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Updated in [March 06th, 2023]

The course objective is to enable each student to enhance his or her quantitative scientific reasoning about problems related to human health. Biostatistics is about quantitative approaches - ideas and skills - to address bioscience and health problems. To achieve mastery of biostatistics skills, a student must "see one, do one, teach one." Therefore, the course is organized to promote regular practice of new ideas and methods.

The course is organized into 3 self-contained modules. Each module except the first is built around an important health problem. The first module reviews the scientific method and the role of experimentation and observation to generate data, or evidence, relevant to selecting among competing hypotheses about the natural world. Bayes theorem is used to quantify the concept of evidence. Then, we will discuss what is meant by the notion of "cause."
 
In the second module, we use a national survey dataset to estimate the costs of smoking and smoking-caused disease in American society. The concepts of point and interval estimation are introduced. Students will master the use of confidence intervals to draw inferences about population means and differences of means. They will use stratification and weighted averages to compare subgroups that are otherwise similar in an attempt to estimate the effects of smoking and smoking-caused diseases on medical expenditures.
In the final module, we will study what factors influence child-survival in Nepal using data from the Nepal Nutritional Intervention Study Sarlahi or NNIPPS. Students will estimate and obtain confidence intervals for infant survival rates, relative rates and odds ratios within strata defined by gestational period, singleton vs twin births, and parental characteristics.
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Learners can learn from this course a variety of biostatistics skills, such as the scientific method, Bayes theorem, point and interval estimation, stratification, weighted averages, and relative rates and odds ratios. They will also gain an understanding of the use of data to draw inferences about population means and differences of means, as well as the effects of smoking and smoking-caused diseases on medical expenditures. Additionally, learners will be able to apply their knowledge to real-world problems, such as the factors that influence child-survival in Nepal.

[Applications]
Upon completion of this course, students will have a better understanding of biostatistics and its application to human health. They will be able to use the scientific method and Bayes theorem to generate data and evidence relevant to selecting among competing hypotheses. Additionally, they will be able to use point and interval estimation, stratification, and weighted averages to compare subgroups and estimate the effects of smoking and smoking-caused diseases on medical expenditures. Finally, they will be able to estimate and obtain confidence intervals for infant survival rates, relative rates, and odds ratios within strata defined by gestational period, singleton vs twin births, and parental characteristics.

[Career Paths]
The career paths recommended to learners of this course include:

1. Biostatistician: Biostatisticians use statistical methods to analyze data related to health and medical research. They develop and apply statistical models to analyze data, interpret results, and provide advice on the design and implementation of research studies. With the increasing demand for data-driven decision making in the healthcare industry, biostatisticians are in high demand.

2. Epidemiologist: Epidemiologists use data to study the distribution and determinants of health-related states or events in specified populations, and the application of this study to the control of health problems. They use a variety of methods to collect and analyze data, including surveys, interviews, and laboratory tests. With the rise of global health concerns, epidemiologists are in high demand.

3. Data Scientist: Data scientists use data to develop insights and solutions to complex problems. They use a variety of methods to collect, analyze, and interpret data, including machine learning, artificial intelligence, and predictive analytics. With the increasing demand for data-driven decision making, data scientists are in high demand.

4. Health Informatics Specialist: Health informatics specialists use data to develop and maintain health information systems. They use a variety of methods to collect, analyze, and interpret data, including database management, data mining, and data visualization. With the increasing demand for data-driven decision making in the healthcare industry, health informatics specialists are in high demand.

[Education Paths]
Recommended Degree Paths:
1. Bachelor of Science in Biostatistics: This degree program provides students with a comprehensive understanding of biostatistical methods and their application to health-related research. Students will learn how to design, analyze, and interpret data from experiments and surveys, and how to use statistical software to analyze data. The degree also covers topics such as epidemiology, public health, and health policy. As the field of biostatistics continues to grow, this degree is becoming increasingly popular and in demand.

2. Master of Science in Biostatistics: This degree program provides students with a more advanced understanding of biostatistical methods and their application to health-related research. Students will learn how to design, analyze, and interpret data from experiments and surveys, and how to use statistical software to analyze data. The degree also covers topics such as epidemiology, public health, and health policy. This degree is becoming increasingly popular and in demand as the field of biostatistics continues to grow.

3. Doctor of Philosophy in Biostatistics: This degree program provides students with an in-depth understanding of biostatistical methods and their application to health-related research. Students will learn how to design, analyze, and interpret data from experiments and surveys, and how to use statistical software to analyze data. The degree also covers topics such as epidemiology, public health, and health policy. This degree is becoming increasingly popular and in demand as the field of biostatistics continues to grow.

4. Master of Public Health in Biostatistics: This degree program provides students with a comprehensive understanding of biostatistical methods and their application to public health research. Students will learn how to design, analyze, and interpret data from experiments and surveys, and how to use statistical software to analyze data. The degree also covers topics such as epidemiology, public health, and health policy. As the field of biostatistics continues to grow, this degree is becoming increasingly popular and in demand.