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Statistics Fundamentals for Business Analytics

Yuval Erez

This course introduces the basic tools and methods of statistical analysis, which can be applied to a wide variety of situations and data encountered in the areas of business and economics. Topics discussed include descriptive statistics, probability, sampling distributions, estimation, and hypothesis testing. By the end of the semester students should be able to compute and interpret basic descriptive statistical measures, understand the basic concepts of probability, and apply techniques of statistical inference.

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This course introduces the basic tools and methods of statistical analysis, which can be applied to a wide variety of situations and data encountered in the areas of business and economics. Topics discussed include descriptive statistics, probability, sampling distributions, estimation, and hypothesis testing. By the end of the semester students should be able to compute and interpret basic descriptive statistical measures, understand the basic concepts of probability, and apply techniques of statistical inference.

What you'll learn

By the end of the semester students should be able to compute and interpret basic descriptive statistical measures, understand the basic concepts of probability, and apply techniques of statistical inference.

Enroll now

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Taught by Yuval Erez, who are recognized for their work in business and economics
Develops basic descriptive statistical measures, sampling distributions, estimation, and hypothesis testing, which are core skills for Economics and Business
Introduces statistical analysis which is highly relevant to economics and business

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Reviews summary

Foundational statistics for business analytics

According to learners, this course offers a solid foundation in statistical concepts tailored for business analytics. Many find the lectures clear and accessible, appreciating how complex topics are broken down. The course is highlighted for its relevant examples and real-world case studies, making concepts easier to apply. However, some students note a lack of practical application using software tools like R or Python, feeling it can be too theoretical and focused on manual calculations. While generally a strong starting point for beginners, those with prior knowledge or seeking advanced, hands-on skills may find it too basic or desire deeper dives into modern analytical methods.
Mixed feedback on lecture engagement and forum activity.
"While the lectures are informative, they sometimes lack engagement."
"I also found the forum discussions weren't as active as I hoped, which made getting quick clarifications difficult."
A debate over hands-on application versus conceptual theory.
"I especially appreciated the real-world case studies; they made the concepts much easier to grasp and apply directly to my work."
"I was hoping for more practical application using software like R or Python, but it sticks mostly to conceptual understanding."
"There's not enough emphasis on practical implementation or real-world business problems. I struggled to see the direct relevance."
"The emphasis on manual calculations seemed a bit out of touch with modern business analytics where software is dominant."
Best suited for those new to statistics in a business context.
"As someone new to data analytics, I found this course incredibly accessible."
"Absolutely essential for anyone stepping into business analytics."
"It's far too basic and doesn't provide any real value for someone with even a little background in statistics."
"I wouldn't recommend it for those seeking immediate actionable insights, but it's a strong starting point."
Provides understandable basics for business analytics.
"This course provided an incredibly solid foundation in statistics tailored perfectly for business applications."
"The lectures were clear, the examples were highly relevant, and the hands-on exercises really helped solidify my understanding."
"The way they broke down complex statistical concepts into manageable lessons was excellent. I found this course incredibly accessible."
"It truly lives up to its 'fundamentals' title for business. It covers all the core statistical methods needed."
Some course examples and content may feel dated.
"My main gripe is that the course content, particularly the examples, felt a little dated."
"My only minor feedback is that some examples could be more contemporary."
"The emphasis on manual calculations seemed a bit out of touch with modern business analytics."

