Introduction to Statistical Analysis: Hypothesis Testing from Coursera

What's inside

Syllabus

Course Overview and Data Setup

In this module you learn about the course and the data you analyze in this course. Then you set up the data you need to do the practices in the course.

Introduction and Review of Concepts

In this module you learn about the models required to analyze different types of data and the difference between explanatory vs predictive modeling. Then you review fundamental statistical concepts, such as the sampling distribution of a mean, hypothesis testing, p-values, and confidence intervals. After reviewing these concepts, you apply one-sample and two-sample t tests to data to confirm or reject preconceived hypotheses.

ANOVA and Regression

In this module you learn to use graphical tools that can help determine which predictors are likely or unlikely to be useful. Then you learn to augment these graphical explorations with correlation analyses that describe linear relationships between potential predictors and our response variable. After you determine potential predictors, tools like ANOVA and regression help you assess the quality of the relationship between the response and predictors.

More Complex Linear Models

In this module you expand the one-way ANOVA model to a two-factor analysis of variance and then extend simple linear regression to multiple regression with two predictors. After you understand the concepts of two-way ANOVA and multiple linear regression with two predictors, you'll have the skills to fit and interpret models with many variables.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Introduces t tests, ANOVA, and linear regression, essential statistical methods commonly used in various fields

Instructed by Jordan Bakerman, a leading expert in statistical analysis with SAS

Suitable for beginners seeking an introduction to statistical analysis using SAS software

Provides a foundation for further learning in statistical analysis and SAS programming

Requires familiarity with basic statistical concepts, which may necessitate prior knowledge or additional research

Reviews summary

Beginner-friendly statistics with sas

Learners say this course is easy to understand and beginner-friendly. Students appreciate the engaging lectures and practical assignments that help them apply statistical concepts using SAS software. Overall, this course is largely positive and well received by learners.

Instructor provides clear explanations.

"Thank you so much to the instructor, Jordan Bakerman for teaching this course."

"Thank you so much!"

"Great"

Assignments help apply concepts.

"Nice one... Thanks. Lecturers were good"

"Great study material / topics."

"If only...1) SAS programming basics"

Course focuses on SAS applications.

"Well Done Everything. Practices need to be clarified more because somebody know Statistics with less SAS and reversely some learners know SAS but less Statistics."

"Awesome Course. Learned how to do Hypothesis Testing like ANOVA and Regression using SAS."

"Another great course from SAS and Coursera."

Easy to follow for beginners.

"Learned how to do Hypothesis Testing like ANOVA and Regression using SAS. Great instructor and explanation, easy to understand and straight forward."

"It is Excellent"

"where do I get my certificate for this course"

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 Introduction to Statistical Analysis: Hypothesis Testing with these activities:

Review your basic math skills

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This will help refresh your memory on basic math skills that you may have forgotten or never learned.

Browse courses on Algebra

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Work through some basic math problems
Take a math quiz

Learn how to use SAS

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This will teach you how to use SAS, which is the software you will be using in this course.

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Watch some SAS tutorials
Complete some SAS exercises

Join a SAS study group

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This will allow you to connect with other students and learn from each other.

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Find a SAS study group
Attend SAS study group meetings

Five other activities

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Read the SAS documentation

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This will help you learn more about SAS and how to use it.

View Melania on Amazon

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Read through the SAS User's Guide
Complete some SAS exercises

Attend a SAS workshop

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This will provide you with an opportunity to learn from experts in the field and get hands-on experience with SAS.

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Find a SAS workshop
Attend the SAS workshop

Do some SAS practice problems

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This will help you practice using SAS and improve your skills.

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Find some SAS practice problems
Solve the SAS practice problems

Volunteer with a non-profit that uses SAS

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This will give you real-world experience using SAS and help you make a difference in the community.

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Find a non-profit that uses SAS
Volunteer with the non-profit

Create a SAS tutorial

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This will help you solidify your understanding of SAS and share your knowledge with others.

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Choose a SAS topic to teach
Create a SAS tutorial

Career center

Learners who complete Introduction to Statistical Analysis: Hypothesis Testing will develop knowledge and skills that may be useful to these careers:

Statistician

Statisticians play a vital role in various industries by collecting, analyzing, and interpreting data to help businesses and organizations make informed decisions. The course, "Introduction to Statistical Analysis: Hypothesis Testing" from SAS, provides a solid foundation for aspiring Statisticians by introducing concepts like hypothesis testing, p-values, and confidence intervals. The course's focus on t tests, ANOVA, and linear regression, which are commonly used in statistical analysis, will be particularly valuable for Statisticians.

See salaries and explore the career path for Statistician

Data Analyst

Data Analysts are in high demand across industries, leveraging data to identify patterns and trends that drive business decisions. The SAS course on "Introduction to Statistical Analysis: Hypothesis Testing" aligns well with a Data Analyst's responsibilities. The course provides a strong foundation in statistical concepts, hypothesis testing, and regression analysis, which are essential skills for Data Analysts to extract meaningful insights from data.

