Classification of Data: Types of Data

00:01 You are probably watching this course because you want to learn the appropriate statistics to perform different tests.

00:07 Maybe you want to use this knowledge as a stepping stone to a career in data science.

00:12 Either way, before we can start testing, we have to get acquainted with the types of variables we usually encounter.

00:19 Different types of variables require different types of statistical and visualization approaches.

00:24 Therefore, to be able to classify the data you are working with is key.

00:29 We can classify data in two main ways, based on its type and on its measurement level.

00:35 Let's start from the types of data we can have.

00:37 There is categorical and numerical data.

00:41 Categorical data describes categories or groups.

00:44 One example is car brands like Mercedes, BMW and Audi.

00:49 They show different categories.

00:51 Another instance is answers to yes and no questions.

00:55 If I ask questions like, Are you currently enrolled in a university or Do you own a car? Yes and no would be the two groups of answers that can be obtained.

01:06 This is categorical data.

01:09 Numerical data, on the other hand, as its name suggests, represents numbers.

01:15 It is further divided into two subsets, discrete and continuous.

01:20 Discrete data can usually be counted in a finite matter.

01:24 A good example would be the number of children that you want to have.

01:27 Even if you don't know exactly how many, you are absolutely sure that the value will be an integer such as zero one, two or even ten.

01:37 Another instance is grades on the SAT exam.

01:40 You may get 1000 1560, 1570 or 2400.

01:47 What is important for a variable to be defined as discrete is that you can imagine each member of the data set knowing that SAT scores range from 600 to 2410 points separate.

01:58 All possible scores that can be obtained is key.

02:02 It's easier to understand discrete data by saying it's the opposite of continuous data.

02:07 Continuous data is infinite and impossible to count.

02:11 For instance, your weight can take on every value in some range.

02:15 Let's dig a bit deeper into this.

02:18 You get on the scale and the screen shows £150 or 68.0389 kilograms.

02:25 But this is just an approximation.

02:28 If you gain £0.01, the figure on the scale is unlikely to change. But your new weight will be £150.01 or 68.0434 kilograms.

02:41 Now think about sweating.

02:44 Every drop of sweat reduces your weight by the weight of that drop.

02:47 But once again, a scale is unlikely to capture that change.

02:51 Your exact weight is a continuous variable.

02:54 It can take on an infinite amount of values, no matter how many digits there are after the dot. To sum up, your weight can vary by incomprehensibly small amounts and is continuous, while the number of children you want to have is directly understandable and is discrete.

03:11 Just to make sure.

03:13 Here are some other examples of discrete and continuous data.

03:17 Grades at university are discrete.

03:19 A. B. C.

03:20 D. E. F or 0 to 100%.

03:25 The number of objects in general, no matter if bottles, glasses, tables or cars, they can only take integer values.

03:34 Money can be considered both.

03:35 But physical money, like banknotes and coins, are definitely discrete.

03:40 You can pay $1 and two for $0.03.

03:43 You can only pay a dollar in $0.24.

03:45 That's because the difference between two sums of money can be $0.01 at most.

03:51 What else is continuous? Apart from weight.

03:54 Other measurements are also continuous.

03:57 Examples are height, area, distance and time.

04:03 All of these can vary by infinitely smaller amounts, incomprehensible for a human.

04:08 Time on a clock is discrete, but time in general isn't.

04:12 It can be anything like 72.123, four, five, 6 seconds.

04:17 We are constrained in measuring weight, height, area, distance and time by our technology, but in general, they can take on any value. All right.

04:28 These were the types of data.

04:30 In our next lesson, we will explore the levels of measurement.