Skip to 0 minutes and 1 secondNow, there's the idea of a bit of terminology here that we need to know variables and data. Now, you may know what these mean but let's just define them formally first. a variable measures some characteristic and it could be about the population which is all the data, say all of your customers out there or it could be a characteristic just out of a small sample of your customers
Skip to 0 minutes and 28 secondsNow that contrasts from data which is the actual or observed values of a variable but let's give an example. A variable might be capital expenditure how much you're spending on your capital projects capital improvement projects as well as indeed maintenance, capital maintenance as well. And data for Firm A, it might be 1.4 billion yen that's the actual value. For Firm B it might be a hundred million yen. So, the variable is the capital expenditure that measures some characteristics but the data is the actual value, observed value and here, you know, it's very different for two different companies
Skip to 1 minute and 13 secondsSo variables then, what kind of types of variables do we have? Well, we're gonna break them down into broad categories, and there's lots of different ways you can do this but we're gonna keep it quite simple. Just break it down into some broad categories and say we have qualitative data and we have quantitative data. within quantitative we're gonna talk about discrete and continuous. But I will leave that for topic two. so we'll deal with that a bit later
Skip to 1 minute and 46 secondsBut, qualitative vs quantitative is an important distinction to make because there's different things, different techniques that we can apply depending on whether its qualitative or quantitative. Now these are quite easy to remember qualitative variables measure a quality or a characteristic not numbers, not numeric so, other words might be categorical or nominal data if you've heard these before but things like hair colour, so brown blonde, black red, okay? So, notice it's not a number, its a quality non-numeric there. maybe it's the make of a car? it could be Toyota, it could be Mazda Suzuki, Holden, Honda, Ford you know, different makes of cars again it's a quality, not a number.
Skip to 2 minutes and 40 secondsGender is another popular one, ah, was it a male customer was it a female customer
Skip to 2 minutes and 47 secondsSatisfaction, good okay? Happy satisfied, not satisfied these are all qualities so they're qualitative variables. The difference or the contrast here is quantitative variables, which measure a numeric quanitity so we can add them we can average them we can do different mathematical calculations that we couldn't do with qualitative variables but that's the main distinction qualitative variables measure a quality a characteristic quantitative variables measure a numeric quantity
Skip to 3 minutes and 31 secondsSo what is this course about? About starting with data we're going to perform some analysis that you're going to learn that green box so we produce new information that can be used to inform better decision making and thereby improve the business decisions So I'll see you for our next topic soon which is graphical, descriptive techniques or just graphs visual representations of information and we're going to look at both qualitative variables and quantitative variables.
Skip to 4 minutes and 11 seconds*music playing alongside Bond University logo*
Terminology for the Course
In this video, Adrian quickly sets out some terminology for data analysis. Make sure you are comfortable with the terms introduced, as they are used throughout the rest of the course. We use this terminology to help us be clear in how we describe data and problems.
Do you feel comfortable with the difference between variables and data? How about qualitative vs quantitative variables?
We now have the foundations needed to jump into the main content of the course. In the next activity we will learn about graphical techniques for describing data. We hope to see you there!
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