Week 1- Introduction and Descriptive Statistics

Question 1

Name three types of Central Tendency (averages)?

Answer 1

Mean
Median
Mode

Question 2

Name two ways to measure the spread of a data set

Answer 2

Standard Deviation
Range

Question 3

What are categorical variables? Give an example

Answer 3

Represents data that may be divided into groups

Age, Gender

Question 4

Which type of central tendency can you use for categorical variables? Give an example

Answer 4

The mode

For example, if you have the following eye colours: {brown, brown, blue, green, blue, brown}, the modal class is brown. You can’t (obviously) use mean or median here.

Question 5

How would you compare wage inequality between two countries (using descriptive statistics, for now)?

Answer 5

You can check the standard deviation

If two countries have the same average salary (more or less), but one has a sd of 15k, and the other of 50k, the latter has higher wage inequality.

Question 6

Name three stages of data analytics

Answer 6

1- Descriptive analytics
2- Predictive analytics
3- Prescriptive analytics

Question 7

What is descriptive analytics?

Answer 7

Basically inferential (generalisation) statistics. Analysing historical data

Question 8

What is predictive analytics?

Answer 8

Building mathematical, computational, and statistical models to make predictions using existing data

Question 9

What is prescriptive analytics?

Answer 9

Building data-driven solutions to control, or change the outcome of an event

Question 10

What are the 4 types of sampling techniques?

Answer 10

1- Simple Random
2- Stratified
3- Clustered
4- Systematic

Question 11

What is a simple random sample?

Answer 11

A random sample from the population

Question 12

What is a stratified sample?

Answer 12

Allows for control of group sizes by sampling based on said groups (e.g., sex, profession, etc.).

Question 13

What is a clustered sample?

Answer 13

Usually based on geography and proximity.

Question 14

What is a systematic sample?

Answer 14

Taking every kth member.

E.g, To find k, divide 836 by 20 to get 41.8.

Rounding gives k = 42.

Randomly select a number from 1 to 42, say 18.

Start at the person numbered 18 and then choose every 42nd member of the list.

Question 15

What is the drawback of Simple random sampling?

Answer 15

Risks overrepresentation of certain groups, unequal group sizes.

Question 16

What is the drawback of stratified sampling?

Answer 16

May lead to biased representation of otherwise smaller groups by overrepresenting their importance.

Question 17

What is an example of clustered sampling?

Answer 17

Sampling from a local hospital, rather than all hospitals.

Question 18

What is the difference between a parameter and a statistic?

Answer 18

Parameters are summaries of population data.

Statistics are summaries of sample data. In many places there are used interchangeably (e.g., in data science).

Question 19

Name two types of qualitative data and describe them

Answer 19

Categorical- No particular order to them. E.g., countries, eye colours, sex, etc.

Ordinal- An order has been applied. E.g., countries by population size, products by amount sold, etc.

Question 20

Name two types of quantitative data and describe them

Answer 20

Discrete- Whole numbers (integers). E.g., number of emails sent.

Continuous- Real numbers, such as temperature, weight, height, etc.