Gamer lingo seems to be everywhere today, from finding power ups, to leveling up, to finding the closest Pokemon Go gym (mine happens to be our local Staples store).
If you’re a die-hard gamer the following will be old hat to you. For the rest of us, to “level up” is to get to get to the next level of a game; you do this by earning enough experience points. Leveling up usually means you gain access to new places, find new challenges, and more.
Och om du letar efter ett roligt sätt att tjäna några erfarenhetspoäng utan risk att förlora några pengar, kanske du vill prova att spela gratis roulette.
But did you know, as gamer lingo goes mainstream, that “leveling up” also means making a move in your life or career for the better? It’s part of mainstream speak now to talk about leveling up your skills and your job: “I feel stale in this role, it’s time to level up.”
Whether you are going to be “hands on keyboard” or working with a data analyst, learning factor and cluster analyses techniques will help to level up your skills and add some statistics experience points to your arsenal (such as earning Professional Researcher Certification credits or counting towards an Insights Association Certificate in Quantitative Research Principles).
These “data reduction” techniques of factor and cluster analyses aim to reduce mountains of data into manageable chunks while remaining true to the original results. Factor analysis helps to reduce the number of variables making it easier to run cluster analyses, and cluster analysis explores what previously undefined groupings may exist in the dataset.
To use factor and cluster analyses, it’s important to understand:
- When to use these techniques
- How to use these techniques
- How to ensure your questionnaire is set up to allow for performing factor and cluster analyses
- How to work with an analyst who may be assisting you with the actual statistical analysis
- How to accurately report out on the analysis results
In our upcoming course Introduction to Factor & Cluster Analysis, instructor Steven Struhl guides students through the topics above, as well as covering common applications for cluster and factor analysis such as market segmentation and customer satisfaction research.
It’s time to level up. Game on!
Looking to get certified? This class qualifies for PRC credits and is also an approved class for the Insights Association Certificate in Quantitative Research Principles.
