MarinStatsLectures-R Programming & Statistics
These R Programming and Statistics tutorials are originally created for Master's and PhD students at UBC by Professor Mike Marin and are now available to public.These videos provide a comprehensive and completely free set of tutorials for introductory and intermediate concepts in Statistics and Statistics with R.Our team:
Professor Mike Marin is the content creator for these video tutorials and is currently teaching at The University of British Columbia in The School of Population and Public Health, Biostatistics and Epidemiology Division. During his career he has won many awards for excellence in teaching. You can learn more about him here: spph.ubc.ca/person/mike-marin/
Ladan Hamadani (B.Sc., BA., MPH), is the media manager and content editor of the videos. She makes sure that the amazing content is polished and presented in a way that is easy to follow. She also works as a research analyst in health sector.
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9.7 Poisson Regression: The Model For Count Data
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9.6 Intro To Data Used In Poisson Regression R Videos
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9.4 Why We Work On Log-Scale?
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Logistic Regression Example
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9.2 Comparing Logistic, Poisson, and Survival Analysis
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9.1 Week 9 Intro and Recap
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8.8 Extensions of The Logistic Regression Model: Multinomial, Ordinal, and Conditional Logistic
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8.7 Logistic Regression: R Square Type Measures in R
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8.6 Logistic Regression: R-Square Type Measures
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8.5 Examining Model Fit
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8.2 Building Model To Estimate Effect Size in R
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8.1 Week 8 Intro And Recap
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3.2 Confounding (Confounder) Explained
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7.7 Logistic Regression in R: Checking Linearity In R
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7.6 Logistic Regression: Checking Linearity
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7.5 Logistic Regression: Model Assumptions
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7.4 Effect Modification in R: Calculating Odds Ratios and Comparing With Stratification In R
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7.3 Effect Modification: Calculating Odds Ratios From Model
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7.2 Likelihood Ratio Test in R (for LBW Data)
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