Behavioral Economics in Experimental Design and Data Analysis Training Course
Behavioral Economics in Experimental Design and Data Analysis Training Course empowers participants to design robust behavioral experiments, analyze complex datasets, and apply findings to real-world challenges.
Skills Covered
Course Overview
Behavioral Economics in Experimental Design and Data Analysis Training Course
Introduction
Behavioral Economics is revolutionizing how we understand human decision-making by integrating psychological insights into economic models. With businesses, governments, and researchers increasingly relying on data-driven insights, mastering experimental design and data analysis in the context of behavioral economics has become essential. Behavioral Economics in Experimental Design and Data Analysis Training Course empowers participants to design robust behavioral experiments, analyze complex datasets, and apply findings to real-world challenges.
This course blends theoretical foundations with practical tools to explore cognitive biases, decision heuristics, and incentive structures. Using R, Python, and experimental software, learners will develop hands-on skills in randomized controlled trials (RCTs), field experiments, and behavioral simulations. Whether you're driving policy, optimizing marketing strategies, or leading academic research, this course equips you to uncover actionable insights from behavioral data.
Course Objectives
- Understand core principles of behavioral economics and human decision-making
- Design rigorous behavioral experiments using randomized controlled trials (RCTs)
- Apply quantitative and qualitative data analysis techniques to behavioral data
- Utilize statistical software (R/Python/SPSS) for behavioral research
- Identify cognitive biases and heuristics in economic decision-making
- Conduct ethical behavioral research with informed consent and privacy compliance
- Develop behavioral interventions for public policy, marketing, and finance
- Interpret and visualize behavioral data using modern data tools
- Evaluate the internal and external validity of experimental studies
- Apply behavioral economics to nudge theory and behavioral policy design
- Translate behavioral insights into real-world business and policy applications
- Use A/B testing and multivariate testing in behavioral design
- Build predictive models using behavioral data and machine learning tools
Target Audiences
- Behavioral economists and researchers
- Policy analysts and public sector professionals
- Marketing and consumer behavior specialists
- Data scientists and statisticians
- UX/UI researchers and product designers
- Academic faculty and graduate students
- Social scientists and psychologists
- Business strategists and consultants
Course Duration: 5 days
Course Modules
Module 1: Foundations of Behavioral Economics
- Overview of traditional vs. behavioral economics
- Key concepts: bounded rationality, heuristics, prospect theory
- System 1 vs. System 2 thinking
- Behavioral game theory basics
- Role of incentives in decision-making
- Case Study: The Ultimatum Game and fairness norms
Module 2: Experimental Design Principles
- Designing hypotheses for behavioral studies
- Between-subjects vs. within-subjects designs
- Randomization and control techniques
- Avoiding experimenter bias
- Sample size and power analysis
- Case Study: Field experiment on default savings rates
Module 3: Conducting RCTs in Behavioral Research
- Components of a valid RCT
- Blinding and placebo considerations
- Managing treatment and control groups
- Attrition, compliance, and spillover effects
- Registration and pre-analysis plans
- Case Study: Behavioral RCT in vaccination uptake
Module 4: Data Collection and Survey Design
- Creating reliable behavioral survey instruments
- Using Likert scales and anchoring techniques
- Digital platforms for data collection
- Reducing response bias and fatigue
- Real-time behavioral tracking tools
- Case Study: Online decision-making in consumer surveys
Module 5: Statistical Analysis of Behavioral Data
- Descriptive vs. inferential statistics
- T-tests, ANOVA, regression models
- Interpreting effect sizes and significance
- Visualizing behavioral data in R/Python
- Addressing missing data and outliers
- Case Study: Impact of framing on financial decision data
Module 6: Advanced Data Techniques in Behavioral Economics
- Clustering and segmentation of behavior
- Predictive modeling using behavioral variables
- Introduction to machine learning for behavioral research
- Time-series and panel data in experiments
- Factor analysis for behavioral constructs
- Case Study: Predicting loan defaults using behavioral scoring
Module 7: Applications of Behavioral Economics
- Behavioral insights in public health
- Consumer behavior and marketing strategies
- Behavioral finance: nudging investor behavior
- Organizational behavior and HR practices
- Legal compliance through behavioral nudges
- Case Study: Reducing energy consumption via behavioral nudges
Module 8: Ethics, Policy Impact, and Communication
- Ethical considerations in behavioral research
- Informed consent and data protection laws
- Communicating results to non-technical audiences
- Scaling and sustaining behavioral interventions
- Evaluating behavioral policies post-implementation
- Case Study: Ethical dilemma in a financial behavior experiment
Training Methodology
- Interactive lectures with real-world examples
- Hands-on labs using R, Python, and Qualtrics
- Group projects and peer-reviewed experimental designs
- Weekly quizzes and formative assessments
- Case study analysis and class discussions
- Final capstone project with presentation of experimental results
Register as a group from 3 participants for a Discount
Send us an email: info@datastatresearch.org or call +254724527104
Certification
Upon successful completion of this training, participants will be issued with a globally- recognized certificate.
Tailor-Made Course
We also offer tailor-made courses based on your needs.
Key Notes
a. The participant must be conversant with English.
b. Upon completion of training the participant will be issued with an Authorized Training Certificate
c. Course duration is flexible and the contents can be modified to fit any number of days.
d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
e. One-year post-training support Consultation and Coaching provided after the course.
f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.