The Power of Statistics from Coursera

This is the fourth of seven courses in the Google Advanced Data Analytics Certificate. In this course, you’ll discover how data professionals use statistics to analyze data and gain important insights. You'll explore key concepts such as descriptive and inferential statistics, probability, sampling, confidence intervals, and hypothesis testing. You'll also learn how to use Python for statistical analysis and practice communicating your findings like a data professional.

Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you enhance your data analytics skills to prepare for your career.

Learners who complete the seven courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate.

By the end of this course, you will:

-Describe the use of statistics in data science

-Use descriptive statistics to summarize and explore data

-Calculate probability using basic rules

-Model data with probability distributions

-Describe the applications of different sampling methods

-Calculate sampling distributions

-Construct and interpret confidence intervals

-Conduct hypothesis tests

What's inside

Syllabus

Introduction to statistics

You’ll explore the role of statistics in data science and identify the difference between descriptive and inferential statistics. You’ll learn how descriptive statistics can help you quickly summarize a dataset and measure the center, spread, and relative position of data.

Probability

You’ll learn the basic rules for calculating probability for single events. Next, you’ll discover how data professionals use methods such as Bayes’ theorem to describe more complex events. Finally, you’ll learn how probability distributions such as the binomial, Poisson, and normal distribution can help you better understand the structure of data.

Sampling

Data professionals use smaller samples of data to draw conclusions about large datasets. You’ll learn about the different methods they use to collect and analyze sample data and how they avoid sampling bias. You’ll also learn how sampling distributions can help you make accurate estimates.

Confidence intervals

You’ll explore how data professionals use confidence intervals to describe the uncertainty of their estimates. You'll learn how to construct and interpret confidence intervals — and how to avoid some common misinterpretations.

Introduction to hypothesis testing

Hypothesis testing helps data professionals determine if the results of a test or experiment are statistically significant or due to chance. You’ll learn about the basic steps for any hypothesis test and how hypothesis testing can help you draw meaningful conclusions about data.

Course 4 end-of-course project

In this end-of-course project, you’ll use statistical methods such as hypothesis testing to analyze a workplace scenario dataset.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches probability, which is used in data analytics to reason about uncertainty

Teaches sampling, which is crucial for making inferences from small datasets

Provides hands-on activities to simulate real-world tasks faced by data professionals

Assumes prior knowledge of foundational analytical principles, which may not be suitable for complete beginners

Focuses on data analytics, which may not be directly applicable to other fields

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 The Power of Statistics with these activities:

Organize and review class materials

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Keep your class materials structured and accessible for effective revision and retention.

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Create a dedicated folder or binder for the course materials.
Organize materials chronologically or by topic.
Review and summarize key concepts regularly.
Create flashcards or use spaced repetition software to aid memorization.

Review probability basics

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Review the fundamentals of probability to strengthen your understanding of statistical concepts.

Browse courses on Probability

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Read the introductory chapter of a statistics textbook or online resource.
Solve practice problems on basic probability concepts, such as sample space, events, and probability.
Discuss probability concepts with a classmate or online forum.

Participate in a study group

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Collaborate with peers to enhance your understanding and build a support system for learning.

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Find or form a study group with classmates or online.
Meet regularly to review course material, discuss concepts, and solve problems together.
Take turns presenting key concepts to each other.
Provide and receive feedback on each other's work.

Five other activities

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Read 'Statistical Rethinking'

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Expand your statistical knowledge by delving into an advanced text that provides a comprehensive overview of Bayesian statistics.

View Statistical Rethinking on Amazon

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Read selected chapters or sections of the book.
Work through the examples and exercises in the book.
Discuss the book's concepts with classmates or online forums.

Solve hypothesis testing problems

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Practice applying hypothesis testing to real-world situations to enhance your analytical skills.

Browse courses on Hypothesis Testing

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Find a dataset related to your field of interest.
Formulate a hypothesis and research question.
Conduct a hypothesis test using statistical software or online tools.
Interpret the results and draw conclusions.
Compare your findings with published research or discuss them with an expert.

Develop a data visualization for a statistical analysis

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Create a visually appealing representation of data to enhance your understanding and showcase your analytical abilities.

Browse courses on Data Visualization

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Identify a dataset and perform a statistical analysis.
Choose an appropriate data visualization tool.
Design and create a data visualization that effectively communicates your findings.
Present your visualization to others for feedback.

Attend a workshop on advanced statistical techniques

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Enhance your knowledge and skills by attending an industry workshop focused on cutting-edge statistical techniques.

Browse courses on Statistical Analysis

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Research and identify relevant workshops.
Register and attend the workshop.
Actively participate in the workshop activities and discussions.
Follow up with the workshop organizers or speakers after the event.

Mentor a junior data analyst

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Consolidate your knowledge by sharing it with others and fostering the growth of aspiring data analysts.

