|Kurslängd||2.0 dagar||Leveranstyp||Self-paced Virtual Class|
|Listpris||Set by Partner|
ONCE YOU ARE ENROLLED IN THIS COURSE, YOU WILL NOT BE ABLE TO CANCEL YOUR ENROLLMENT.
After you receive confirmation that you are enrolled, you will be sent further instructions to access your course material and remote labs. You will then have a 30 day window in which to complete your course. Within this 30 days, you will have 336 hours of elab time. The self-paced format gives you the opportunity to complete the course at your convenience, at any location, and at your own pace. The course is available 24 hours a day, but lab system access is allocated on a first-come, first-served basis. When you are not using the elab system, ensure that you suspend your elab to maximize your hours available to use the elab system. Once you have accessed the course, help is available Monday through Friday; questions will be responded to within 24 hours.
NO EXTENSIONS FOR THIS COURSE WILL BE GRANTED.
This is the self paced training version of "Advanced Statistical Methods for Healthcare Research" classroom course. The first part of the course focuses on the Analysis of Variance (ANOVA) techniques which allow you to test whether the means of several populations are the same. You will develop an understanding of when to apply the techniques, how to apply them and how to interpret the results. The second part of the course will build upon your knowledge of linear regression and will introduce you to logistic regression. We will include categorical predictors in regression models via dummy variables, discuss variable selection methods, model building philosophies and learn how to run and interpret logistic regression in IBM SPSS Statistics.
This intermediate course is intended for Healthcare professionals who want to identify significant differences between two or more groups and who want to analyze binary outcome data using logistic regression methods.
A good working knowledge of IBM SPSS Statistics Base and inferential statistics is required prior to attending this course. Attendance on the Statistical Methods for Healthcare Research course is strongly recommended.