Welcome back everybody. The topic for this video is translating user research to support design. Now in the last few lessons we've been concentrating on gathering data from users and doing user research. So you wind up with data, well now what? In the next series of lectures, what we're going to be doing, is giving you some techniques for analyzing that data, for making sense of it, and then for capturing the results in representations that can be used to guide design. So, let's talk a little bit about the data analytic methods you'll be learning. Roughly you'll be learning two general classes and methods, we'll call them Qualitative and Quantitative. Qualitative methods are tailored to work on data that's expressed as text. Now, this typically means are the kind of responses you get from interviews where people fill out forms or you take notes on the responses, notes that you've taken from observing people as they work or as they do the activities, online information, lets say information from documents that are produced online. So, qualitative methods are structured ways that you, as a person, as an analyst, can go through this textual data and discover patterns or themes, concepts that emerge, things like user needs and requirements. So qualitative methods let you do that sort of thing. Quantitative methods, on the other hand, are applied to structured or numeric data. Things like logs of user activity, or large scale responses to surveys, things like that. And the way you analyze those, you end up with things like statistics, graphs, charts, overview aggregate numbers that give you a picture of what is in the data. Now once you've analyzed this data, or once you've analyzed your data, you need to come up with representations of this data that can be used to guide your design decisions. And over the next few lectures, we're going to be talking through a number of such representations. So personas, and we've touched on most of these in an earlier course as well. So personas are model users based on user research, you noticed patterns, you cluster users together who share common reactions, or just common goals, attitudes, responses and so on, and then you come up with a fictional user who represents the aggregate of user attributes. And this is useful in focusing design and making sure that your design can support this class of users. Usage stories are rich descriptions of system usage and in some cases this system may not exist or if it exists It may not do the things that you talk about this in this narrative, in this users story. And the point of a usage story is to serve as a vision for what could be, for what might be, and gather interest and assess whether this is a vision that people think is actually worth implementing. A task is a more focused description of what a particular user or user group is trying to accomplish, and once you have gone to the trouble of defining tasks, then these can be used to guide design. Namely, you want to make sure that your system can actually allow users to accomplish this task. And a scenario, or walkthrough scenario, is a way, a specific way that a task can be accomplished in a specific interface. So once you have a task, once you have an interface, this is a step-by-step sequence of actions for accomplishing that task in that interface. So that's a quick overview of what you'll be learning in the next few lectures, and we will be going into detail on all of those things. We'll look forward to seeing you next time.