Measurement / Scale / Data

Question 1

Nominal scale of measurement -definition

Answer 1

defines the identity property of data. This scale has certain characteristics, but doesn’t have any form of numerical meaning. The data can be placed into categories but can’t be multiplied, divided, added or subtracted from one another. It’s also not possible to measure the difference between data points.

Question 2

Nominal data can be broken down again into three categories:

Answer 2

Nominal with order: Some nominal data can be sub-categorised in order, such as “cold, warm, hot and very hot.”
Nominal without order: Nominal data can also be sub-categorised as nominal without order, such as male and female.
Dichotomous: Dichotomous data is defined by having only two categories or levels, such as “yes’ and ‘no’.

Question 3

Ordinal scale of measurement definition

Answer 3

defines data that is placed in a specific order. While each value is ranked, there’s no information that specifies what differentiates the categories from each other. These values can’t be added to or subtracted from.

Question 4

Example of ordinal data

Answer 4

include satisfaction data points in a survey, where ‘one = happy, two = neutral, and three = unhappy.’ Where someone finished in a race also describes ordinal data. While first place, second place or third place shows what order the runners finished in, it doesn’t specify how far the first-place finisher was in front of the second-place finisher.

Question 5

Interval scale of measurement definition

Answer 5

contains properties of nominal and ordered data, but the difference between data points can be quantified. This type of data shows both the order of the variables and the exact differences between the variables. They can be added to or subtracted from each other, but not multiplied or divided

This scale is also characterised by the fact that the number zero is an existing variable

Question 6

Interval scale measurement ex

Answer 6

Data points on the interval scale have the same difference between them. The difference on the scale between 10 and 20 degrees is the same between 20 and 30 degrees. This scale is used to quantify the difference between variables, whereas the other two scales are used to describe qualitative values only. Other examples of interval scales include the year a car was made or the months of the year.

Question 7

Ratio scale of measurement definition

Answer 7

include properties from all four scales of measurement. The data is nominal and defined by an identity, can be classified in order, contains intervals and can be broken down into exact value.

Question 8

Ratio date example

Answer 8

Weight, height and distance are all examples of ratio variables. Data in the ratio scale can be added, subtracted, divided and multiplied.

Weight, height and distance are all examples of ratio variables. Data in the ratio scale can be added, subtracted, divided and multiplied.

Question 9

Descriptive statistics - what do they do?

Answer 9

help demonstrate, represent, analyse and summarise the findings contained in a sample. They present data in an easy-to-understand and presentable form, such as a table or graph. Without description, the data would be in its raw form with no explanation.

Question 10

What are Inferential statistics ?

Answer 10

used to develop a hypothesis from the data set. It would be impossible to get data from an entire population, so data scientists can use inferential statistics to extrapolate their results. Using these statistics, they can make generalisations and predictions about a wider sample group, even if they haven’t surveyed them all.

Question 11

What can I get mode from?

Answer 11

All of them

Question 12

What can I get median from?

Answer 12

Ordinal, interval and ratio

Question 13

What can I get mean from ?

Answer 13

Ratio and interval

Question 14

What has a rue zero?

Answer 14

Ratio