Key Concepts in Data Analysis and Statistics

Data

the facts and figures collected, analyzed, and summarized for presentation and interpretation.

Data set

all the data collected in a particular study.

Elements

the entities on which data are collected.

Variable

a characteristic of interest for the elements.

Observation

the set of measurements obtained for a particular element.

Nominal scale

A scale that uses labels/names as identification, no order/ranking.

Ordinal scale

his type of data lets you name categories and put them in order, like ranking

Interval scale

A scale with ordered numbers and equal spacing, but no true zero. (Temperature in Celsius — 0°C doesn’t mean “no temperature,” just a point on the scale)

Ratio scale

A scale with ordered numbers, equal spacing, and a true zero — so you can say things like “twice as much”. (Weight — 0 kg means no weight, and 10 kg is twice as heavy as 5 kg)

Categorical data

labels or names used to identify an attribute of each element. (Categorical data use either the nominal or ordinal scale of measurement and may be nonnumeric or numeric.)

Categorical variable

a variable with categorical data.

Quantitative data

numerical values that indicate how much or how many of something. (obtained using either the interval or ratio scale of measurement.)

Quantitative variable

a variable with quantitative data.

Cross-sectional data

data collected at the same or approximately the same point in time.

Time series data

data collected over several time periods.

Descriptive statistics

tabular, graphical, and numerical summaries of data.

Population

the set of all elements of interest in a particular study.

Sample

a subset of the population.

Census

a survey to collect data on the entire population.

Sample survey

a survey to collect data on a sample.

Statistical inference

the process of using data obtained from a sample to make estimates or test hypotheses about the characteristics of a population.

Analytics

the scientific process of transforming data into insight for making better decisions.

Descriptive analytics

the set of analytical techniques that describe what has happened in the past.

Predictive analytics

the set of analytical techniques that use models constructed from past data to predict the future or assess the impact of one variable or another.

Prescriptive analytics

the set of analytical techniques that yield a best course of action.

Big data

a set of data that cannot be managed, processed, or analyzed with commonly available software in a reasonable amount of time. Characterized by great volume, high velocity, or wide variety.

Data mining

the process of using procedures from statistics and computer science to extract useful information from extremely large databases.