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 Fundamentals for Business Analytics with these activities:
Review basic statistical concepts
Reviewing basic statistical concepts will provide a solid foundation for understanding the more advanced topics covered in this course.
Browse courses on Descriptive Statistics
Show steps
  • Review notes or textbooks from previous statistics courses.
  • Take practice problems or quizzes to test your understanding.
  • Watch online tutorials or videos on basic statistical concepts.
Practice Probability Problems
Regular practice is key to mastering probability concepts. This activity provides ample opportunities to solve various probability problems, solidifying your understanding and building confidence in this foundational topic.
Browse courses on Probability
Show steps
  • Find practice problems online or in textbooks.
  • Solve the problems and check your answers.
  • Repeat until you feel comfortable with the concepts.
Learn about Statistical Software
Familiarity with statistical software is essential for data analysis. This activity introduces you to commonly used software, enabling you to apply your statistical knowledge to real-world datasets and enhance your employability.
Browse courses on Statistical Software
Show steps
  • Choose a statistical software program (e.g., SPSS, R, Python).
  • Find online tutorials or courses for the software.
  • Follow the tutorials and practice using the software.
Ten other activities
Expand to see all activities and additional details
Show all 13 activities
Follow tutorials on statistical software
Gaining proficiency in statistical software will enhance your ability to analyze and interpret data in this course.
Browse courses on Statistical Software
Show steps
  • Identify the most appropriate statistical software for your needs.
  • Find and enroll in online tutorials or workshops on the software.
  • Practice using the software by completing exercises and projects.
Discuss Statistical Concepts
Engaging in discussions with peers allows you to exchange knowledge, clarify concepts, and gain diverse perspectives. This activity fosters a collaborative learning environment and deepens your understanding of statistical methods.
Show steps
  • Join or create a study group.
  • Meet regularly to discuss course material and solve problems.
  • Share notes and resources with each other.
Attend study groups or discussion forums
Participating in peer study sessions or online discussions will provide opportunities to ask questions, share insights, and collaborate with others.
Show steps
  • Find or organize a study group with classmates.
  • Attend online discussion forums and participate in discussions.
  • Review and contribute to shared notes or summaries.
Review the Basics of Hypothesis Testing
This book provides a comprehensive overview of the fundamental concepts of hypothesis testing. By reviewing this book, you'll strengthen your understanding of this important statistical technique.
View Business Statistics, Global Edition on Amazon
Show steps
  • Read Chapters 1-3 of the book.
  • Complete the practice problems at the end of each chapter.
  • Take a practice quiz on hypothesis testing.
Interpret Statistical Results
Applying your knowledge of statistical analysis to real-world data is crucial. This hands-on project allows you to do just that, enhancing your ability to interpret statistical results and draw meaningful conclusions.
Browse courses on Descriptive Statistics
Show steps
  • Gather data from a reliable source.
  • Conduct a statistical analysis using the methods learned in the course.
  • Interpret the results of your analysis and draw conclusions.
  • Create a presentation or report to communicate your findings.
Read 'Introduction to the Practice of Statistics' by Moore and McCabe
This book provides a comprehensive overview of statistical methods and their applications, complementing the course materials.
View Introduction to the Practice of Statistics on Amazon
Show steps
  • Read and take notes on each chapter.
  • Complete the练习 exercises at the end of each chapter.
  • Discuss the concepts with classmates or a study group.
Participate in a Data Analysis Competition
Competitions provide a stimulating environment to test your skills, learn from others, and showcase your abilities. By participating in a data analysis competition, you can gain practical experience and further enhance your knowledge in this field.
Browse courses on Data Analysis
Show steps
  • Find a data analysis competition that aligns with your interests.
  • Team up with other students or participate individually.
  • Analyze the data and develop a solution.
  • Submit your solution and compete for prizes and recognition.
Create a data visualization project
Creating a data visualization project will allow you to apply your statistical knowledge and skills to a real-world dataset.
Browse courses on Data Visualization
Show steps
  • Choose a dataset that interests you.
  • Clean and analyze the data.
  • Create visualizations using statistical software or online tools.
  • Write a report or presentation to explain your findings.
Volunteer as a research assistant
Volunteering as a research assistant will provide practical experience in applying statistical methods to real-world research projects.
Show steps
  • Identify research projects that align with your interests.
  • Contact researchers or professors to inquire about volunteer opportunities.
  • Assist with data collection, analysis, or interpretation under the guidance of a mentor.
Start a personal project using statistical methods
Embarking on a personal project will allow you to explore a topic of your choice and apply your statistical knowledge in a meaningful way.
Show steps
  • Identify a problem or question that you want to investigate.
  • Collect or generate data relevant to your question.
  • Analyze the data using statistical methods.
  • Draw conclusions and present your findings.

