Lecture 1: Introduction to Business Statisticscontents.kocw.net/KOCW/document/2013/kyunghee/jungsunho/01.pdf · Business Statistics Lecture 1: Introduction to Business Statistics

Business Statistics

Lecture 1: Introduction to Business Statistics

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Agenda

Introduction to statistics (Ch.1)

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Introduction to statistics – Intro Ch.1

What is statistics?

aim: making statements about real world phenomena

“statistics is a way to get information from data”

collecting, analyzing and interpreting data…

…in order to get insight into phenomena…

…to assist in decision making processes

Intuition check: Purchase history

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Flat screen TV sales of the UK

Some Basic Concepts

Population: The entire set of things of interest. Parameter: A property descriptive of the

population Population mean

Sample: The part of the population. Typically this provides the data we will look at. Estimate: A property of a sample

Sample mean

Some Basic Concepts

Descriptive Statistics: Summarize/describe the properties of samples (or

populations when they are completely known)

Inferential Statistics: Draw conclusions/make inferences about the

properties of populations from sample data

Descriptive vs. Inferential Statistics

Population sample Mean( ) = 105

descriptive

X

Descriptive vs. Inferential Statistics

Population

sample

Mean(μ) =

Mean( ) = 105

inferential

descriptive

X

? 100

Some Basic Concepts

Variable:

Something that varies

A condition or characteristic that can have different values

Constant

Some Basic Concepts

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Values of the variable are the range of possible values for a variable.

E.g. student marks (0..100)

Data are the observed values of a variable.

E.g. student marks: {67, 74, 71, 83, 93, 55, 48}

Types of Variables

Nominal

Ordinal

Interval

Ratio

Qualitative (Categorical)

Quantitative (Numerical)

Types of Variables

Dependent variables (Y): Outcomes/Responses

Predicted variables

Independent variables (X): Aka factors in experimental designs

Aka predictors/covariates

Group 1 (treatment)

Group 2 (control)

Ad

No Ad

Y = Consumer preference (1-10) X = Ad (0 = no, 1 = yes)

population sample

Random sampling

Random assignment

We want to test the effect of a particular ad on consumers’ preference ratings.