Lecture 2 Flashcards
what role do statistics play in business?
statistics play an important role in virtually all aspects of business (e.g., strategy, marketing, operations, supply chain)
Do statistics aid in managing financial risks?
Yes
Aids in managing financial risks, detecting fraudulent transactions & preventing equipment breakdowns
Common applications of statistics include…?
Predictive modelling
Pattern recognition (trends)
Anomaly detection
Classification
Sentiment analysis
Sentiment = ?
A view or opinion that is held or expressed
What are examples of business use cases for statistics?
Customer analytics
Targeted advertising
Website personalisation
Risk management
Investment optimisation
Fraud detection
Examples of data sources for statistics?
Bloomberg
Google dataset search
Examples of statistical software?
Jamovi, stata
Examples of challenges in statistics?
Varied & massive amount of data increases complexity
Datasets may include structured, unstructured & semi structured data
Eliminating bias in datasets
What impact do biases have on results?
They skew results if they’re not identified and addressed, creating flawed findings
They can also have a harmful impact on groups of people
Why is “numbers don’t lie” invalid?
Even when figures are accurate, organisations can apply their own agendas to mislead
May not tell the whole story
What does data help us do?
It provides us insights into the world around us
Examples of unethical use of statistics?
Biased sampling
Only showing data that supports your views
Using too much jargon to confuse audience
Using the wrong method of analysis
What is the statistical enquiry circle?
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
Is data collected for specific purposes?
Yes
What are the two types of data?
Primary data (data collected directly from the data source)
Secondary data (data previously collected by someone else)
What are the other two types of data?
Qualitative & quantitative
Is data the same as information?
No
What are the differences between data and information?
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
Qualitative data = ?
Names or labels used to identify an attribute of each element
Quantitative data = ?
Represents measurements or counts
Always numeric
What do the levels of measurement determine?
Level of measurement indicates the data summarisation and statistical analyses that are most appropriate
What are the four levels of measurement?
Nominal
Ordinal
Interval
Ratio
Nominal data = ?
Labels, names used for identification etc
Ordinal data = ?
Exhibits properties of nominal data and may be rank-ordered
Interval data = ?
Has properties of ordinal data but also shows uniform distances between successive values
Ratio data = ?
All properties of interval data and the ratio of two values is meaningful
The higher the level of measurement…
The more precise the data is
Does precision guarantee accuracy?
No
Big data = ?
A great quantity of diverse information that arrives in increasing volumes
What are the 3 V’s of big data?
Volume of info
Velocity at which data is created
Variety of data available
Statistics involves…
Collection
Description
Analysis
Inference
Based on data
Descriptive statistics = ?
Inferential statistics = ?
Descriptive = summarises characteristics (e.g., mean, median, mode)
Inferential = relates variables in a dataset (e.g., correlation)
Does statistics = mathematics?
No