Career center

Learners who complete Statistics Fundamentals for Business Analytics will develop knowledge and skills that may be useful to these careers:
Statistician
Statisticians collect, analyze, and interpret data to provide insights and solve problems. This course can serve as a fundamental building block for a career as a Statistician. Topics such as descriptive statistics, probability, and hypothesis testing provide a strong foundation for understanding statistical principles and methodologies.
See salaries and explore the career path for Statistician
Data Scientist
Data Scientists use statistical and machine learning techniques to extract insights from data. This course can provide a foundational understanding of statistical concepts essential for Data Scientists. Topics such as descriptive statistics, probability, and hypothesis testing can help them effectively analyze and interpret complex datasets.
See salaries and explore the career path for Data Scientist
Biostatistician
Biostatisticians apply statistical methods to medical and health-related data. This course can provide a valuable foundation for aspiring Biostatisticians. The course's focus on topics such as descriptive statistics, probability, and hypothesis testing can help them understand and analyze complex health-related data.
See salaries and explore the career path for Biostatistician
Machine Learning Engineer
Machine Learning Engineers design and implement machine learning models. This course can provide a solid foundation for aspiring Machine Learning Engineers. Topics such as probability, sampling distributions, and hypothesis testing can help them understand the statistical principles underlying machine learning algorithms and improve model performance.
See salaries and explore the career path for Machine Learning Engineer
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make informed decisions. This course can provide the foundational knowledge needed to excel as a Data Analyst. Topics such as descriptive statistics, probability, sampling distributions, estimation, and hypothesis testing provide a solid base for understanding and working with data effectively.
See salaries and explore the career path for Data Analyst
Quantitative Analyst
Quantitative Analysts use statistical and mathematical models to analyze financial data and make investment decisions. This course can provide a strong foundation for a successful career as a Quantitative Analyst. Concepts such as probability, sampling distributions, and hypothesis testing are essential for understanding and applying quantitative analysis techniques.
See salaries and explore the career path for Quantitative Analyst
Business Analyst
Business Analysts use data and statistical techniques to identify and solve business problems. This course can be a useful step towards a career in Business Analysis. Concepts in descriptive statistics, probability, and hypothesis testing can help Business Analysts make data-driven recommendations and improve business outcomes.
See salaries and explore the career path for Business Analyst
Market Research Analyst
Market Research Analysts collect and analyze market data to understand consumer behavior and trends. This course can provide a foundation for a successful career as a Market Research Analyst. Topics such as descriptive statistics, probability, and sampling distributions can help analysts design and conduct effective market research studies.
See salaries and explore the career path for Market Research Analyst
Risk Analyst
Risk Analysts identify, assess, and manage risks faced by organizations. This course can provide a valuable foundation for a career as a Risk Analyst. Concepts such as probability, sampling distributions, and hypothesis testing are crucial for understanding and quantifying risk.
See salaries and explore the career path for Risk Analyst
Statistical Analyst
Statistical Analysts use mathematical and statistical techniques to collect, analyze, interpret, and present data. This course can be a useful tool for aspiring Statistical Analysts. A background in descriptive statistics, probability, and hypothesis testing can help analysts work with various forms of data. An understanding of these concepts can also help them use techniques of statistical inference and interpret complex datasets.
See salaries and explore the career path for Statistical Analyst
Financial Analyst
Financial Analysts use statistical techniques to evaluate investments and make financial recommendations. This course can provide a foundation for a rewarding career as a Financial Analyst. A strong understanding of probability, sampling distributions, and hypothesis testing can help analysts assess risk and make sound investment decisions.
See salaries and explore the career path for Financial Analyst
Actuary
Actuaries use statistical and mathematical methods to assess and manage risk. This course can be a useful stepping stone for aspiring Actuaries. Topics covered, such as probability, sampling distributions, and hypothesis testing, provide a solid base for understanding actuarial concepts and methodologies.
See salaries and explore the career path for Actuary
Epidemiologist
Epidemiologists investigate the causes and patterns of health and disease in populations. This course can provide a helpful foundation for aspiring Epidemiologists. Topics such as descriptive statistics, probability, and sampling distributions can enhance their ability to design and conduct epidemiological studies and analyze health-related data.
See salaries and explore the career path for Epidemiologist
Operations Research Analyst
Operations Research Analysts use statistical and mathematical techniques to improve operational efficiency. This course can provide a helpful foundation for a career as an Operations Research Analyst. The course's focus on topics such as descriptive statistics, probability, and hypothesis testing can equip analysts with problem-solving skills and data analysis expertise.
See salaries and explore the career path for Operations Research Analyst
Software Engineer
Software Engineers design, develop, and maintain software applications. While not directly related to the field of Statistics, this course can provide a helpful foundation for Software Engineers who work with data-intensive applications. Topics such as descriptive statistics, probability, and sampling distributions can enhance their ability to understand and analyze data.
See salaries and explore the career path for Software Engineer