See salaries and explore the career path for Data Analyst

Quantitative Analyst

Quantitative Analysts use statistical models and data analysis techniques to assess risk and make informed investment decisions in the financial industry. The SAS course, "Introduction to Statistical Analysis: Hypothesis Testing," provides a solid grounding in hypothesis testing, statistical inference, and regression analysis. These concepts are crucial for Quantitative Analysts to evaluate financial data, develop trading strategies, and manage risk.

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Biostatistician

Biostatisticians apply statistical principles to medical and health-related data to support research and decision-making in healthcare. The SAS course on "Introduction to Statistical Analysis: Hypothesis Testing" provides a strong foundation in statistical methods, including hypothesis testing and regression analysis, which are essential skills for Biostatisticians. The course will help Biostatisticians analyze clinical trial data, evaluate treatment effectiveness, and contribute to medical research.

See salaries and explore the career path for Biostatistician

Market Research Analyst

Market Research Analysts gather and analyze market data to understand consumer behavior, identify trends, and develop marketing strategies. The SAS course on "Introduction to Statistical Analysis: Hypothesis Testing" equips aspiring Market Research Analysts with the skills to design and conduct surveys, analyze data, and draw meaningful conclusions. The course's focus on hypothesis testing and regression analysis will help Market Research Analysts make informed decisions and contribute to successful marketing campaigns.

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Epidemiologist

Epidemiologists investigate the distribution and patterns of diseases and health conditions in populations. The SAS course, "Introduction to Statistical Analysis: Hypothesis Testing," provides a solid foundation in statistical methods, including hypothesis testing and regression analysis, which are crucial for Epidemiologists to analyze epidemiological data, identify risk factors, and develop prevention strategies.

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Actuary

Actuaries use mathematical and statistical models to assess risk and uncertainty in the insurance and finance industries. The SAS course on "Introduction to Statistical Analysis: Hypothesis Testing" provides a strong foundation in statistical methods, including hypothesis testing and regression analysis, which are essential skills for Actuaries to evaluate risk, set premiums, and make sound financial decisions.

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Data Scientist

Data Scientists leverage statistical methods, data analysis techniques, and machine learning algorithms to extract insights from data and drive decision-making. The SAS course on "Introduction to Statistical Analysis: Hypothesis Testing" provides a solid foundation in statistical concepts and hypothesis testing, which are core skills for Data Scientists. The course's focus on t tests, ANOVA, and linear regression will help aspiring Data Scientists build a strong foundation for their careers.

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Quality Assurance Analyst

Quality Assurance Analysts ensure that products and services meet quality standards by identifying and resolving defects. The SAS course, "Introduction to Statistical Analysis: Hypothesis Testing," provides a foundation in statistical methods, including hypothesis testing and regression analysis, which are useful for Quality Assurance Analysts to analyze data, identify trends, and improve product quality.

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Risk Manager

Risk Managers identify, assess, and mitigate risks in various industries, including finance, insurance, and healthcare. The SAS course, "Introduction to Statistical Analysis: Hypothesis Testing," provides a foundation in statistical methods, including hypothesis testing and regression analysis, which are useful for Risk Managers to analyze data, quantify risks, and develop mitigation strategies.

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Educational Researcher

Educational Researchers study the effectiveness of educational programs and interventions to improve teaching and learning outcomes. The SAS course, "Introduction to Statistical Analysis: Hypothesis Testing," provides a solid foundation in statistical methods, including hypothesis testing and regression analysis, which are essential skills for Educational Researchers to analyze data, evaluate educational interventions, and make evidence-based recommendations.

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Operations Research Analyst

Operations Research Analysts use mathematical and statistical models to optimize business processes and improve decision-making. The SAS course, "Introduction to Statistical Analysis: Hypothesis Testing," provides a foundation in statistical methods, including hypothesis testing and regression analysis, which are useful for Operations Research Analysts to analyze data, identify inefficiencies, and develop optimization strategies.

See salaries and explore the career path for Operations Research Analyst

Financial Analyst

Financial Analysts evaluate financial data to make investment recommendations and advise clients on financial matters. The SAS course, "Introduction to Statistical Analysis: Hypothesis Testing," provides a foundation in statistical methods, including hypothesis testing and regression analysis, which are useful for Financial Analysts to analyze market data, evaluate investment opportunities, and make informed financial decisions.

See salaries and explore the career path for Financial Analyst

Business Analyst

Business Analysts study business processes to identify areas for improvement and develop solutions to enhance efficiency and profitability. The SAS course, "Introduction to Statistical Analysis: Hypothesis Testing," provides a foundation in statistical methods, including hypothesis testing and regression analysis, which are useful for Business Analysts to analyze data, identify trends, and make recommendations for business improvement.

See salaries and explore the career path for Business Analyst

Marketing Analyst

Marketing Analysts use data analysis techniques to understand consumer behavior, identify market trends, and develop marketing strategies. The SAS course, "Introduction to Statistical Analysis: Hypothesis Testing," provides a foundation in statistical methods, including hypothesis testing and regression analysis, which are useful for Marketing Analysts to analyze market data, evaluate marketing campaigns, and make data-driven marketing decisions.

See salaries and explore the career path for Marketing Analyst