Logistic regression: Predict categorical outcomes (for example, who is most likely to buy your product) while taking the sample design into account to more accurately identify groups
Ordinal regression: Predict ordinal outcomes such as customer satisfaction (low, medium or high)
General linear models: Predict numerical outcomes while taking the sample design into account
Cox regression: Predict time to an event for samples drawn by complex sampling methods
Intuitive Sampling wizard: Guides you step by step through the process of designing and drawing a sample
Easy-to-use Analysis Preparation wizard: Helps prepare public-use data sets for analysis, such as the National Health Inventory Survey data from the Centers for Disease Control and Prevention (CDC)
Easier collaboration with colleagues: More easily share sampling and analysis plans
More accurate analyses: Enables you to take up to three stages into account when analyzing data from a multistage design
A more precise picture of your data: Unlike traditional statistics, subpopulation assessments consider other subpopulations
1.Sampling Wizard
2.Sampling Wizard – Design Variables
3.Sampling Wizard – Output
is proudly powered by Powered by WordPress.com.