Module #1 Introduction to Quantitative Analysis in Veterinary Epidemiology Overview of the importance of quantitative analysis in veterinary epidemiology, course objectives, and expected outcomes
Module #2 Descriptive Statistics in Veterinary Epidemiology Descriptive statistics, data types, and measures of central tendency and variability in veterinary epidemiological data
Module #3 Data Visualization in Veterinary Epidemiology Introduction to data visualization principles, types of plots, and best practices for visualizing veterinary epidemiological data
Module #4 Probability Theory and Concepts Basic probability concepts, probability rules, and conditional probability in the context of veterinary epidemiology
Module #5 Statistical Inference in Veterinary Epidemiology Introduction to statistical inference, hypothesis testing, and confidence intervals in veterinary epidemiology
Module #6 Study Design in Veterinary Epidemiology Types of study designs, experimental and observational studies, and sampling strategies in veterinary epidemiology
Module #7 Measures of Disease Frequency Incidence rates, prevalence, and mortality rates in veterinary epidemiology, with examples and case studies
Module #8 Measures of Disease Association Odds ratio, relative risk, and correlation coefficients in veterinary epidemiology, with examples and case studies
Module #9 Diagnostic Test Evaluation Sensitivity, specificity, positive and negative predictive values, and receiver operating characteristic (ROC) curves in veterinary epidemiology
Module #10 Survival Analysis in Veterinary Epidemiology Introduction to survival analysis, Kaplan-Meier estimates, and Cox proportional hazards model in veterinary epidemiology
Module #11 Linear Regression in Veterinary Epidemiology Introduction to simple and multiple linear regression, model assumptions, and interpretation of coefficients in veterinary epidemiology
Module #12 Logistic Regression in Veterinary Epidemiology Introduction to logistic regression, odds ratios, and model interpretation in veterinary epidemiology
Module #13 Generalized Linear Mixed Models (GLMMs) in Veterinary Epidemiology Introduction to GLMMs, model specification, and interpretation of results in veterinary epidemiology
Module #14 Time Series Analysis in Veterinary Epidemiology Introduction to time series analysis, autoregressive integrated moving average (ARIMA) models, and seasonal decomposition in veterinary epidemiology
Module #15 Spatial Analysis in Veterinary Epidemiology Introduction to spatial analysis, spatial autocorrelation, and spatial regression in veterinary epidemiology
Module #16 Risk Analysis in Veterinary Epidemiology Introduction to risk analysis, risk assessment, and decision analysis in veterinary epidemiology
Module #17 Machine Learning in Veterinary Epidemiology Introduction to machine learning, supervised and unsupervised learning, and model evaluation in veterinary epidemiology
Module #18 Model Validation and Selection Model validation techniques, model selection criteria, and avoidance of overfitting in veterinary epidemiology
Module #19 Veterinary Epidemiology Software and Tools Overview of software and tools commonly used in veterinary epidemiology, including R, Python, and Excel
Module #20 Data Management and Quality Control Best practices for data management, data quality control, and data cleaning in veterinary epidemiology
Module #21 Ethics and Communication in Veterinary Epidemiology Ethical considerations, communication strategies, and reporting guidelines in veterinary epidemiology
Module #22 Case Study 1:Investigating an Outbreak Real-world example of investigating an outbreak, with hands-on practice using epidemiological methods and software
Module #23 Case Study 2:Analyzing Surveillance Data Real-world example of analyzing surveillance data, with hands-on practice using statistical methods and software
Module #24 Case Study 3:Evaluating a Diagnostic Test Real-world example of evaluating a diagnostic test, with hands-on practice using statistical methods and software
Module #25 Course Wrap-Up & Conclusion Planning next steps in Quantitative Analysis in Veterinary Epidemiology career
