![]() The structured data are things like the ingredients, the oven temperature, how many calories a serving has, and how long you cook the food. ![]() Let's say you're looking at a recipe on your favorite online cooking blog. Instead of asking someone why they do something, you’re finding out what they do, or how many people do that thing, or how often – and so on. Instead of talking to people and getting their opinions, you’re asking them yes or no questions. Think data you can put in a spreadsheet and analyze. Quantitative research, on the other hand, involves collecting facts and figures and often results in numerical, structured data. Things that are hard to quantify with numbers or measure with figures. You can also make observations from photographs or from watching people – things like the way people are looking at each other lovingly, or how two old people might hold hands while they watch TV.įrom these observations, you can theorize that those people love each other, are close to each other, know each other well and are comfortable around each other, and so on. They’re not just responding “yes” or “no” – they’re telling you what they think. When you engage with people in these ways, you’re giving the opportunity to give more in-depth, elaborate responses. Doing interviews, setting up focus groups, giving people open-ended questionnaires, studying photo collections, and observing people in their daily routines are all forms of qualitative data collection. You can conduct qualitative research in a few different ways. This gives you insights into their behavior, beliefs, opinions, and so on. When you’re researching a group, you want to study them in their natural environment. Qualitative research focuses on the human perspective, and usually answers the question “why?” If you want to learn how people perceive their environment, why they hold certain beliefs, or how they understand their problems, you’ll conduct qualitative research. Now let’s get more into the details of qualitative and quantitative research so you know how to conduct each. Alright that one’s a bit more of a stretch, but it works. On the other hand, qualitative data gives you more insight into what people think, feel, and believe – the quality of a thing, person, or situation. That’s all about quantity (sounds like quantitative, right?). Well, here’s a quick and easy way to remember at least the basic difference: quantitative data deals with quantities of things – numbers and measurable information, like how many people visit a website each day. So what’s the difference between these two data types? The combination of a deep knowledge in economics and a solid command in data science offered by the Master leads to a large spectrum of job market outcomes, as economic researcher, applied economist or data analyst in various public, academic or private sectors.When you’re conducting research, your data will fall into two categories: qualitative or quantitative. The Master 2 Quantitative Economic Analysis, more oriented toward research in economics, allows you to deepen your understanding of economic issues still with a quantitative approach. You will then specialize in a specific field through one of the two Master 2 tracks: The Master 2 Digital Economics, oriented to professional outcomes, deepens your knowledge in Data Science techniques in link with business decisions. During your Master first year, you will learn about both the fundamentals of economics and data science, through intensive computer programming courses. At the end of your master degree, you will have gained an excellent command of quantitative methods used in economics, including innovative techniques for Big Data processing, allied with a deep understanding of the economic decision-making process. The Master in Quantitative Economics offers solid training in economics and quantitative methods, entirely taught in English.
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