Sample Size and Power Determination
This course will teach you how to make sample size determinations for various statistical tests and for confidence intervals, as needed for experimental studies such as comparison studies, as well as for other types of experiments.
Overview
In this course you will learn how to find the appropriate sample size, and the power of your study. The power of your study is its ability to detect a treatment effect of a specified size, if it exists. The goal of power analysis is to balance controllable and uncontrollable factors that influence a study by treating them as a series of “What if’s.” This process of finding a balance among factors can be aided by the use of graphs to visualize a range of options in a single picture in order to find the one that strikes the optimal balance between feasible sample size and acceptable power.
- Introductory, Intermediate
- 4 Weeks
- Expert Instructor
- Tuiton-Back Guarantee
- 100% Online
- TA Support
Learning Outcomes
At the end of the course students will understand how to use power analysis to effectively plan the appropriate sample size for a study. They will learn to recognize which factors are controllable and which are not, and how to balance those factors to find the optimal trade-off between feasible sample size and acceptable power.
- Specify the factors that interact to determine sample size
- Estimate unknowns needed to calculate sample size
- Deal with paired data
- Find sample size for a regression analysis
- Use software to calculate sample size needed for tests of means, proportions
Who Should Take This Course
Anyone responsible for the planning of a study, or its subsequent analysis. Investigators writing grant applications or other proposals in which sample size must be specified.
Our Instructors
Mr. Kuber Deokar
Mr. Kuber Deokar is Data Science Lead at UpThink EduTech Services Pvt. Ltd. (Pune, India). He holds a masters degree in Statistics from the University of Pune, India, where he also taught undergraduate statistics. He is a co-author of Machine Learning for Business Analytics with Galit Shmueli, Peter Bruce and Nitin Patel.
Kuber has over a decade of experience in course designing, development, delivery, and management. He handles and is responsible for the coordination of online courses and ensures seamless interactions between the management teams, course creators, course instructors, teaching assistants, and students He also serves as senior instructor and shares instructional responsibilities for several courses. He teaches Predictive Analytics and Statistical Modeling courses here at Statistics.com. Kuber has a special interest in Machine Learning and Responsible Artificial Intelligence.
Course Syllabus
Week 1
Introduction to Sample Size Determination and Power, Including Useful Software
- Hypothesis tests and confidence intervals
- Factors that determine sample size
- Sample size for estimating a population mean
- Examples, including a study from the literature
- External and internal pilot studies
- Ways to estimate sigma
- What should be avoided:Â Retrospective power and standardized effect sizes
- Ethical issues in power analysis
- Recommended references
- Software
Week 2
Tests on Population Means (continued)
- T-Test or Z-Test for population mean?
- Testing the normality assumption
- Confidence Intervals on Power and/or Sample Size?
- Two-sample study from the literature with unequal sample sizes
- Sample sizes determined by scientist in two stages without software
- Illustration of more efficient sample determination using software
- Using coefficient of variation
- Paired data
- Additional examples
Week 3
Tests on Proportions and Variances
- One proportion
- Software disagreement and rectification
- Two proportions
- Options, including transformations built into software, for tests of proportions
- One variance and two variances
- Examples
Week 4
Regression and Design
- Simple linear regressionComplexity caused by what must be inputted
- Complexity caused by what must be inputted
- Multiple linear regression
- Optional material: Repeated measures designs, Logrank test for survival analysis
- Literature references for sample size determination with more advanced statistical methods and some information on corresponding software capability
Class Dates
2025
Instructors: Mr. Kuber Deokar
Instructors: Mr. Kuber Deokar
Prerequisites
Some familiarity with experimental designs would be helpful, but is not required.
For those working in the life sciences, Biostatistics 1 – For Medical Science and Public Health may also be helpful.
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Additional Information
Organization of Course
This course takes place online at The Institute for 4 weeks. During each course week, you participate at times of your own choosing – there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.
At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.
Time Requirements
This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.
Homework
Homework in this course consists of short answer questions to test concepts and guided data analysis problems using software.
In addition to assigned readings, this course also has supplemental readings available online.
Course Text
All necessary materials will be provided online, including a few relevant journal articles. The Dr. Thomas Ryan’s recently published book, Sample Size Determination and Power, is recommended as a reference book.
Software
Participants should have access to a software package in which they can do power and sample size calculations. Power and Precision, R, MINITAB, and nQuery are used in the course Notes and examples. Other software packages such as Stata, PASS, and Russ Lenth’s Java applet may be used for the weekly assignments; limited assistance with these other packages may be available from the teaching assistants
Course Fee & Information
Enrollment
Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date unless you specify otherwise.
Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.
Group Rates
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Discounts
Academic affiliation? In most courses you are eligible for a discount at checkout.
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Invoice or Purchase Order
Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment.
Options for Credit and Recognition
This course is eligible for the following credit and recognition options:
No Credit
You may take this course without pursuing credit or a record of completion.
Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.
CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.
Supplemental Information
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