Basic Statistics from Coursera

Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This course will also prepare you for the next course in the specialization - the course Inferential Statistics.

In the first part of the course we will discuss methods of descriptive statistics. You will learn what cases and variables are and how you can compute measures of central tendency (mean, median and mode) and dispersion (standard deviation and variance). Next, we discuss how to assess relationships between variables, and we introduce the concepts correlation and regression.

The second part of the course is concerned with the basics of probability: calculating probabilities, probability distributions and sampling distributions. You need to know about these things in order to understand how inferential statistics work.

The third part of the course consists of an introduction to methods of inferential statistics - methods that help us decide whether the patterns we see in our data are strong enough to draw conclusions about the underlying population we are interested in. We will discuss confidence intervals and significance tests.

You will not only learn about all these statistical concepts, you will also be trained to calculate and generate these statistics yourself using freely available statistical software.

What's inside

Syllabus

Before we get started...

In this module we'll consider the basics of statistics. But before we start, we'll give you a broad sense of what the course is about and how it's organized. Are you new to Coursera or still deciding whether this is the course for you? Then make sure to check out the 'Course introduction' and 'What to expect from this course' sections below, so you'll have the essential information you need to decide and to do well in this course! If you have any questions about the course format, deadlines or grading, you'll probably find the answers here. Are you a Coursera veteran and ready to get started? Then you might want to skip ahead to the first course topic: 'Exploring data'. You can always check the general information later. Veterans and newbies alike: Don't forget to introduce yourself in the 'meet and greet' forum!

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Prepares learners to take the next course in this series. This shows a logical progression and supports the development of complex knowledge and skills

Teaches foundational statistical concepts, providing learners with a strong basis for future study

Includes an introduction to inferential statistics, which helps learners understand how to draw conclusions from data

Teaches descriptive statistics, a core part of data analysis used in many fields

Covers correlation and regression, which are widely used in research and data analysis

Provides a solid foundation in probability, which is fundamental for statistical inference

Reviews summary

Foundational statistics with theoretical depth

Learners say this course provides a solid theoretical foundation in basic statistics, with many praising the instructor's clear explanations of fundamental concepts like descriptive statistics, probability, and inferential statistics. Students find it a good starting point, particularly for understanding the 'why' behind statistical methods. However, some note that the course is heavily theoretical and that the assignments can be quite challenging, sometimes feeling disconnected from lecture content. While effective for conceptual understanding and preparation for further study, learners suggest it may require additional resources for hands-on application and practice.

Focuses heavily on underlying statistical theory.

"This course is very theoretical, which is great for understanding principles."

"It gives you a deep understanding of the concepts, less focus on practical software use."

"If you want to know the 'why' behind stats, this is good. If you want practical skills, maybe less so."

Excellent preparation for subsequent courses.

"This course laid an excellent foundation for the next course in the specialization."

"It covers the essential basics needed before moving on to more advanced topics."

"Feel much better prepared for inferential statistics after taking this."

Concepts are explained clearly and effectively.

"The instructor explains the concepts very clearly and makes them easy to understand."

"I finally grasped probability distributions thanks to the way it was taught here."

"Lectures were well-structured and easy to follow, even for complex topics."

Requires external practice for application.

"You need to find your own practice problems to really solidify your understanding."

"The course is heavy on theory but light on hands-on examples or exercises."

"Good course, but plan to supplement with practice outside the platform."

Homework and quizzes can be quite challenging.

"The assignments were significantly harder than I expected based on the lectures."

"I struggled a lot with the homework problems; they required skills not fully taught."

"Some quiz questions seemed tricky or not directly related to the course material."

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 Basic Statistics with these activities:

Review Probability and Statistics

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Brush up on basic concepts of probability and statistics to strengthen your foundation for the course.

Browse courses on Probability

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Revisit textbooks or online resources on probability and statistics.
Solve practice problems and exercises to test your understanding.

Organize and Review Course Materials

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Stay organized by compiling and reviewing course materials regularly to reinforce your learning.

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Gather notes, assignments, quizzes, and exams.
Create a system for organizing and storing these materials.
Periodically review the materials to refresh your memory.

Solve Practice Problems

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Regular practice with problem-solving strengthens your grasp of statistical concepts and prepares you for assessments.

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Access problem sets from the course materials or external sources.
Attempt to solve the problems independently.
Review solutions and learn from your mistakes.

Four other activities

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Participate in Discussion Forums and Study Groups

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Engage with peers to discuss course concepts, clarify doubts, and deepen your understanding through collaborative learning.

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Join online discussion forums or form study groups.
Actively participate in discussions and ask questions.
Collaborate with peers on projects or assignments.

Explore Online Tutorials and Simulations

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Seek out additional learning resources to enhance your understanding of specific statistical techniques.

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Identify areas where you need additional support.
Search for tutorials or simulations that address those specific topics.
Work through the tutorials or simulations at your own pace.

Volunteer at a Research Project

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Gain hands-on experience in a research setting, applying statistical methods to real-world problems and contributing to the advancement of knowledge.

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Identify research projects or organizations where you can volunteer your time.
Apply your statistical skills to assist with data collection, analysis, or interpretation.
Learn from experienced researchers and gain insights into the practical applications of statistics.

Develop a Statistical Model

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Challenge yourself by creating a statistical model that addresses a real-world problem, expanding your practical skills and showcasing your abilities.

