Methods will provide you with the essential statistical concepts and methods needed to be successful in this field. You will learn about hypothesis testing, contingency tables, sampling design, correlation, and linear regression, which are all techniques used by Financial Analysts to analyze financial data and make informed decisions. This course will help you develop the skills needed to analyze financial data, identify trends, and make sound investment recommendations.

See salaries and explore the career path for Financial Analyst

Quantitative Analyst

Quantitative Analysts use statistical methods to analyze financial data and make investment decisions. This course in Statistical Methods will provide you with the essential statistical concepts and methods needed to be successful in this field. You will learn about hypothesis testing, contingency tables, sampling design, correlation, and linear regression, which are all techniques used by Quantitative Analysts to analyze financial data and make informed decisions. This course will help you develop the skills needed to analyze financial data, identify trends, and make sound investment decisions.

See salaries and explore the career path for Quantitative Analyst

Actuary

Actuaries use statistical methods to assess and manage risk. This course in Statistical Methods will provide you with the essential statistical concepts and methods needed to be successful in this field. You will learn about hypothesis testing, contingency tables, sampling design, correlation, and linear regression, which are all techniques used by Actuaries to analyze data and make informed decisions. This course will help you develop the skills needed to assess and manage risk, and make sound decisions in the face of uncertainty.

See salaries and explore the career path for Actuary

Operations Research Analyst

Operations Research Analysts use statistical methods to improve the efficiency and effectiveness of business operations. This course in Statistical Methods will provide you with the essential statistical concepts and methods needed to be successful in this field. You will learn about hypothesis testing, contingency tables, sampling design, correlation, and linear regression, which are all techniques used by Operations Research Analysts to analyze data and make informed decisions. This course will help you develop the skills needed to analyze data, identify inefficiencies, and develop solutions to improve business operations.

See salaries and explore the career path for Operations Research Analyst

Biostatistician

Biostatisticians use statistical methods to analyze data in the biomedical field. This course in Statistical Methods will provide you with the essential statistical concepts and methods needed to be successful in this field. You will learn about hypothesis testing, contingency tables, sampling design, correlation, and linear regression, which are all techniques used by Biostatisticians to analyze biomedical data and make informed decisions. This course will help you develop the skills needed to analyze biomedical data, identify trends, and make sound decisions in the biomedical field.

See salaries and explore the career path for Biostatistician

Epidemiologist

Epidemiologists use statistical methods to investigate the causes and patterns of disease. This course in Statistical Methods will provide you with the essential statistical concepts and methods needed to be successful in this field. You will learn about hypothesis testing, contingency tables, sampling design, correlation, and linear regression, which are all techniques used by Epidemiologists to analyze data and make informed decisions. This course will help you develop the skills needed to analyze epidemiological data, identify trends, and make sound decisions in the field of public health.

See salaries and explore the career path for Epidemiologist

Survey Researcher

Survey Researchers use statistical methods to design and conduct surveys, and analyze the data collected from those surveys. This course in Statistical Methods will provide you with the essential statistical concepts and methods needed to be successful in this field. You will learn about hypothesis testing, contingency tables, sampling design, correlation, and linear regression, which are all techniques used by Survey Researchers to analyze data and make informed decisions. This course will help you develop the skills needed to design and conduct surveys, analyze survey data, and make sound decisions based on the results.

See salaries and explore the career path for Survey Researcher

Business Analyst

Business Analysts use statistical methods to analyze data and make recommendations to improve business performance. This course in Statistical Methods will provide you with the essential statistical concepts and methods needed to be successful in this field. You will learn about hypothesis testing, contingency tables, sampling design, correlation, and linear regression, which are all techniques used by Business Analysts to analyze data and make informed decisions. This course will help you develop the skills needed to analyze business data, identify trends, and make sound recommendations to improve business performance.

See salaries and explore the career path for Business Analyst

Risk Manager

Risk Managers use statistical methods to assess and manage risk. This course in Statistical Methods will provide you with the essential statistical concepts and methods needed to be successful in this field. You will learn about hypothesis testing, contingency tables, sampling design, correlation, and linear regression, which are all techniques used by Risk Managers to analyze data and make informed decisions. This course will help you develop the skills needed to assess and manage risk, and make sound decisions in the face of uncertainty.

See salaries and explore the career path for Risk Manager

Social Scientist

Social Scientists use statistical methods to analyze data about human behavior and society. This course in Statistical Methods will provide you with the essential statistical concepts and methods needed to be successful in this field. You will learn about hypothesis testing, contingency tables, sampling design, correlation, and linear regression, which are all techniques used by Social Scientists to analyze data and make informed decisions. This course will help you develop the skills needed to analyze social data, identify trends, and make sound decisions in the field of social science.

See salaries and explore the career path for Social Scientist

Economist

Economists use statistical methods to analyze economic data and make predictions about the economy. This course in Statistical Methods will provide you with the essential statistical concepts and methods needed to be successful in this field. You will learn about hypothesis testing, contingency tables, sampling design, correlation, and linear regression, which are all techniques used by Economists to analyze data and make informed decisions. This course will help you develop the skills needed to analyze economic data, identify trends, and make sound predictions about the economy.

See salaries and explore the career path for Economist