This course is best suited for individuals who have a technical background in mathematics/statistics/computer science/engineering pursuing a career change to jobs or industries that are data-driven such as finance, retain, tech, healthcare, government and many more. The opportunity is endless.

Model Diagnostics and Remedial Measures
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Model Diagnostics and Remedial Measures
This course is part of Advanced Statistical Techniques for Data Science Specialization

Instructor: Kiah Ong
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Recommended experience
What you'll learn
Describe the assumptions of the linear regression models.
Use diagnostic plots to detect violations of the assumptions of a linear regression model.
Perform variable selections and model validations.
Skills you'll gain
- Statistical Inference
- Statistical Methods
- Scatter Plots
- Statistical Analysis
- Model Evaluation
- Time Series Analysis and Forecasting
- Feature Engineering
- Correlation Analysis
- Verification And Validation
- Statistical Modeling
- Probability Distribution
- Plot (Graphics)
- Statistical Hypothesis Testing
- Data Transformation
- Regression Analysis
Tools you'll learn
Details to know

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11 assignments
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There are 3 modules in this course
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Build toward a degree
This course is part of the following degree program(s) offered by Illinois Tech. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
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Johns Hopkins University

Illinois Tech
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