Google Interview Hacks

What projects would you be interested in working on? * Applications of the HEART metrics within usability testing * how we can apply behavior modification and motivational theories to improve a current system or flow such that it improves their happiness, engagement, adoption, overall life satisfaction, relationships * Understanding and defining what metrics would best capture human behavior * Improving lifestyles and cognitive behaviors by improving app awareness and/or activation, discovery, accessibility, and usability. Exploring the use cases that will improve these factors * Understanding various demographics behavior with apps, organizing them, accessing them, learning about them, motivations behind downloading and searching apps

Imagine doing research in a specific UX in which half the people hate a specific design aspect (where it's actually completely impossible that this would ever happen in that particular UX). How would you solve that Look at the big picture -- what are the tradeoffs for this design in terms of stakeholder goals? If this is specifically a design issue, would users hate it so much that would not use the ? Does this design that hate have other benefits such as error reduction or lower task reduction? I would bring these ideas into the discussion to help team members zoom out and evaluate the bigger picture in a more service design rather than interface design resolution.

How do you determine which task to use? Discuss with stakeholders and users about what the important goals are for the product and things that are even possible to do through interviews. Are we trying to look for action or intent? Action is more straightforward performance-related numbers and I would just conduct stakeholder and user interviews to discuss about what the important goals are for the product and things that are even possible to do. Intent would be more interesting, that would have to include developing metrics to evaluate content, motivation and attitudes as well as thhe collective performance based on user actions or lack of action. Something like that HEART metrics would influence what tasks I use

How do you determine which task to use? Discuss with stakeholders and users about what the important goals are for the product and things that are even possible to do through interviews. Are we trying to look for action or intent? Action is more straightforward performance-related numbers and I would just conduct stakeholder and user interviews to discuss about what the important goals are for the product and things that are even possible to do. Intent would be more interesting, that would have to include developing metrics to evaluate content, motivation and attitudes as well as thhe collective performance based on user actions or lack of action. Something like that HEART metrics would influence what tasks I use

How many tasks to ask a specific user? No definite answer to what is enough (especially since you don't want to overwhelm/pressure them or make them believe it is time-based) prepare a set of tasks that you can ask them as well as potential probing questions to complete within an allotted time frame (i.e. how many tasks can you fit in is the more important question)

Should I run a field visit or usability test? A field visit tells you if you're designing the right thing (big picture). A usability test tells you if you've designed the thing right (microscope). For example, your product might perform fine in a usability test but it will fail if people don't really care about the tasks you've asked them to complete. • Is there a user problem to be solved? (If unsure, carry out field research). • Have we solved it? (If unsure, carry out usability testing).

Name an alternative to one-way ANOVA for independent groups (where ANOVA assumptions not met) ?  Name an alternative to Repeated measures ANOVA?  What would be suitable follow-up tests to use instead of T-tests for each respectively? To be used when your data does not meet ANOVA assumptions (e.g. not normally distributed and small sample) Not as powerful as parametric tests Based on 'ranked' data rather than means, so not skewed by extreme scores Kruskal-Wallis: alternative to one-way ANOVA for independent groups Friedman's ANOVA: alterative to RM ANOVA Use pairwise comparisons to follow up if significant (reducing alpha level): Mann-Whitney Tests - independent groups Wilcoxon Test - related groups