Analysis of Survey Data, London – 24, 25 May 2023

Product code: Analysis of Survey Data -London-2023


May 24, 2023 - May 25, 2023

Do you create consumer surveys or questionnaires yet feel lost or under-equipped in trying to make the most out of the data? Once you have collected data from hundreds, perhaps thousands of consumers – where do you begin in trying to draw meaningful conclusions, that can influence business decision making and deliver true insights? Do you feel somewhat anxious with the many statistical methods that you’ve heard about but don’t really understand how to apply them, or what differentiates one method from another?

If you feel like one of the above applies to you, don’t worry — you’re not alone! Perhaps the best place to start is to think about the question you’re trying to answer with your survey, i.e., what is your overall objective? Below are four scenarios that our common in our experience:

Scenario 1:

Exploratory survey looking to understand relationships between several variables (most likely of different types, for example some are qualitative or quantitative)
To analyse data in this scenario: You are likely to need cross tabulations including chi-square tests, analysis of variance (ANOVA), correspondence analysis and even clustering methods.

Scenario 2:

I have liking or preference data and want to relate this data to demographic, usage and attitude and purchase data.
To analyse data in this scenario: You are likely to want to know about regression, factor analysis, and/or multiple correspondence analysis and clustering methods

Scenario 3:

I’m trying to measure a latent variable (e.g., complexity or satisfaction) through several survey items, and/or perhaps using a published questionnaire such as the Big 5 Personality Traits.
How do I analyse the data?
To analyse data in this scenario: You will need to know about factor analysis and clustering methods

Scenario 4:

I’m in the early stage of product development and want to survey consumers regarding their associations and expectations to a specified concept that we’ve developed (e.g., “fresh”, “raw” or “natural”). How do I develop a survey, how many respondents are required and how to analyse the data?
You will likely need to know about analysis of variance, regression and clustering methods, and analysing textual data


This comprehensive two day face-to-face course covers all of the above methods and more, enabling you to gain full insight into the methods you need to answer business questions. No matter what your survey is, there is a method to objectively combine the data using statistical methods.

Some of the analysis methods above also fall under the category of Machine Learning techniques.

By the end of the course you will have practised several techniques with worked examples using the XLSTAT statistical software and have worked solutions to use, for when you repeat these analyses on your own back at your office.

Participants can choose to attend either one or both of the two days. If you only choose to attend Day 2, it is expected you will have a good understanding of basic statistics including variability, statistical significance, ANOVA etc, and have experience of using XLSTAT. No previous experience of statistics or of using XLSTAT software is required if you attend Day 1.




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Other course information


Day 1 – Survey Design and Analysis Essentials
  1. Survey Design Essentials
    1. Identify your key objectives
    2. Survey design top tips
    3. Survey representativeness
    4. Bias
    5. Sample size – do you have enough data?
  2. Managing misleading data
    1. Data cleaning & pre-processing
    2. Dealing with Missing data
    3. Causation vs correlation
  3. Simple summaries of the responses and looking for associations
    1. Data types
    2. Cross tabs and chi-square tests
    3. Correlation
    4. Correspondence analysis and Visualizations
  4. Making comparisons, looking for trends and patterns (across products, between groups, over time, etc.)
    1. Analysis of Variance
    2. Regression
    3. Multiple Correspondance Analysis (MCA)
Day 2 – Looking Deeper into Survey Analysis: Identifying and Quantifying Trends and Patterns
  1. Segmenting your data into groups of people that behave/answer similarly to identify key customer groups
    1. AHC clustering
    2. K-Means clustering
    3. Latent Class clustering
  2. Measuring latent concepts and condensing my survey into themes
    1. Factor analysis
  1. Using a body of evidence for decision making – converting data into insight
    1. Linking back to objectives
    2. Telling a story
    3. Presenting technical information to non-technical people


The Analysis of Survey Data Course will be led by Gemma Hodgson and Joshua Brain.

Follow this link to be introduced to your trainers

Course Notes

  • 2 day face-to-face course – you can attend either Day 1 or Day 2 or both days
  • Your own laptop is required with XLSTAT Installed (if you do not have XLSTAT already, you can download the trial for the course and then purchase afterwards if you want to buy it
  • Price includes refreshments and lunch but not travel or accommodation. (We advise you do not book travel or accommodation until course is confirmed as going ahead 14 days before as no refunds can be given for those expenses – see cancellation policy below)

Currently, the course is planned to run at The Stanley Building, 7 Pancras Square, Kings Cross, London N1C 4AG, subject to booking numbers. For directions and further information use the following link:

We offer a 10% discount on registrations when two or more people from the same company register for the same course at the same time. We also offer a 10% discount for members of academia – please choose the appropriate option when purchasing.

Registration Policy
Registration is not final until payment is received. Unpaid spaces will be opened to new registrants 30 days ahead of course.

Payment can be made in GBP, EUR or USD. Please choose the appropriate currency when you checkout.

Refund policy
Cancellation of registration can be made up to 14 days ahead, and return of payments, minus reasonable administrative expenses, will be made for these cancellations. Cancellations within 7 days of the course start will receive a credit for a future course. Registrants who fail to attend or cancel less than 14 days prior to the seminar start date are responsible for the entire fee. Substitution of another person for the same course may be made at any time as long as payment is made.

Course Cancellation
Qi Statistics Ltd retains the right to cancel the course 14 days before the start date if less than 4 delegates have registered by that date. Please contact us directly if you have any queries in this regard.