1. |
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Course Intro
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What is biostatistics? One real world example. What we are going to learn? |
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2. |
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Study Design
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Study Design: Observational and Randomized; Discussion on Research question and appropriate Study designs for each senario. |
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3. |
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Quantifying the extent of Disease / Summarizing Data Collected in the Sample
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Learn some terms, prevalence, Incidence, Risk Difference, Population Attributable Risk, Relative Risk, Odds Ratio; Also learned some sampling methods, ROC, EER |
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4. |
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Real Data Analysis (BRFSS data), search for open big data in Public Health Research
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Real world big data analysis using BRFSS data; More discussion on publicly available open big data sets in Public Health Reserach |
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5. |
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Confidence Interval, R for Data Science(dplyr, ggplot)
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Learned CI for one sample, two sample continuous, and categorical outcomes, CI for RD, RR, and OR; Also learned R data analysis |
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6. |
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More details on CI calculation for OR and RR; solved quiz problems
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CI derivation for OR using delta method and CLT; In practice CI derivation for RR; Solved other quiz problems |
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7. |
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Hypothesis Testing
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Hypothesis testing for one, two samples for continuous and dichotomous outcomes; |
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8. |
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Multivariate Methods; Sample Size Calculation
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linear regression, logistic regression; Sample size calculation for diverse senarios |
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9. |
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How to read Research papers
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Discussion on how to read Research papers in Public Health Research |
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10. |
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Nonparametric methods; Survival analysis 1
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Learned concepts for sign test, wilcoxon signed rank test, wilcoxon rank sum tests; Learned time to event variables, cencering, and Kaplan Meier approach |
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11. |
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Team based work for Team project
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How to search research papers; Discuss topics for team project; How to visualize findings |
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12. |
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Survival analysis 2 ; Multiple Testing
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log-rank test, Cox-proportional hazard regression; basic multiple testing methods; bonferroni, holms for FWER, and Benjamini and Hochberg for FDR. |
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