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    QUANTITATIVE DATA 

    FOR DECISION-MAKING

    • Home
    • Team
    • Courses 
      • R Coding and Biostatistics
      • Mathematical Modeling
      • Schedule of Courses
    • Contact
    • …  
      • Home
      • Team
      • Courses 
        • R Coding and Biostatistics
        • Mathematical Modeling
        • Schedule of Courses
      • Contact
      Student Portal
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      • Biostatistics I (with Intermediate R) for Public Health Practitioners and Researchers in Liberia

         

         

        Congratulations on successfully completing the course. See below for a comprehensive list of skills and concepts covered.

      • Class 1

        • Characterizing variables as either continuous or categorical

        • Identifying the appropriate function to use to generate descriptive statistics in R

        • Interpreting the results from descriptive statistics

        • Searching for open access articles

        • Documenting observations about public health in the Liberia context

        Class 2

        • Generating bar plots and balloon plots in R

        • Implementing the steps to formally test independence between two variables

        • Calculating the chi-squared test statistic

        • Implementing the chi-squared test in R

        • Recognizing when the Fisher’s exact test is more appropriate

        Classes 3-4

        • Performing the t-test and ANOVA in R

        • Understanding one-tailed versus two-tailed tests

        • Investigating the assumptions of the t-test

        • Visualizing associations between continuous and categorical variables

        • Performing hypothesis testing to arrive at a statistical conclusion

        Class 5

        • Recognizing outliers and their influence on distributions

        • Characterizing distributions of continuous and discrete variables

        • Investigating the assumptions of the t-test

        • Performing the ANOVA and Tukey’s HSD in R

        • Concluding about significant differences in distributions among three or more groups

        Class 6 (Full Example - Correlation Coefficient)

        • Investigating associations between two continuous variables

        • Recognizing nonparametric tests as alternatives when assumptions are not met

        Class 7 (Full Example - T-Test)

        • Replacing variables with data recognized as an updated class

        • Investigating associations between two continuous variables

        • Recognizing nonparametric tests as alternatives when assumptions are not met

        • Using realistic/unclean data to conduct a bi-variable analysis with appropriate checking of assumptions

        Class 8 (Full Example - ANOVA)

        • Using realistic/unclean data to conduct a bi-variable analysis with appropriate checking of assumptions

        • Investigating associations between continuous variables and categorical variables

        • Recognizing nonparametric tests as alternatives when assumptions are not met

        Class 9 (Full Example - Chi-Squared Test)

        • Using realistic/unclean data to conduct a bi-variable analysis with appropriate checking of assumptions

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