Statistics Made Simple

For over 10 years, Creascience's instructors have been developping original teaching tools geared toward a non-technical presentation of fundamental statistical tools and concepts. Their areas of expertise encompass research and development to market research. The team's reputation is largely due to its excellent ability to explain complex mathematical concepts in laymen's terms and to provide participants with tools that can be used right after the training.

What Makes Our Training Sessions Different?

Creascience has established a strong reputation for the development of innovative training methods and creative knowledge transfer thinking. Whether you attend a public or an in-house session, our courses are designed to maximize learning and increase self-sufficiency in the use of statistical methods. A variety of proven strategies are used to achieve this goal, making our classes unique in many regards:

Small class size for a personalized follow-up

You have questions to ask ? We make sure that there is enough time to address them. This is why class size is limited to 10 people per session.

Avoiding information overload: training programs adapted to the duration of the session

It is unrealistic to believe that participants will grasp all subtleties of several complex methods in a day or two. Therefore, instead of packing our courses with as many statistical methods as possible, we prefer to focus on fundamental but practical concepts underlying the methods. By mastering these tools, participants can both correctly use the methods and interpret the results, and they also are in a good position to further explore more advanced topics by themselves.

Critical Presentation of Methods

All statistical methods have strengths and limitations that users need to be aware of. To avoid misuse and misinterpretation, such aspects are emphasized during our sessions. Case studies are used for this purpose and exhibit both good and not so good usage of methods - with a more appropriate alternative in the latter case -.

Descriptive Examples Instead of Equations

For most statistical techniques, mathematical theory is not the best way to help participants understand the conditions of use and the interpretation of results. The underlying statistical theories of each technique are touched on just enough to keep participants out of trouble without overwhelming them with equations. Our teaching modules are geared toward non-technical presentations using applications taken from a variety of fields. These are used to explain how methods work as well as problem likely to be encountered in practice and remedial measures.

Varied Case Studies and Exercices

Fundamental concepts covered in the session are deepened by exercises and case studies chosen for their relevance and integration in the teaching sequence. All sessions include group discussions on specific problems and practical issues, interpretation of software output and hands-on applications.

Instructors Share Their Experience and Insights

All our instructors possess several years of experience using the techniques that they teach. They share this experience with participants to provide them with insights regarding practical aspects, pitfalls and creative applications. To further enhance the learning experience, real-life case studies taken from their practice are used to illustrate the scope and the limitations of the techniques.

Use Your Own Statistical Software

A specific statistical package is never imposed for hands-on sessions. On the contrary, we strongly encourage participants to use their own software if they have one. Otherwise, we can help determine the one that best suits their needs. Instructors are familiar with most statistics packages and can very easily assist attendees. Participants agree that using their own software package is a big plus since they can immediately apply what they learned when they return to their office. Moreover, many have pointed out that it is a real advantage to have different software within a given session as it allows comparing their relative strenghts and weaknesses.