Data Analysis Tools from Coursera

What's inside

Syllabus

Hypothesis Testing and ANOVA

This session starts where the Data Management and Visualization course left off. Now that you have selected a data set and research question, managed your variables of interest and visualized their relationship graphically, we are ready to test those relationships statistically. The first group of videos describe the process of hypothesis testing which you will use throughout this course to test relationships between different kinds of variables (quantitative and categorical). Next, we show you how to test hypotheses in the context of Analysis of Variance (when you have one quantitative variable and one categorical variable). Your task will be to write a program that manages any additional variables you may need and runs and interprets an Analysis of Variance test. Note that if your research question does not include one quantitative variable, you can use one from your data set just to get some practice with the tool. If your research question does not include a categorical variable, you can categorize one that is quantitative.

Chi Square Test of Independence

This session shows you how to test hypotheses in the context of a Chi-Square Test of Independence (when you have two categorical variables). Your task will be to write a program that manages any additional variables you may need and runs and interprets a Chi-Square Test of Independence. Note that if your research question only includes quantitative variables, you can categorize those just to get some practice with the tool.

Pearson Correlation

This session shows you how to test hypotheses in the context of a Pearson Correlation (when you have two quantitative variables). Your task will be to write a program that manages any additional variables you may need and runs and interprets a correlation coefficient. Note that if your research question only includes categorical variables, you can choose other variables from your data set just to get some practice with the tool.

Exploring Statistical Interactions

In this session, we will discuss the basic concept of statistical interaction (also known as moderation). In statistics, moderation occurs when the relationship between two variables depends on a third variable. The effect of a moderating variable is often characterized statistically as an interaction; that is, a third variable that affects the direction and/or strength of the relation between your explanatory (X) and response (Y) variable. Your task will be to test your own research question in the context of one or more potential moderating variables.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Focuses on hypothesis testing, ANOVA, Chi-Square, and Pearson Correlation Analysis, which are fundamental statistical concepts

Teaches learners how to apply statistical tests to specific data and research questions, developing their analytical skills

Emphasizes the use of statistical software packages (SAS or Python), providing learners with practical experience

Provides opportunities for learners to share their progress and gain feedback from peers, fostering a collaborative learning environment

Involves learners actively in hypothesis testing and statistical analysis, promoting hands-on learning

Reviews summary

Data analysis tools: well-received with clear lectures

Learners say this is a largely positive data analysis course that offers well-explained lectures and engaging assignments. Many students recommend this course, calling it interesting, excellent, and interactive. While a few students found the course too challenging, most found the material easy to learn thanks to the clear and engaging lectures.

Some learners found the course to be a bit challenging, but most found it to be manageable.

"It is an interactive session, with good notes and videos."

"Early lectures were exceedingly easy, but the difficulty jumped suddenly in the third week."

"With few tweaks will be an excellent course. Challenging - yes! Boring - no!"

Assignments are interactive, practical, and exploratory in nature.

"It is an interactive session, with good notes and videos."

"Very good class. Excellent assignments of exploratory nature."

"Great class, don't miss! It get me started with R. Very practical, many exercises."

Lectures are clear, engaging, and informative.

"Well-explained lectures."

"Educate the key concepts with simple examples."

"Excellent course in describing statistics."

Students have mixed opinions on the peer review process.

"lecture videos are interesting, clear, and have high production value. assignments are reasonable. Would be nice if they were reviewed by an expert from the school rather than peer reviewed though."

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 Data Analysis Tools with these activities:

Review Basic Statistics

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Strengthen your foundation in statistics by reviewing basic concepts.

Browse courses on Probability

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Review lecture notes or textbooks on basic statistics.
Solve practice problems to test your understanding.
Consult with a tutor or instructor if needed.

Organize Course Materials

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Stay organized and improve your learning by compiling and reviewing course materials.

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Gather all course materials, including lecture notes, assignments, and quizzes.
Organize the materials into a logical structure.
Review the materials regularly to reinforce your understanding.

Explore Statistical Software

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Become familiar with statistical software to enhance your data analysis capabilities.

Browse courses on SAS

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Choose a statistical software package (e.g., SAS, Python).
Find tutorials on the software's website or other online resources.
Follow the tutorials to learn the basics of the software.

Five other activities

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Form a Study Group

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Enhance your learning by collaborating with peers in a study group.

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Find a group of peers who are interested in forming a study group.
Set regular meeting times and a study schedule.
Review course material together, discuss concepts, and work on assignments.

Practice Statistical Tests

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Reinforce your understanding of statistical tests by completing practice problems.

Browse courses on Hypothesis Testing

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Review the lecture material on the statistical test you want to practice.
Find practice problems online or in textbooks.
Solve the practice problems and check your answers.

Conduct a Research Project

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Develop and test your own research question using the statistical methods learned in this course.

Browse courses on Hypothesis Testing

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Identify a research question relevant to your interests and the course material.
Design a study to test your research question.
Collect data using appropriate methods.
Analyze your data using the statistical tests learned in this course.
Write a report summarizing your findings.

Create a Presentation on Statistical Analysis

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Showcase your knowledge of statistical analysis by creating a presentation that explains a statistical concept or method.

Browse courses on Data Visualization

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Choose a statistical concept or method to present.
Research the topic and gather relevant information.
Create a presentation that includes clear explanations, examples, and visuals.
Practice your presentation and deliver it to a group.

