[LBOLYTC] Unit 1: Introduction to Data Analytics

Data Analytics

An emerging scientific process that allows us to go deep into our data in search of much-needed & fact-based insights.

Data Analytics

The science that deals w/ the collection, organization, analysis, interpretation, & presentation of data to assist in making more effective decisions

Data Analytics

The process of examining datasets to draw conclusions about the information they contain

Data Analytics

exists at the intersection of information technology, statistics & business

4 Characteristics of Data Analytics

Descriptive
Diagnostic
Predictive
Prescriptive

Descriptive

What is the data telling you?

Descriptive Statistics

Consists of methods concerned with collection, organization, summarization and presentation of a set of data

Diagnostic

Why is it happening?

Predictive

What’s likely to happen?

Inferential Statistics

comprised of those methods concerned with making predictions or inferences about an entire population based on information provided by the sample

Prescriptive

What do I need to do?

Data

Facts & figures from w/c conclusions can be drawn

Data Analytics

Its process starts by COLLECTING DATA THAT WE NEED.

Data Set

A set of facts & figures being collected for a statistical study

Data Set

Provides information about some group of individual elements

Element

A person, object, situation or any other entity about w/c we wish to draw a conclusion

Variable

A characteristic of a population or sample element

Variable

Used to describe an element

Variable

any characteristic or information measurable or observable on every element of the population or sample

Population

consists of the totality of all the elements or entities from which you want to obtain an information

Sample

subset of the population

Measurement

Carried out to assign a value of the variable to the element

Cross-Sectional Data

Data collected at the same or approximately the same point in time

Cross-Sectional Data

Data that we measure at ONLY ONE POINT IN TIME

Time Series Data

Data collected over different time periods

Time Series Data

Data that we measure OVER A SERIES OR SUCCESSIVE PERIODS OF TIME

2 Types of Variables

Quantitative
Qualitative

Quantitative Variable

A variable having values that are numbers representing quantities

Quantitative Variable

Possible measurements of the values of a variable are numbers representing quantities

Quantitative Variable

variables that indicate how much a given characteristic an individual, object, or event possesses

Qualitative Variable

A variable having values that indicate into w/c of several categories a population element belongs

Qualitative Variable

Measurements fall into several categories

Qualitative Variable

variables that indicate what kind of a given characteristic an individual, object, or event possesses.

2 Types of Qualitative Variables

Nominal
Ordinal

Nominal

A qualitative variable for w/c there is no meaningful ordering or ranking of the categories

Nominal

Variables whose values are simply labels or names or categories without any explicit or implicit ordering of the labels

Nominal

Lowest level of measurement known as categorical scale

Ordinal

A qualitative variable for w/c there is meaningful ordering or ranking of the categories

Ordinal

Measurements may be numerical or non-numerical

Ordinal

Variables whose values are simply labels or names or categories with an implied ordering in these labels

Ordinal

Ranking can be done on the data

Ordinal

Distance between two labels can not be determined

2 Types of Quantitative Variables

Ratio
Interval

Ratio

A quantitative variable measured on a scale such that ratios of its values are meaningful and there is an inherently defined zero value

Ratio

makes up most quantitative variables

Ratio

Variables whose values have all the properties of the interval scale and the ratio of two values is meaningful

Ratio

Has a true zero point

Ratio

Highest level of measurement

Interval

A quantitative variable measured on a scale such that ratios of its values are NOT meaningful and there is NOT an inherently defined zero value

Interval

Variables whose values can be ordered and distance between any two labels are of known size

Interval

Always numeric and have no true zero point

Existing Source

Data already gathered by public or private sources

Experimental and Observational Studies

Data we collect ourselves for a specific purpose

Experimental Study

A statistical study in w/c the researcher is able to set or manipulate the values of the factors

Response Variable

A variable of interest that we aim to study

Factors

Other variables that may be related to the response variable of interest that are also measured

Observational Study

A statistical study in w/c the researcher is not able to control the values of the factors

Survey

an instrument employed to collect data

Census

the process of collecting information from the population

Survey

the process of collecting information from the sample

Survey

questions asked relate to people’s behaviors, opinions, beliefs & other characteristics

Paramater

a summary or numerical measure used to describe a population

Statistic

a summary or numerical measure used to describe a sample

Constant

a characteristic or property of a population or sample which makes the members similar to each other

Discrete Variables

variables whose values are obtained through the process of counting

Continuous Variables

variables whose values are obtained through the process of measuring

Dependent Variable

a variable which is affected by another variable

Independent

a variable which affects the dependent variable