Reading list

We've selected 16 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 Fundamentals for Business Analytics.
Cover image
Probability and Statistical Inference
Save
Provides a rigorous introduction to probability and mathematical statistics, making it suitable for advanced students.
Probability and Statistical Inference
Kindle Edition
$$$
Cover image
Statistical Methods for the Social Sciences, Global...
Save
Introduces the basic principles of statistics, emphasizing the importance of interpretation and context.
Statistical Methods for the Social Sciences, Global...
Paperback
Check
Statistical Methods for the Social Sciences, Global...
Kindle Edition
Check
Cover image
The Elements of Statistical Learning
Save
Comprehensive guide to modern statistical learning methods, providing a valuable reference for practitioners.
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Hardcover
$$$
The Elements of Statistical Learning: Data Mining,...
Kindle Edition
$$$
Cover image
Deep Learning
Save
Comprehensive guide to deep learning and neural networks, providing a valuable resource for advanced learners.
Deep Learning
Paperback
$$$
Deep Learning (Adaptive Computation and Machine...
Hardcover
$$$
Deep Learning (Adaptive Computation and Machine...
Kindle Edition
$$$
Cover image
Bayesian Data Analysis, Third Edition
Save
Provides a comprehensive introduction to Bayesian statistics, with a focus on computational methods and applications.
Bayesian Data Analysis (Chapman & Hall/CRC Texts in...
Kindle Edition
$$$$
Cover image
Statistical Rethinking
Save
Provides a practical introduction to Bayesian statistics, using R and Stan for data analysis and modeling.
Statistical Rethinking
Paperback
Check
Statistical Rethinking
Kindle Edition
Check
Essentials of Statistics for Business & Economics
Save
Combines a solid foundation in statistical theory with practical applications to business and economics.
Essentials of Statistics for Business & Economics
Paperback
Check
Essentials of Statistics for Business & Economics
Kindle Edition
Check
Cover image
Business Statistics Student Solutions Manual
Save
Provides a comprehensive overview of statistical methods with a focus on business applications.
Student solutions manual [for] Business statistics ...
Paperback
$$$
Cover image
Data Mining
Save
Provides an overview of data mining techniques and their applications in various domains, including business and industry.
Data Mining: Practical Machine Learning Tools and...
Paperback
$$$
DATA MINING, 4TH EDITION
Paperback
$$
Data Mining: Practical Machine Learning Tools and...
Kindle Edition
$$
Cover image
Hands-On Machine Learning with Scikit-Learn, Keras,...
Save
Provides practical examples of machine learning techniques using popular libraries like Scikit-Learn, Keras, and TensorFlow.
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Kindle Edition
$$
Cover image
Reinforcement Learning, second edition
Save
Provides a foundational understanding of reinforcement learning concepts and algorithms, making it suitable for advanced students.
Reinforcement Learning, second edition: An...
Hardcover
$$$
Reinforcement Learning, second edition: An...
Kindle Edition
$$$
Statistical Techniques in Business and E
Save
Emphasizes the use of statistical software to analyze data and make informed decisions.
ISE Statistical Techniques in Business and Economics
Paperback
$$$
Cover image
Introduction to the Practice of Statistics
Save
Is designed to help students develop conceptual understanding of statistical ideas and learn to reason with data. It has a clear writing style and interesting examples.
Introduction to the Practice of Statistics
Paperback
Check
Introduction to the Practice of Statistics
Kindle Edition
Check
Cover image
Hands-On Artificial Intelligence for Banking
Save
Is an online resource that provides a comprehensive overview of machine learning algorithms and techniques.
Hands-On Artificial Intelligence for Banking: A...
Paperback
$$
Hands-On Artificial Intelligence for Banking: A...
Kindle Edition
$$
Cover image
Probability with STEM Applications
Save
Provides a theoretical understanding of statistics with a focus on engineering and scientific applications.
Probability with STEM Applications, 3rd Edition
Kindle Edition
$$$$
Cover image
Applied Mathematics and Modeling for Chemical...
Save
Focuses on the applications of statistics in a variety of fields, such as engineering, medicine, and finance.
Solutions Manual to Accompany Applied Mathematics...
Kindle Edition
$$$
Solutions Manual to Accompany Applied Mathematics...
Paperback
$$$

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Course image
Effort
2 to 4 hours per week for 6 weeks
Level
Elementary
Via
edX
Institution
Lehigh University
Instructor
Yuval Erez
Language
English
Transcript
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Taught by Yuval Erez, who are recognized for their work in business and economics
Develops basic descriptive statistical measures, sampling distributions, estimation, and hypothesis testing, which are core skills for Economics and Business
Introduces statistical analysis which is highly relevant to economics and business
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