ST 260 PP 1

Measurement

Assignment of a value to a characteristic of an object or event.

Data

measurements that are collected, recorded, and summarized for presentation, analysis, and interpretation.

Element

an entity or object on which data are collected. Also called a case or an individual.

Variable

characteristic of the elements whose value may differ from element to element and is of interest to the data collector.

Observation

measurement of a variable or variables on a single element.

Qualitative data

labels or names for a characteristic.

Quantitative data

measurement of amount or quantity.

Nominal level

data that can only categorized

Ordinal level

data can be categorized and ranked

Interval level

values convey how much more or less one value is from another

Ratio level

values can take on a ‘natural’ or ‘absolute’ zero

Cross-sectional data

values are collected from many entities during a given period of time.

Time series data

values are collected from a single entity over several (usually successive) time periods.

Cross-sectional data example

how tall is each student in the class?

Time series data

how tall was a single student on each of his/her birthdays?

Survey/observation

Selection of a proportion of the population and measurement or observation of the values of the variables in question for the selected elements

Experiementation

Manipulation of the values (or levels) of one or more (independent) variables or treatments and observation of the corresponding change in the values of one or more (dependent) variables or responses

Primary data

Data collected by the user to to answer a specific question. Example: survey collection (observation) Experimentation

Secondary data

Data used to answer a question other than that for which they were originally intended. Example: Newspapers, Magazines, Books, Government Publications, online databases

Statistics

art and science of collecting, describing, analyzing, interpreting, and presenting data

Population

Collection of all possible elements of interest.

Census

Collection of the values for all variables of interest that correspond to all elements of a population. The size of the census (number of elements in the population) is usually denoted N. Note that when a census is collected, we can say that the data tell/say something to us.

Parameter

A summary measure used to describe values of a variable for the entire population.

Sample

a collection of elements that comprise a subset of the population.

The size of a sample is

usually denoted with n

Statistic

an estimate of the value of a parameter based on the elements that belong to the sample. Can be descriptive or inferential.

Descriptive statistics

tabular, graphical, and numerical methods used to summarize one or more characteristics of a population or a sample.

Inferential statistics

use of data obtained through sampling to estimate the value of or test a hypothesis about a parameter (i.e., use of inductive logic).

Probability

science of numerically measuring the likelihood that a given event will occur

Why sample?

Expense - Speed - Destructive Nature of Data Collection - Accuracy - Inaccessibility of Some Elements - Invasiveness of some Sampling (blood, human tissue)

Applications of statistics to business disciplines

Operations/production, finance, management, economics, marketing, accounting, IS

Statistical software

SAS - SPSS - Systat - SHAZAM - Stata - Statgraphics

Programming Languages with Statistical Capabilities

S-Plus - R - Python