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Identify a junior data analyst who could benefit from your guidance.
Schedule regular meetings to provide support, answer questions, and offer advice.
Review their work and provide constructive feedback.
Connect them with other professionals in the field.

Career center

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

Data Scientist

Data Scientists play a critical role in industries ranging from healthcare to finance, so those who master this field will find themselves in high demand. This course helps build a foundation for a successful career as a Data Scientist, teaching a range of fundamental statistical methods that are frequently used for analyzing data and uncovering meaningful insights.

See salaries and explore the career path for Data Scientist

Business Analyst

Business Analysts leverage data to improve many aspects of an organization. In order to be successful in this role, a solid understanding of statistics is crucial to be able to comprehend and communicate complex data in a clear manner. This course can help you develop the necessary skills in these areas, making you a well-rounded candidate for Business Analyst positions.

See salaries and explore the career path for Business Analyst

Data Analyst

Data Analysts are tasked with collecting, cleaning, and analyzing data to support decision-making within an organization. This course covers statistical concepts that are essential for Data Analysts, such as probability, sampling methods, hypothesis testing, and constructing confidence intervals, providing you with the tools you need to succeed in this role.

See salaries and explore the career path for Data Analyst

Statistician

Statisticians use statistical methods to collect, analyze, interpret, and present data, working across a range of industries from finance to healthcare. Common statistical methods used by Statisticians are taught in this course, including descriptive and inferential statistics, confidence intervals, and hypothesis testing, making it a valuable tool for those aspiring to become Statisticians.

See salaries and explore the career path for Statistician

Market Researcher

Market Researchers are responsible for gathering and interpreting market data to inform business decisions. This course delves into statistical concepts that are pivotal for Market Researchers, such as probability, sampling methods, confidence intervals, and hypothesis testing, helping you acquire the skills needed to excel in this role.

See salaries and explore the career path for Market Researcher

Financial Analyst

Financial Analysts use data to make informed investment recommendations and assess the financial health of companies. This course covers statistical methods that are essential for Financial Analysts, such as probability, hypothesis testing, and constructing confidence intervals, equipping you with the tools you need to succeed in this field.

See salaries and explore the career path for Financial Analyst

Biostatistician

Biostatisticians apply statistical methods to solve problems in the life sciences. This course provides a foundation in statistical concepts that are used by Biostatisticians, including probability, sampling methods, hypothesis testing, and constructing confidence intervals, equipping you with the skills needed to succeed in this specialized field.

See salaries and explore the career path for Biostatistician

Operations Research Analyst

Operations Research Analysts use statistical methods to improve the efficiency and effectiveness of operations within an organization. This course teaches statistical concepts that are commonly used by Operations Research Analysts, including probability, sampling methods, and hypothesis testing, making it a valuable asset for aspiring candidates.

See salaries and explore the career path for Operations Research Analyst

Epidemiologist

Epidemiologists investigate the causes and patterns of health and disease in populations. This course covers statistical methods that are essential for Epidemiologists, such as probability, sampling methods, and hypothesis testing, providing you with the tools you need to make informed decisions in this field.

See salaries and explore the career path for Epidemiologist

Survey Researcher

Survey Researchers design, conduct, and analyze surveys to collect data on various topics. This course provides a solid foundation in statistical methods that are used by Survey Researchers, including probability, sampling methods, and constructing confidence intervals, enabling you to gather and interpret data effectively in this role.

See salaries and explore the career path for Survey Researcher

Risk Analyst

Risk Analysts use statistical methods to identify, assess, and manage risks within an organization. This course provides a solid foundation in statistical concepts that are essential for Risk Analysts, including probability, hypothesis testing, and constructing confidence intervals, giving you the tools you need to succeed in this role.

See salaries and explore the career path for Risk Analyst

Actuary

Actuaries use statistical methods to assess risk and uncertainty in the insurance and finance industries. This course provides an introduction to statistical concepts that are used by Actuaries, including probability, hypothesis testing, and constructing confidence intervals, equipping you with the foundational knowledge needed to succeed in this field.

See salaries and explore the career path for Actuary

Data Engineer

Data Engineers design and build data pipelines and infrastructure to support data analysis. This course may be useful for aspiring Data Engineers as it provides an introduction to statistical concepts, including probability, sampling methods, and hypothesis testing, which can enhance their understanding of data and its applications.

See salaries and explore the career path for Data Engineer

Quantitative Analyst

Quantitative Analysts use statistical methods to analyze financial data and make investment decisions. This course may be useful for aspiring Quantitative Analysts as it provides an introduction to statistical concepts, including probability, hypothesis testing, and constructing confidence intervals, which can enhance their understanding of financial data and its applications.

See salaries and explore the career path for Quantitative Analyst

Software Engineer

Software Engineers design, develop, and maintain software systems. This course may be useful for aspiring Software Engineers who are interested in developing data-driven applications, as it provides an introduction to statistical concepts that can enhance their ability to analyze and interpret data.

See salaries and explore the career path for Software Engineer