Welcome to the Biostatistics Course at the Institute for Applied Research and Training (IART)!
Over the next few weeks, we will delve into the intricacies of biostatistics, exploring its principles and practical applications.
Throughout this course, we will demystify statistical methods in biological research, examining the fundamental tools used to tabulate, analyze data, and interpret data in various biological contexts. From study design, and data exploration to data analysis, we’ll explore the techniques and methodologies employed in statistical research, gaining a deeper understanding of the statistical tools that drive modern biological investigations.
Our exploration will span a range of applications, delving into the critical role of statistical methods that aid in tackling real-world challenges and fostering evidence-based solutions in health and beyond. By the end of this course, you’ll not only have a comprehensive understanding of biostatistics but also the skills and knowledge to critically evaluate statistical approaches in biological research.
Get ready to immerse yourself in the fascinating world of biostatistics, where you will analyze, explore, and broaden your horizons!
This course will comprise several modules, each covered on a weekly basis.
Course Duration: 1 Month
Eligibility:- Under Graduate, Graduate and Post Graduate
Mode of Instruction: English and Hindi
Week 1 - Module 1:
Chapter 1: An Introduction to Statistics and its Application in Biostatistics.
Chapter 2: Introduction to Data Types.
Chapter 3: Overview of Descriptive Statistics.
Chapter 4: Hands-on-
- Preparation of Data in MS Excel
- Exploration of data (Descriptive Statistics & Graphs in MS Excel).
Week 2 - Module 2:
Chapter 1: Basics of Statistical Inference.
Chapter 2: An Introduction to Probability and Distribution Theory.
Chapter 3: Comparison of two groups: Categorical and Continuous outcomes.
Chapter 4: Hands-on-
Applying Parametric and Non-parametric tests for comparison of two groups in GraphPad.
Week 3 - Module 3:
Chapter 1: Comparison of three groups: Categorical and Continuous outcomes.
Chapter 2: Hands-on-
Applying Parametric and Non-parametric tests for comparison of three groups in GraphPad.
Chapter 3: Correlation and Linear Regression.
Chapter 4: Multiple Predictor Variables: Linear and Logistic Regression.
Week 4 - Module 4:
Chapter 1: Hands-on-
Correlation (statistical test and Graphical representation).
Chapter 2: Hands-on-
Applying Simple and multiple Linear regression in GraphPad.
Chapter 3: Hands-on –
Applying Binary Logistic Regression with one and multiple predictor variables in GraphPad.
Chapter 4: Odds Ratio vs. Relative Risk.
Applications and Job Opportunities for Biostatistics Course:
Applications:
- Research Assistant: Analyze data for research projects in healthcare, public health, and life sciences.
- Clinical Research Associate (CRA): Monitor clinical trials for data accuracy and adherence to protocols.
- Public Health Analyst: Analyze data to understand and address public health issues.
- Biostatistician: Design and analyze studies to answer scientific questions in healthcare and biological research.
- Epidemiologist: Investigate the patterns and causes of diseases in populations.
- Quality Assurance (QA) Analyst: Monitor and ensure the quality of data in healthcare organizations.
Job Opportunities (within 1-2 years of experience):
- Entry-level Biostatistician: Assist senior biostatisticians with data analysis and reporting.
- Data Analyst: Analyze data for businesses or organizations in healthcare, pharmaceuticals, or other industries.
- Biometric Analyst: Analyze risks and design insurance plans for health insurance companies.
- Statistician: Apply statistical methods to solve problems in various industries.
- Research Coordinator: Coordinate research projects and manage data collection and analysis.
Note: This is not an exhaustive list, and the specific opportunities you qualify for will depend on your additional skills and experience.
Additional :
- The hands-on focus on data preparation, exploration, and analysis using MS Excel and GraphPad makes this course particularly valuable for entry-level positions.
- Combining this course with additional training in programming languages like R or Python would further enhance your job prospects.
- Networking with professionals in the field through online communities or attending industry events can help you learn about job opportunities and gain valuable insights.
Note: Thesis work/projects are also available for Master's students and can be customized according to requirements.
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