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Identify a problem or issue that can be addressed using statistical methods.
Gather and analyze relevant data.
Develop and implement a statistical model.
Evaluate the performance of your model.
Present your findings in a clear and concise manner.

Career center

Learners who complete Basic Statistics will develop knowledge and skills that may be useful to these careers:

Statistician

Statisticians apply statistical methods to collect and analyze data, interpret results, and make recommendations. This course can help build a foundation of basic statistical concepts for those who wish to enter this field. The course teaches students how to calculate and interpret measures of central tendency, dispersion, and correlation. It also introduces the basics of probability and probability distributions, which are essential for understanding how to make inferences from data.

See salaries and explore the career path for Statistician

Data Analyst

Data analysts use their knowledge of statistics and data analysis techniques to help organizations make informed decisions. This course can help build a foundation of basic statistical concepts for those who wish to enter this field. The course teaches students how to calculate and interpret measures of central tendency, dispersion, and correlation. It also introduces the basics of probability and probability distributions, which are essential for understanding how to analyze data.

See salaries and explore the career path for Data Analyst

Market Researcher

Market researchers use statistical methods to collect and analyze data about consumers and markets. This course can help build a foundation of basic statistical concepts for those who wish to enter this field. The course teaches students how to calculate and interpret measures of central tendency, dispersion, and correlation. It also introduces the basics of probability and probability distributions, which are essential for understanding how to make inferences from data.

See salaries and explore the career path for Market Researcher

Financial Analyst

Financial analysts use statistical methods to analyze financial data and make recommendations about investments. This course can help build a foundation of basic statistical concepts for those who wish to enter this field. The course teaches students how to calculate and interpret measures of central tendency, dispersion, and correlation. It also introduces the basics of probability and probability distributions, which are essential for understanding how to analyze financial data.

See salaries and explore the career path for Financial Analyst

Actuary

Actuaries use statistical methods to assess risk and uncertainty. This course can help build a foundation of basic statistical concepts for those who wish to enter this field. The course teaches students how to calculate and interpret measures of central tendency, dispersion, and correlation. It also introduces the basics of probability and probability distributions, which are essential for understanding how to assess risk and uncertainty.

See salaries and explore the career path for Actuary

Epidemiologist

Epidemiologists use statistical methods to study the distribution and determinants of health-related states or events. This course can help build a foundation of basic statistical concepts for those who wish to enter this field. The course teaches students how to calculate and interpret measures of central tendency, dispersion, and correlation. It also introduces the basics of probability and probability distributions, which are essential for understanding how to analyze epidemiological data.

See salaries and explore the career path for Epidemiologist

Biostatistician

Biostatisticians use statistical methods to design and analyze studies in the field of biology. This course can help build a foundation of basic statistical concepts for those who wish to enter this field. The course teaches students how to calculate and interpret measures of central tendency, dispersion, and correlation. It also introduces the basics of probability and probability distributions, which are essential for understanding how to analyze biological data.

See salaries and explore the career path for Biostatistician

Survey Researcher

Survey researchers use statistical methods to design and analyze surveys. This course can help build a foundation of basic statistical concepts for those who wish to enter this field. The course teaches students how to calculate and interpret measures of central tendency, dispersion, and correlation. It also introduces the basics of probability and probability distributions, which are essential for understanding how to design and analyze surveys.

See salaries and explore the career path for Survey Researcher

Operations Research Analyst

Operations research analysts use statistical methods to improve the efficiency of organizations. This course can help build a foundation of basic statistical concepts for those who wish to enter this field. The course teaches students how to calculate and interpret measures of central tendency, dispersion, and correlation. It also introduces the basics of probability and probability distributions, which are essential for understanding how to analyze operational data.

See salaries and explore the career path for Operations Research Analyst

Quality Control Inspector

Quality control inspectors use statistical methods to ensure that products and services meet quality standards. This course can help build a foundation of basic statistical concepts for those who wish to enter this field. The course teaches students how to calculate and interpret measures of central tendency, dispersion, and correlation. It also introduces the basics of probability and probability distributions, which are essential for understanding how to ensure quality.

See salaries and explore the career path for Quality Control Inspector

Risk Manager

Risk managers use statistical methods to assess and manage risk. This course may be useful for those who wish to enter this field. The course introduces the basics of probability and probability distributions, which are essential for understanding how to assess and manage risk.

See salaries and explore the career path for Risk Manager

Business Analyst

Business analysts use statistical methods to analyze business data and make recommendations. This course may be useful for those who wish to enter this field. The course teaches students how to calculate and interpret measures of central tendency, dispersion, and correlation.

See salaries and explore the career path for Business Analyst

Data Scientist

Data scientists use statistical methods to analyze data and make predictions. This course may be useful for those who wish to enter this field. The course teaches students how to calculate and interpret measures of central tendency, dispersion, and correlation. It also introduces the basics of probability and probability distributions.

See salaries and explore the career path for Data Scientist

Software Engineer

Software engineers use statistical methods to develop and test software. This course may be useful for those who wish to enter this field. The course teaches students how to calculate and interpret measures of central tendency, dispersion, and correlation.

See salaries and explore the career path for Software Engineer

Quantitative Analyst

Quantitative analysts use statistical methods to analyze financial data and make recommendations. This course may be useful for those who wish to enter this field. The course teaches students how to calculate and interpret measures of central tendency, dispersion, and correlation.

See salaries and explore the career path for Quantitative Analyst