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James Abdey

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

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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
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● Correlation and linear regression

Good to know

Know what's good
, what to watch for
, 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

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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
Connect with an expert in the field to gain insights and support.
Browse courses on Statistics
Show steps
  • 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
Ensure a strong foundation in probability to support your understanding of statistical concepts.
Browse courses on Probability
Show steps
  • 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.
Gain a comprehensive understanding of statistical inference from a highly regarded textbook.
Show steps
  • 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
Expand to see all activities and additional details
Show all eight activities
Learn R for statistical analysis
Become familiar with the R programming language to perform statistical analysis on data sets.
Browse courses on R
Show steps
  • 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
Reinforce your understanding of statistical inference by solving practice problems.
Browse courses on Statistical Inference
Show steps
  • 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
Collaborate with peers to discuss and understand hypothesis testing concepts.
Browse courses on Hypothesis Testing
Show steps
  • 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
Develop your skills in presenting statistical data visually.
Browse courses on Data Visualization
Show steps
  • 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
Gain practical experience and deepen your understanding of statistical techniques by contributing to an open-source project.
Browse courses on Open Source
Show steps
  • 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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.

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 1 Part 2: Statistical Methods.
Comprehensive guide to statistical methods for psychology. It covers a wide range of topics, including descriptive statistics, hypothesis testing, regression analysis, and ANOVA.
Comprehensive guide to statistical methods and techniques for the social sciences. It covers a wide range of topics, including descriptive statistics, hypothesis testing, regression analysis, and ANOVA.
Comprehensive introduction to mathematical statistics. It covers a wide range of topics, including probability theory, estimation, and hypothesis testing.
Comprehensive guide to statistical methods for social work. It covers a wide range of topics, including descriptive statistics, probability, hypothesis testing, and regression analysis.
Comprehensive guide to statistical methods for business and economics. It covers a wide range of topics, including descriptive statistics, probability, hypothesis testing, and regression analysis.
Comprehensive guide to statistics for lawyers. It covers a wide range of topics, including descriptive statistics, probability, hypothesis testing, and regression analysis.
Provides a modern and accessible introduction to statistical thinking. It covers a wide range of topics, including data visualization, probability, and statistical inference.
Gentle introduction to Bayesian statistics. It covers a wide range of topics, including Bayes' theorem, probability theory, and statistical inference.
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Gentle introduction to statistics, suitable for beginners. It covers a wide range of topics, including descriptive statistics, probability, and hypothesis testing.

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