Lecture 2

Question 1

what role do statistics play in business?

Answer 1

statistics play an important role in virtually all aspects of business (e.g., strategy, marketing, operations, supply chain)

Question 2

Do statistics aid in managing financial risks?

Answer 2

Yes

Aids in managing financial risks, detecting fraudulent transactions & preventing equipment breakdowns

Question 3

Common applications of statistics include…?

Answer 3

Predictive modelling
Pattern recognition (trends)
Anomaly detection
Classification
Sentiment analysis

Question 4

Sentiment = ?

Answer 4

A view or opinion that is held or expressed

Question 5

What are examples of business use cases for statistics?

Answer 5

Customer analytics
Targeted advertising
Website personalisation
Risk management
Investment optimisation
Fraud detection

Question 6

Examples of data sources for statistics?

Answer 6

Bloomberg
Google dataset search

Question 7

Examples of statistical software?

Answer 7

Jamovi, stata

Question 8

Examples of challenges in statistics?

Answer 8

Varied & massive amount of data increases complexity

Datasets may include structured, unstructured & semi structured data

Eliminating bias in datasets

Question 9

What impact do biases have on results?

Answer 9

They skew results if they’re not identified and addressed, creating flawed findings

They can also have a harmful impact on groups of people

Question 10

Why is “numbers don’t lie” invalid?

Answer 10

Even when figures are accurate, organisations can apply their own agendas to mislead

May not tell the whole story

Question 11

What does data help us do?

Answer 11

It provides us insights into the world around us

Question 12

Examples of unethical use of statistics?

Answer 12

Biased sampling

Only showing data that supports your views

Using too much jargon to confuse audience

Using the wrong method of analysis

Question 13

What is the statistical enquiry circle?

Answer 13

Problem, plan, data, analysis, conclusion

Define the problem,
Study and establish the variables
Collect & treat dataset
Explore the data & analyse
Solve the issue & provide answers

Question 14

Is data collected for specific purposes?

Answer 14

Yes

Question 15

What are the two types of data?

Answer 15

Primary data (data collected directly from the data source)

Secondary data (data previously collected by someone else)

Question 16

What are the other two types of data?

Answer 16

Qualitative & quantitative

Question 17

Is data the same as information?

Answer 17

No

Question 18

What are the differences between data and information?

Answer 18

Data provides raw facts/figures, information provides context

Data is meaningless until it’s organised, information is the processed and meaningful form of data

Understanding data is more difficult than understanding information

Input = data, output = information

Question 19

Qualitative data = ?

Answer 19

Names or labels used to identify an attribute of each element

Question 20

Quantitative data = ?

Answer 20

Represents measurements or counts

Always numeric

Question 21

What do the levels of measurement determine?

Answer 21

Level of measurement indicates the data summarisation and statistical analyses that are most appropriate

Question 22

What are the four levels of measurement?

Answer 22

Nominal
Ordinal
Interval
Ratio

Question 23

Nominal data = ?

Answer 23

Labels, names used for identification etc

Question 24

Ordinal data = ?

Answer 24

Exhibits properties of nominal data and may be rank-ordered

Question 25

Interval data = ?

Answer 25

Has properties of ordinal data but also shows uniform distances between successive values

Question 26

Ratio data = ?

Answer 26

All properties of interval data and the ratio of two values is meaningful

Question 27

The higher the level of measurement…

Answer 27

The more precise the data is

Question 28

Does precision guarantee accuracy?

Answer 28

No

Question 29

Big data = ?

Answer 29

A great quantity of diverse information that arrives in increasing volumes

Question 30

What are the 3 V’s of big data?

Answer 30

Volume of info
Velocity at which data is created
Variety of data available

Question 31

Statistics involves…

Answer 31

Collection
Description
Analysis
Inference

Based on data

Question 32

Descriptive statistics = ?
Inferential statistics = ?

Answer 32

Descriptive = summarises characteristics (e.g., mean, median, mode)

Inferential = relates variables in a dataset (e.g., correlation)

Question 33

Does statistics = mathematics?

Answer 33

No