Hypothesis Testing
What you'll learn
- Identify the key components of hypothesis testing, including null and alternative hypotheses, significance levels, and types of errors.
- Explain the rationale behind different types of hypothesis tests (e.g., t-tests, z-tests) and when each is appropriate to use.
- Apply the hypothesis testing framework to real-world data, performing tests to evaluate claims about population parameters.
- Analyze the results of hypothesis tests by interpreting p-values, confidence intervals, and the significance of results.
- Evaluate the outcomes of hypothesis tests, assessing the risk of Type I and Type II errors and the implications of these risks in decision-making.
- Create and communicate clear reports of statistical findings, including all relevant assumptions, calculations, and interpretations of hypothesis test results.
Requirements
- Comfort with elementary algebra and interpreting mathematical expressions.
- Familiarity with basic probability concepts and rules.
- Ability to interpret and construct graphs, such as histograms and box plots.
Description
This course provides a comprehensive introduction to hypothesis testing, one of the most fundamental techniques in inferential statistics. The course is designed to guide students through the process of making data-driven decisions by evaluating claims about populations based on sample data. Beginning with the essential concepts of null and alternative hypotheses, students will learn how to construct testable statements about population parameters and will explore the reasoning behind the formulation of these hypotheses. The course will emphasize the critical role of hypothesis testing in drawing conclusions in various real-world contexts, from scientific research to business decision-making.
A key focus of the course will be the framework for making decisions using sample data. Students will develop a deep understanding of statistical significance and the logic behind rejecting or failing to reject a null hypothesis. They will also become familiar with the critical concepts of Type I and Type II errors, learning how to interpret p-values and confidence levels, and gaining insights into how these affect conclusions in hypothesis testing. Throughout the course, students will engage with one-sample and two-sample t-tests, z-tests for population proportions.
By the end of the course, students will have the tools and knowledge to apply hypothesis testing to a range of research and business problems. They will also be equipped to critically evaluate the results of hypothesis tests reported in academic studies and the media. With an emphasis on both theoretical understanding and practical application, the course prepares students to confidently use hypothesis testing in their future academic and professional endeavors.
Who this course is for:
- Undergraduate students seeking a deeper understanding of hypothesis testing in statistics.
- Students in psychology, economics, biology, business, public health, and social sciences.
- Individuals who have completed an introductory statistics course and want to further their knowledge of inferential statistics.
- Students preparing for careers in research or data analysis.
- Learners interested in applying statistical techniques to real-world problems, such as experiments and business performance evaluation.
- Those planning to pursue advanced studies or careers in academia, industry, or government requiring strong statistical decision-making skills.
Instructor
- 4.4 Instructor Rating
- 57,161 Reviews
- 966,287 Students
- 163 Courses
Through working with students from many different schools, Mr. Steele has learned best practices for helping people understand accounting fast. Learning new skills and finding the best way to share knowledge with people who can benefit from it is a passion of his.
Mr. Steele has experience working as a practicing Certified Public Accountant (CPA), an accounting and business instructor, and curriculum developer. He has enjoyed putting together quality tools to improve learning and has been teaching, making instructional resources, and building curriculum since 2009. He has been a practicing CPA since 2005. Mr. Steele is a practicing CPA, has a Certified Post-Secondary Instructor (CPI) credential, a Master of Science in taxation from Golden Gate University, a Bachelor’s Degree in Business Economics with an emphasis in accounting from The University of California Santa Barbara, and a Global Management Accounting Designation (CGMA) from The American Institute of CPA (AICPA).
Mr. Steele has also authored five books that can be found on Amazon or in audiobook format on Audible. He has developed bestselling courses in accounting topics including financial accounting and QuickBooks accounting software.
In addition to working as an accountant, teaching, and developing courses Mr. Steele has helped create an accounting website at accountinginstruction, a YouTube channel called Accounting Instruction, Help, and How Too, and has developed supplemental resources including a Facebook Page, Twitter Page, and Podcasts that can be found on I-tunes, Stitcher, or Soundcloud. Mr. Steele's teaching philosophy is to make content applicable, understandable, and accessible.
Adult learners are looking for application when they learn new skills. In other words, learners want to be able to apply skills in the real world to help their lives. Mr. Steele’s formal accounting education, practical work experience, and substantial teaching experience allow him to create a curriculum that combines traditional accounting education with practical knowledge and application. He accomplishes the goals of making accounting useful and applicable by combining theory with real-world software like Excel and QuickBooks.
Many courses teach QuickBooks data entry or Excel functions but are not providing the real value learners want. Real value is a result of learning technical skills like applications, in conjunction with specific goals, like accounting goals, including being able to interpret the performance of a business.
Mr. Steele makes knowledge understandable by breaking down complex concepts into smaller units with specific objectives and using step by step learning processes to understand each unit. Many accounting textbooks cram way too much information into a course, making it impossible to understand any unit fully. By breaking the content down into digestible chunks, we can move forward much faster.
Mr. Steele also makes use of color association in both presentations and Excel worksheets, a learning tool often overlooked in the accounting field, but one that can vastly improve the speed and comprehension of learning accounting concepts.
The material is also made understandable through the application of concepts learned. Courses will typically demonstrate the accounting concepts and then provide an Excel worksheet or practice problems to work through the concepts covered. The practice problems will be accompanied by an instructional video to work through the problem in step by step format. Excel worksheets will be preformatted, usually including an answer tab that shows the completed problem, and a practice tab where learners can complete the problem along with a step by step presentation video.
Mr. Steele makes learning accounting accessible by making use of technology and partnering with teaching platforms that have a vision of spreading knowledge like Udemy.