Create a Statistical Model

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Deepen your understanding of statistical modeling by creating your own statistical model.

Browse courses on Regression Analysis

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Identify a problem that can be solved using statistical modeling.
Collect and prepare data.
Choose an appropriate statistical model.
Build and train the model.
Evaluate the performance of the model.

Career center

Learners who complete Data Analysis Tools will develop knowledge and skills that may be useful to these careers:

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. They work in a variety of industries, including finance, insurance, and healthcare. This course can help you in this role by providing you with the skills you need to: test hypotheses about your data, apply the appropriate statistical tests to your specific data and question, and use statistical software packages (SAS or Python).

See salaries and explore the career path for Quantitative Analyst

Business Analyst

Business Analysts use data to identify and solve business problems. They work with stakeholders to gather requirements, analyze data, and develop recommendations. This course can help you in this role by providing you with the skills you need to: test hypotheses about your data, apply the appropriate statistical tests to your specific data and question, and use statistical software packages (SAS or Python).

See salaries and explore the career path for Business Analyst

Market Researcher

Market Researchers gather and interpret data about consumers and markets. They use their findings to help businesses develop new products and marketing campaigns. This course can help you in this role by providing you with the skills you need to: test hypotheses about your data, apply the appropriate statistical tests to your specific data and question, and use statistical software packages (SAS or Python).

See salaries and explore the career path for Market Researcher

Statistician

Statisticians collect, analyze, and interpret data. They use their findings to help businesses and organizations make informed decisions. This course can help you in this role by providing you with the skills you need to: test hypotheses about your data, apply the appropriate statistical tests to your specific data and question, and use statistical software packages (SAS or Python).

See salaries and explore the career path for Statistician

Data Analyst

Data Analysts collect, analyze, interpret, and present data. They use their findings to help businesses make informed decisions. This course can help you in this role by providing you with the skills you need to: test hypotheses about your data, apply the appropriate statistical tests to your specific data and question, and use statistical software packages (SAS or Python).

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use data to solve business problems. They work with stakeholders to gather requirements, analyze data, and develop solutions. This course can help you may be useful in this role by providing you with the skills you need to: test hypotheses about your data, apply the appropriate statistical tests to your specific data and question, and use statistical software packages (SAS or Python).

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers build and deploy machine learning models. They work with data scientists to gather data, train models, and evaluate results. This course may be useful in this role by providing you with the skills you need to: test hypotheses about your data, apply the appropriate statistical tests to your specific data and question, and use statistical software packages (SAS or Python).

See salaries and explore the career path for Machine Learning Engineer

Software Engineer

Software Engineers design, develop, and maintain software applications. They work with users to gather requirements, design systems, and write code. This course may be useful in this role by providing you with the skills you need to: test hypotheses about your data, apply the appropriate statistical tests to your specific data and question, and use statistical software packages (SAS or Python).

See salaries and explore the career path for Software Engineer

Actuary

Actuaries use mathematical and statistical models to assess risk and uncertainty. They work in a variety of industries, including insurance, finance, and healthcare. This course may be useful in this role by providing you with the skills you need to: test hypotheses about your data, apply the appropriate statistical tests to your specific data and question, and use statistical software packages (SAS or Python).

See salaries and explore the career path for Actuary

Financial Analyst

Financial Analysts use financial data to make investment recommendations. They work with clients to gather information, analyze data, and develop investment strategies. This course may be useful in this role by providing you with the skills you need to: test hypotheses about your data, apply the appropriate statistical tests to your specific data and question, and use statistical software packages (SAS or Python).

See salaries and explore the career path for Financial Analyst

Operations Research Analyst

Operations Research Analysts use mathematical and statistical models to solve business problems. They work with businesses to improve efficiency, reduce costs, and make better decisions. This course may be useful in this role by providing you with the skills you need to: test hypotheses about your data, apply the appropriate statistical tests to your specific data and question, and use statistical software packages (SAS or Python).

See salaries and explore the career path for Operations Research Analyst

Risk Manager

Risk Managers identify, assess, and manage risks. They work with businesses to develop strategies to mitigate risks and protect their assets. This course may be useful in this role by providing you with the skills you need to: test hypotheses about your data, apply the appropriate statistical tests to your specific data and question, and use statistical software packages (SAS or Python).

See salaries and explore the career path for Risk Manager

Biostatistician

Biostatisticians use statistical methods to design and analyze medical studies. They work with researchers to develop new treatments and improve patient care. This course may be useful in this role by providing you with the skills you need to: test hypotheses about your data, apply the appropriate statistical tests to your specific data and question, and use statistical software packages (SAS or Python).

See salaries and explore the career path for Biostatistician

Epidemiologist

Epidemiologists study the causes and distribution of diseases. They use statistical methods to identify risk factors and develop prevention strategies. This course may be useful in this role by providing you with the skills you need to: test hypotheses about your data, apply the appropriate statistical tests to your specific data and question, and use statistical software packages (SAS or Python).

See salaries and explore the career path for Epidemiologist

Survey Researcher

Survey Researchers design, conduct, and analyze surveys. They work with businesses and organizations to collect data about their customers, employees, or other stakeholders. This course may be useful in this role by providing you with the skills you need to: test hypotheses about your data, apply the appropriate statistical tests to your specific data and question, and use statistical software packages (SAS or Python).

See salaries and explore the career path for Survey Researcher