Data Analytics for Decision Making PDF

Topic 1: What Is Statistics? Dr. Ahmed Bakri, Dr. Krisztina Soreg & Mr. Antonio Moya o o o o o #1 Data-driven global economy #2 Data is one of the most valuable assets a business can have #3 Data analysis is the future which will demand skills for jobs as functioal analysts, data engineers, data sci...

Topic 1: What Is Statistics? Dr. Ahmed Bakri, Dr. Krisztina Soreg & Mr. Antonio Moya o o o o o #1 Data-driven global economy #2 Data is one of the most valuable assets a business can have #3 Data analysis is the future which will demand skills for jobs as functioal analysts, data engineers, data scientists and advanced analysts #Data empowers us to take rational strategic decisions → A whole number that can’t be divided or broken into individual parts, fractions or decimals Countable in a finite amount of time Best visual tool: bar & pie charts E.g.: number of students, population of a country, number of employees in a firm, days of the months (limited) Discrete data Values that can be broken down into different parts, units, fractions and decimals Measurable: continuous data points → not countable! Best visual tool: histogram E.g.: height, weight, time, temperature, width, speed of cars, distance, length of a film Continuous data Metrics (scales) A unit of measurement that provides a way to objectively quantify performance E.g.: senior managers might assess overall business performance using such metrics as net profit, return on investment, market share, and customer satisfaction Ratio data Nominal data Ordinal data Interval data 1) Nominal (categorical) data A variable determined by categories. The variables are given a descriptive name or label to represent their value. The categories bear no quantitative relationship to one another → calculation is not possible: can’t be multiplied, divided, added or subtracted, no difference between data points! E.g.: geographical location of clients, hair colour, gender, postal code, political party, religion, etc. 2) Ordinal data Data can be compared to one another → order matters but not the difference between values, can’t be added to or subtracted from! No fixed units of measurement: extent or limit of something E.g.: rating a service as poor, average, good, very good or excellent, income level, education level, satisfaction rating, etc. 3) Interval data Constant differences between observations and have arbitrary zero points (we can go below 0) → no starting point or true zero (negative numbers are possible) → can be added and subtracted only Values measured along a scale (computable), with each point placed at an equal distance from one another: order + difference E.g.: temperature (Farenheit), temperature (Celcius), pH, credit score 4) Ratio data Continuous data having a natural (true) zero (an object is twice as big or as long as another) → category, order, difference It can be added, subtracted, divided and multiplied True zero: the data has no value point (you can’t have 0 kilos) There can be no negative variable: we cannot go below 0! E.g.: Kelvin scale (temperature), height, speed, dollars, profit