06-09-2013, 10:18 PM
https://class.stanford.edu/courses/Medic...cine/about
COURSE SYLLABUS
Week 1 - Descriptive statistics and looking at data
Week 2 - Review of study designs; measures of disease risk and association
Week 3 - Probability, Bayes' Rule, Diagnostic Testing
Week 4 - Probability distributions
Week 5 - Statistical inference (confidence intervals and hypothesis testing)
Week 6 - P-value pitfalls; types I and type II error; statistical power; overview of statistical tests
Week 7 - Tests for comparing groups (unadjusted); introduction to survival analysis
Week 8 - Regression analysis; linear correlation and regression
Week 9 - Logistic regression and Cox regression
Thank you for signing up for Statistics in Medicine. The course starts Tuesday, June 11.
Whether you've taken a course in statistics and probability before or this is your first time delving into the field, I think you will enjoy this course. My goal is to introduce you to the exciting and highly relevant field of medical statistics. After completing this course, you should better understand how to: interpret and look at data; apply statistics and probability to real-world problems; and critically evaluate the results of medical studies.
Here are a few logistical details to help you plan for and get started in the course:
The course has no prerequisites, but you will need to be familiar with a few basic math tools (summation sign, factorial, natural log, exponential, and the equation of a line). If you need a refresher on these topics, please view the brief math review at
Basic Math Review - YouTube
before starting the rest of the course.
When the course opens, I will be asking you to fill out a brief pre-course survey and a brief starting-point assessment These items have no impact on your grade, but will help us to better understand the audience, learning goals, and learning outcomes.
The course is divided into weekly units that contain videos, quizzes, and a homework assignment. Homework for each unit is due weekly by Tuesday at noon Pacific Time. For example, Unit 1 homework is due Tuesday June 18 at 12pm PDT and Unit 2 homework is due June 25 at 12pm PDT. Late submissions won't carry any credit, but your lowest grade won't be counted. All the course materials will be posted June 11, so you may work ahead of this schedule if you choose. At the end of the course, there will be a multiple-choice final exam. More details about assignments and grades will be posted in the course syllabus and in weekly announcements. To earn a Statement of Accomplishment, you must score at least 60% in the course (above 90% earns a Statement with distinction).
The course offers a number of optional videos and modules. These cover more challenging math topics and problems, proofs and derivations, and training in data analysis in R (with Deducer). You may choose to view some, all, or none of these modules depending on your interest and math background. Skipping these extra modules will not affect the continuity of the course; and they are not required for course completion (earning a Statement of Accomplishment).
If you know others who may be interested in taking this course, please forward the link as it is not too late to sign up: https://medstats.class.stanford.edu
If you have read about these new Massively Open Online Courses, or MOOCs, you will be aware that they are all still very much experimental, so everyone involved is learning as we go along, the students, the support staff, the teaching assistants, and the faculty, like myself. I'm excited to be part of this new experiment, and I'm glad you have decided to join me.
I look forward to meeting and working with you online.
Kristin Sainani
COURSE SYLLABUS
Week 1 - Descriptive statistics and looking at data
Week 2 - Review of study designs; measures of disease risk and association
Week 3 - Probability, Bayes' Rule, Diagnostic Testing
Week 4 - Probability distributions
Week 5 - Statistical inference (confidence intervals and hypothesis testing)
Week 6 - P-value pitfalls; types I and type II error; statistical power; overview of statistical tests
Week 7 - Tests for comparing groups (unadjusted); introduction to survival analysis
Week 8 - Regression analysis; linear correlation and regression
Week 9 - Logistic regression and Cox regression
Thank you for signing up for Statistics in Medicine. The course starts Tuesday, June 11.
Whether you've taken a course in statistics and probability before or this is your first time delving into the field, I think you will enjoy this course. My goal is to introduce you to the exciting and highly relevant field of medical statistics. After completing this course, you should better understand how to: interpret and look at data; apply statistics and probability to real-world problems; and critically evaluate the results of medical studies.
Here are a few logistical details to help you plan for and get started in the course:
The course has no prerequisites, but you will need to be familiar with a few basic math tools (summation sign, factorial, natural log, exponential, and the equation of a line). If you need a refresher on these topics, please view the brief math review at
Basic Math Review - YouTube
before starting the rest of the course.
When the course opens, I will be asking you to fill out a brief pre-course survey and a brief starting-point assessment These items have no impact on your grade, but will help us to better understand the audience, learning goals, and learning outcomes.
The course is divided into weekly units that contain videos, quizzes, and a homework assignment. Homework for each unit is due weekly by Tuesday at noon Pacific Time. For example, Unit 1 homework is due Tuesday June 18 at 12pm PDT and Unit 2 homework is due June 25 at 12pm PDT. Late submissions won't carry any credit, but your lowest grade won't be counted. All the course materials will be posted June 11, so you may work ahead of this schedule if you choose. At the end of the course, there will be a multiple-choice final exam. More details about assignments and grades will be posted in the course syllabus and in weekly announcements. To earn a Statement of Accomplishment, you must score at least 60% in the course (above 90% earns a Statement with distinction).
The course offers a number of optional videos and modules. These cover more challenging math topics and problems, proofs and derivations, and training in data analysis in R (with Deducer). You may choose to view some, all, or none of these modules depending on your interest and math background. Skipping these extra modules will not affect the continuity of the course; and they are not required for course completion (earning a Statement of Accomplishment).
If you know others who may be interested in taking this course, please forward the link as it is not too late to sign up: https://medstats.class.stanford.edu
If you have read about these new Massively Open Online Courses, or MOOCs, you will be aware that they are all still very much experimental, so everyone involved is learning as we go along, the students, the support staff, the teaching assistants, and the faculty, like myself. I'm excited to be part of this new experiment, and I'm glad you have decided to join me.
I look forward to meeting and working with you online.
Kristin Sainani
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