Introduction to Applied Statistics
Statistical tools for modern data analysis can be used across a range of industries to help you guide organizational, societal and scientific advances. This course uses industry-standard applications and software (R and Python) for numerical reasoning and predictive data modeling, with an emphasis on conceptual rather than theoretical understanding.
Topics Include
- Bootstrap
- Correlated errors
- Data snooping
- Interactions and qualitative variables
- Multiple linear regression
- Penalized regression
- Poisson
- Regression and prediction
- Simple linear regression
- Transformations
- Variance and cross-validation
Course Page
Price
$4,056.00
Subject to change
Delivery
Online, instructor-led
Level
Introductory
Commitment
10 weeks, 5-15 hrs/week
Credit
Data Mining and Applications Graduate Certificate
Statistics Graduate Certificate
School
Stanford School of Humanities and Sciences
Language
English