Public Opinion Polling and Survey Methods Training Course

Public Opinion Polling and Survey Methods Training Course

Introduction

Public opinion polling and survey methods are critical tools for understanding societal trends, informing policy, and guiding strategic decisions in politics, business, and social science research. Public Opinion Polling and Survey Methods Training Course provides a hands-on, practical approach to mastering the latest methodologies and best practices in the field. Participants will learn to design, implement, and analyze surveys that produce accurate and reliable data, enabling them to interpret complex information and draw meaningful conclusions.

In an age of data-driven insights and evidence-based decision-making, the ability to conduct rigorous public opinion research is more valuable than ever. This course goes beyond theoretical concepts to cover practical applications, from crafting effective survey questions to leveraging advanced data analysis techniques and navigating the ethical challenges of modern research. By completing this program, participants will be equipped with the essential skills to contribute to informed public discourse and professional research initiatives, ensuring their work is both impactful and methodologically sound.

Course Duration

10 days

Course Objectives

1. Design and develop scientifically sound survey research and polling instruments.
2. Understand and apply various sampling techniques to ensure a representative sample and reduce bias.
3. Formulate clear, unbiased, and effective questionnaires and survey questions.
4. Master data collection methods including online, telephone, and face-to-face surveys.
5. Perform quantitative data analysis using statistical software like R, SPSS, or Stata.
6. Interpret and visualize survey data to communicate findings effectively.
7. Identify and mitigate common sources of survey error and sampling bias.
8. Understand the ethical considerations and professional standards in public opinion research.
9. Conduct pre-election polls and voter behavior analysis.
10. Use survey experiments to test causal relationships and measure public attitudes.
11. Apply advanced weighting and imputation techniques for complex survey data.
12. Translate polling results into actionable strategic insights for campaigns, policy, or marketing.
13. Stay current with emerging trends in digital polling and social media research.

Target Audience

1. Political Campaign Staff and Strategists
2. Public Relations and Communications Professionals.
3. Market Research Analysts.
4. Government and Policy Analysts.
5. Journalists and Media Professionals
6. Academics and Researchers
7. Non-profit and Advocacy Professionals.
8. Data Analysts and Scientists

Course Modules 

Module 1: Foundations of Public Opinion Research

• Introduction to public opinion and its role in society.
• The evolution of polling from straw polls to scientific surveys.
• Key terms: population, sample, census, and parameter.
• Ethical principles and best practices in survey research.
• Case Study: The 1936 Literary Digest poll failure and what it taught us about sampling bias.

Module 2: Survey Design and Questionnaire Development

• Principles of effective questionnaire design.
• Writing clear, concise, and unbiased survey questions.
• Scales and measurement: Likert scales, semantic differential, and rating scales.
• Question order, routing, and survey flow.
• Case Study: Redesigning a biased political survey to be more neutral and effective.

Module 3: Sampling Theory and Techniques

• Probability sampling methods: simple random, stratified, and cluster sampling.
• Non-probability sampling: convenience, quota, and snowball sampling.
• Calculating sample size and margin of error.
• Understanding and minimizing non-response bias.
• Case Study: Sampling a specific voter demographic for a local political campaign.

Module 4: Data Collection Methods

• Online surveys: using platforms like Qualtrics, SurveyMonkey, and Google Forms.
• Telephone polling: Random Digit Dialing (RDD) and new challenges with mobile phones.
• Face-to-face interviews and mail-in surveys.
• Mixed-mode surveys and their advantages.
• Case Study: Choosing the best data collection method for a public health survey in a rural area.

Module 5: Introduction to Survey Data Analysis

• Cleaning and preparing raw survey data.
• Descriptive statistics: mean, median, mode, and standard deviation.
• Exploring data distribution and creating frequency tables.
• Basic cross-tabulation and pivot tables.
• Case Study: Analyzing descriptive statistics from a recent national consumer survey.

Module 6: Advanced Statistical Analysis

• Inferential statistics: t-tests, ANOVA, and chi-square tests.
• Correlation and simple regression analysis.
• Introduction to multivariate analysis.
• Using statistical software (e.g., SPSS, R) for analysis.
• Case Study: Using regression analysis to determine the factors influencing voter support for a new policy.

Module 7: Weighting and Data Adjustment

• Understanding the need for weighting in survey data.
• Common weighting techniques: raking and post-stratification.
• When and how to apply weights to a dataset.
• Interpreting weighted vs. unweighted results.
• Case Study: Correcting for demographic imbalances in a survey sample using raking.

Module 8: Data Visualization and Reporting

• Principles of effective data visualization.
• Creating compelling charts and graphs (bar charts, line graphs, pie charts).
• Writing professional and impactful survey reports.
• Presenting findings to different audiences.
• Case Study: Developing a comprehensive report and infographic for a client based on a customer satisfaction survey.

Module 9: Political and Election Polling

• Pre-election polls, tracking polls, and exit polls.
• Forecasting election outcomes and understanding predictive models.
• Analyzing voter behavior and political demographics.
• Identifying "likely voters" and managing turnout models.
• Case Study: Critically evaluating and deconstructing a series of recent pre-election polls.

Module 10: Digital and Social Media Polling

• The rise of online panels and social media as data sources.
• Challenges and opportunities of digital polling.
• Sentiment analysis and text mining for qualitative insights.
• Ethical considerations with scraping social media data.
• Case Study: Using social media sentiment analysis to gauge public reaction to a brand campaign.

Module 11: Survey Experiments

• Introduction to experimental design in surveys.
• Testing causal hypotheses with A/B testing and split-ballot experiments.
• Measuring the impact of question wording, priming, and framing effects.
• The role of placebo and control groups.
• Case Study: Designing a survey experiment to measure the effect of different message framings on public opinion about climate policy.

Module 12: Qualitative Methods in Polling

• Introduction to focus groups and in-depth interviews.
• Combining qualitative and quantitative data for a richer understanding.
• Recruiting and moderating effective focus groups.
• Coding and thematic analysis of qualitative data.
• Case Study: Using a focus group to understand why survey respondents hold a particular opinion.

Module 13: Advanced Analytics and Machine Learning

• Introduction to machine learning for survey data.
• Predictive modeling and classification.
• Using unsupervised learning to find patterns in data.
• Applying models to a new dataset.
• Case Study: Building a predictive model to identify which consumers are most likely to purchase a new product.

Module 14: Practical Project and Application

• Participants will work in teams to design and field a mini-survey on a topic of their choice.
• They will apply all the skills learned throughout the course: questionnaire design, sampling, data collection, and analysis.
• Peer review and feedback sessions on project designs.
• Presentation of findings to the class.
• Case Study: Presenting final project findings and strategic recommendations to a panel of "clients."

Module 15: Future of Polling and Emerging Trends

• The impact of AI and automation on survey research.
• The challenge of declining response rates and how to address them.
• New frontiers in data collection: mobile apps, wearables, and big data.
• Maintaining public trust in polling in an age of misinformation.
• Case Study: A forward-looking discussion on how pollsters can adapt to a rapidly changing media and technology landscape.

Training Methodology

• Interactive Lectures: Facilitated discussions, not just one-way information delivery.
• Case Study Analysis: In-depth examination of historical and contemporary movements to extract lessons.
• Group Exercises & Simulations: Participants work in teams to apply course concepts to real-world scenarios.
• Guest Speakers: Activists and leaders share their experiences and insights.
• Action Planning: Participants develop a personal or organizational action plan for a specific cause.

Q&A and Feedback Sessions: Open forums for discussion and peer learning

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.