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The [course_title] course teaches the basic statistics terms with a special focus on the R statistic software package.

In the course, you will learn the components of biostatistical methods used in both omics and population health research. The course teaches you the common statistical terms and definitions, and statistical theory so that you can handle the challenges of biomedical big data.

Upon completion, you will gain a strong command over R software.

Assessment

This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.

Certification

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Having an Official Edukite Certification is a great way to celebrate and share your success. You can:

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Course Credit: Osaka University

Course Curriculum

Module: 1
Weekly Handouts,WEEK 1 00:15:00
Weekly Handouts,WEEK 2 00:05:00
Weekly Handouts,WEEK 3 00:10:00
Weekly Handouts,WEEK 4 00:05:00
Weekly Handouts,WEEK 5 00:15:00
Weekly Handouts,WEEK 6 00:05:00
Weekly Handouts,WEEK 7 00:10:00
Weekly Handouts,WEEK 8 00:10:00
Weekly Handouts,WEEK 9 00:10:00
Weekly Datasets,WEEK 6 00:05:00
Introduction 00:05:00
Module: 2
Video 1 00:01:00
Video 2 00:03:00
Video 3 00:03:00
Video 4 00:04:00
Video 5 00:05:00
Video 6 00:03:00
Video 7 00:02:00
Video 8 00:02:00
Module: 3
Weekly Handout (W1) 00:10:00
Video 1: Descriptive Statistics 00:03:00
Video 2: Standard Deviation 00:06:00
Video 3: How to Use Mean and Standard Deviation(1) 00:07:00
Video 4: How to Use Mean and Standard Deviation(2) 00:03:00
Video 5: P-Value and Hypothesis Testing 00:05:00
Video 6: What is a Scientific Evidence? 00:05:00
Video 7: Disproving Hypothesis 00:10:00
Video 8: Pitfalls of P-Value 00:09:00
Video 9: Confidence Interval (1) 00:05:00
Video 10: Confidence Interval (2) 00:06:00
Video11: Confidence Interval (3) 00:03:00
Video 12: Statistical Graphs 00:08:00
Video 13: Summary of This Lecture 00:03:00
Module: 4
Weekly Handouts (W2) 00:05:00
Video 1: Introduction of Week 2 00:05:00
Video 2: PECO 00:04:00
Video 3: Classification of Clinical Studies 00:07:00
Video 4: 3 Types of Observational Studies 00:04:00
Video 5: Sampling Method 00:04:00
Video 6: Cohort Study 00:06:00
Video 7: Data collection and Timing Method 00:06:00
Video 8: Identify Study Design 00:05:00
Video 9: Cross Sectional 00:04:00
Video 10: Advantages of Cohort Studies 00:05:00
Video 11: Disadvantages of Cohort Studies 00:03:00
Video 12: Advantages of Cohort Studies (additional) 00:02:00
Video 13: Advantages of Case Control Study 00:05:00
Video 14: Disadvantages of Case Control Study 00:06:00
Module: 5
Weekly Handouts (W3) 00:10:00
Weekly Handouts (W3) 1 00:05:00
Video 1: Introduction of Week 3 00:02:00
Video 2: Real Life Example 00:05:00
Video 3: Quote by famous biostatistician 00:02:00
Video 4: Factors to be considered for test selection 00:03:00
Video 5: Univariate 00:02:00
Video 6: Confounding (1) 00:06:00
Video 7: Confounding (2) 00:05:00
Video 8: Comparing Difference 00:02:00
Video 9: Paired or Independent groups? 00:03:00
Video 10: Outcome Type 00:04:00
Video 11: Normality 00:05:00
Video 12: Groups 00:02:00
Video 13: Sample Size 00:04:00
Video 14: Regression 00:03:00
Video 15: Summary 00:01:00
Video 16: Example #1 00:01:00
Video 17: Example #1 (answers) 00:03:00
Video 18: Example #2 and #3 00:01:00
Video 19: Example #3 (answers) 00:03:00
Video 20: Example #4 and #5 00:03:00
Module: 6
Weekly Handouts (W4) 00:15:00
Weekly Handouts (W4) 1 00:05:00
Video 1: How to compare mean and median between two groups (1) 00:03:00
Video 2: How to compare mean and median between two groups (2) 00:06:00
Video 3: How to compare mean and median between two groups (3) 00:03:00
Video 4: Perform Student T-test to compute the P value to compare two means 00:06:00
Video 5: Perform parametric test 00:03:00
Video 6: Non-parametric test 00:04:00
Video 7: Student t-test using lock transformed outcome variable 00:04:00
Video 8: Mann-Whitney U-test using R 00:02:00
Video 9: Mann-Whitney U-test (Wilcoxon rank-sum test) 00:06:00
Video 10: Paired t-test 00:04:00
Video 11: Compute the p-value for paired t-test 00:04:00
Video 12: Check the paired t-test assumption 00:03:00
Video 13: Wilcoxon signed-rank test 00:06:00
Module: 7
Weekly Handouts (W5) 00:10:00
Video 1: Comparing binary outcome between groups (1) 00:03:00
Video 2: Comparing binary outcome between groups (2) 00:06:00
Video 3: Comparing binary outcome between groups (3) 00:02:00
Video 4: Computing P-value 00:06:00
Video 5: Compute the Rate (1) 00:04:00
Video 6: Result of the Rate 00:02:00
Video 7: Compute the Rate (2) 00:01:00
Video 8: Compare the Two Results 00:02:00
Video 9: Use the Rate 00:01:00
Video 10: Rate vs Proportion 00:03:00
Video 11: Risk ratio and risk difference (1) 00:06:00
Video 12: Risk ratio and risk difference (2) 00:02:00
Video 13: Risk ratio vs Odds ratio (1) 00:04:00
Video 14: Risk ratio vs Odds ratio (2) 00:05:00
Video 15: Risk ratio vs Odds ratio (3) 00:06:00
Video 16: Risk ratio vs Odds ratio (Case-control study) (1) 00:05:00
Video 17: Risk ratio vs Odds ratio (Case-control study) (2) 00:03:00
Video 18: How to compute odds ratio in R commander 00:04:00
Module: 8
Weekly Datasets,WEEK 6 00:05:00
Dataset Preparation 6 00:05:00
Video 1: Sample Size Computation 00:03:00
video 2: Impacts on p-value 00:06:00
Video 3: R01 and Consort 00:03:00
video 4: Statistical Hypothesis testing 00:06:00
Video 5: Power 00:01:00
Video 6: Computing Sample Size 00:04:00
Video 7: T-test Option and Dichotomous Option 00:06:00
Video 8: How to Graph 00:04:00
Video 9: Improving Analytical Power 00:02:00
Video 10: Comparing 2 Propotions 00:06:00
Video 11: Conclusion 00:02:00
Assessment
Submit Your Assignment 00:00:00
Certification 00:00:00

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