This course offers an introductory overview of the fundamental and foundational biostatistical concepts and methods that are critical in the field of public health. Emphasizing the application and interpretation of biostatistical methods, it covers a broad spectrum of topics including graphical and numerical descriptive statistics for data summarization and exploration; probability theory with an emphasis on the binomial (discrete) and normal (continuous) distributions, which are crucial for understanding statistical inference; and inferential statistics, encompassing point estimation, interval estimation, and hypothesis testing to support evidence-based decision-making. The course also introduces nonparametric statistical methods for analyzing data without assuming a specific distribution.
Outcomes: Explain the fundamental concepts of probability and statistics as they apply to public health data; Analyze graphical and numerical descriptive statistics to effectively summarize public health data; Evaluate basic inferential statistical methods, including hypothesis testing and confidence intervals, to draw and justify conclusions from public health data; Justify the appropriate statistical methods for specific public health research scenarios based on the data type and research question; Communicate statistical information effectively to various audiences within the field of public health.
Outcomes: Explain the fundamental concepts of probability and statistics as they apply to public health data; Analyze graphical and numerical descriptive statistics to effectively summarize public health data; Evaluate basic inferential statistical methods, including hypothesis testing and confidence intervals, to draw and justify conclusions from public health data; Justify the appropriate statistical methods for specific public health research scenarios based on the data type and research question; Communicate statistical information effectively to various audiences within the field of public health.