This online Principles Express course will introduce you to the critical concepts common to the analysis of quantitative research data, with special attention to survey data analysis. These concepts will help analysts, buyers of research services, and those designing research. Knowing how best to look at data and derive insights is critical to ensuring that the information has a positive impact on the business.
The analysis of quantitative data is integral to the research process. Information is gathered for a reason, usually to inform a business decision. Consequently, an inappropriate interpretation of the collected data can have disastrous results.
UGA offers introductory and advanced Data Analysis courses.
Because the analysis of quantitative data is a broad topic, there are two University of Georgia online, Principles Express courses devoted to it. This course is introductory in nature and has greater focus on survey data. Importantly, the concepts introduced in this course are foundational and have application even in situations where more advanced analytic techniques are applied.
The second is standalone, Principles Express course that focuses on more advanced analytic techniques.
Quantitative research requires flexibility.
Ideally, the analytical plan has been developed at an earlier stage — at the same time as the research design — so the basic approach to translating data into actionable insights is established before the data is collected. However, in the consultative role that the researcher must play, it is imperative to be adaptable when the planned analysis doesn't yield helpful findings. In this case, the researcher must be familiar with alternative methods and approaches that may reveal more valuable information.
In the data analysis stage of a project, the researcher reviews the data and pays particular attention to elements that will enable the development of insight about the business decision. This is achieved through the design and application of a meaningful analysis of the data. In order to be relevant, timely, and cost effective the key is to stay focused on the business decision and research questions.
Developing a data analysis plan.
The professional market researcher is not expected to have a complete understanding of all the data analysis techniques. The researcher’s key obligation is to manage the use of these techniques to develop and organize an analysis of the data that satisfies the information requirements of the project.
The most appropriate statistical methods should be selected when projecting findings to target populations and determining whether different groups' measurements are significantly different from each other. This course focuses on alternative statistical analysis methods and developing a data analysis plan.
The majority of the material in this course looks at survey data in the context of consumers. However, not all data is survey data and not all projects are with consumers. Therefore the material also covers topics like secondary data, B2B (business-to-business) market research, and healthcare research.
After completing this course you should be able to:
- Describe the process of creating an analysis plan, and give examples of alternative analytic purposes (e.g., explanatory versus confirmatory).
- Describe the key data sources.
- Name and define the key data types (nominal, ordinal, interval, ratio, etc.).
- Explain the process of matching analytic techniques to different situations and needs, and give examples.
- Summarize descriptive and visual approaches used to familiarize oneself with the data and to identify problems with the data.
- Explain how to assess the impact of missing responses, and select and apply appropriate remedies.
- State the reasons for and methods of statistically adjusting data; e.g., weighting, variable re-specification, and scale transformation.
- Assess the characteristics of the distribution of the data and explain the implications of normality, non-normality, skewness, and multimodal data.
- Illustrate the process for creating and testing hypotheses.
- Compare and contrast the differences between type I and type II errors, and their potential impact on business decisions.
- Describe the difference between statistical and business significance in the context of group comparisons, and explain the factors that have an impact on statistical significance.
- Describe the difference between association and causality, and the potential impact on business decisions and outcomes.
- Identify the major computer programs in current use in market research for the analysis of data.
- Explain how to turn findings into market research conclusions, link findings to business decisions, and create actionable recommendations.
Who Should Attend?
- Entry-level researchers looking for a solid introduction to quantitative data analysis.
- Mid-level staff seeking to expand their skillset.
- Experienced researchers looking to catch up with the latest developments.
- Corporations seeking professional development options for their internal training portfolio.
- Suppliers seeking courses for new-employee onboarding.
- Researchers whose job involves leading or contributing to project design.
- Analysts needing to understand how best to analyze quantitative data, and the pitfalls to avoid.
- Client-side researchers responsible for designing research and ensuring that the analysis leads to reliable insights.
- People just entering the research field who want to understand this important aspect of the research process.
- Enroll at any time
- Complete the course's required graded components within 30 days
- For more details on How Does “Introduction to Data Analysis” Course Work, please download the file.
- For Frequently Asked Questions, please download the file.
$359 - Standard Fee
$329 - Association Discount (Members* of: Insights Association; ESOMAR; Intellus Worldwide; ARF; AMA, and the attendees of TMRE 2018 and IIeX NA 2018.)
$50 - One-Month Extension (only one extension is granted per participant)
*Membership/Attendance will be verified.
Prepayment is required to be registered. Prices listed are per person (US Funds). Prices are subject to change.
Students successfully completing graded components earn a Digital Badge and 1.2 Continuing Education Units (CEU) from The University of Georgia. For details about the University of Georgia CEU, please download the file.
As a graduate of the course you will be recognized by industry associations, employers, peer groups and other professionals as having knowledge of the many data collection options that are available and for choosing the most appropriate method given the target population you need to reach. This recognition will help you advance in your company and the industry.
This course offers continuing education for research practitioners. If you are PRC certified through the Insights Association (IA), this course qualifies for 12 hours for continuing education. If you have any questions about PRC, please contact certificationATinsightsassociation.org or dial +1-202-800-2545.
CAIP Canada also recommends the course for candidates looking to fill in the gaps or gain a refresher in specific areas.
Ray Poynter – Managing Director, The Future Place & Founder of NewMR
Ray is the author of The Handbook of Mobile Market Research, The Handbook of Online and Social Media Research and the #IPASOCIALWORKS Guide to Measuring Not Counting. He is the founder of NewMR.org, editor of the ESOMAR book Answers to Contemporary Market Research Questions, and is the Managing Director of The Future Place, a UK-based consultancy, specializing in training.
Ray has spent the last 35 years at the intersection of innovation, technology, and Market Research, during which time Ray has held director level positions with Vision Critical, Virtual Surveys, The Research Business, Millward Brown, Sandpiper and IntelliQuest.