- Data Analysis
- Statistical Hypothesis Testing
- Data-Driven Decision-Making
- Statistical Inference
- Data Collection
- Statistics
- Data Visualization
- Correlation Analysis
- Regression Analysis
- Predictive Modeling
- Statistical Methods
- Descriptive Statistics
Statistical Thinking for Industrial Problem Solving, presented by JMP
Completed by Eliav Silberstein
November 25, 2021
53 hours (approximately)
Eliav Silberstein's account is verified. Coursera certifies their successful completion of Statistical Thinking for Industrial Problem Solving, presented by JMP
What you will learn
How to describe data with statistical summaries, and how to explore your data using advanced visualizations.
Understand statistical intervals, hypothesis tests and how to calculate sample size.
How to fit, evaluate and interpret linear and logistic regression models.
How to build predictive models and conduct a statistically designed experiment.
Skills you will gain
