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What is Statistics ?

1. Collecting Data Data Analysis

e.g., Survey

2. Presenting Data

e.g., Charts & Tables

3. Characterizing Data Making decisione.g., Average

Business Statistics

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Statistical

Methods

Descriptive

Statistics

Inferential

Statistics

Statistical Methods

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Descriptive Statistics

1. Involves

Collecting Data

Presenting Data

Characterizing Data

2. Purpose

Describe Data

X = 30.5 S2 = 113

0

25

50

Q1 Q2 Q3 Q4

$

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Inferential Statistics

1. Involves

Estimation

HypothesisTesting

2. Purpose

Make decisions about

population characteristics

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Types of

Data

QuantitativeData

QualitativeData

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Quantitative Data

Measured on a numeric

scale.

Number of defectiveitems in a lot.

Salaries of CEO's of

oil companies.

Ages of employees at

a company. 3

52

71

4

8

943

120 1221

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Qualitative Data

Classified into categories.

College major of eachstudent in a class.

Gender of each employeeat a company.

Method of payment(cash, check, credit card).

$ Credit

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Type of Data

Four type of data :Nominal

Ordinal

Interval

Rasio

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Data

Categorical Numerical

Discrete Continuous

Examples:

Marital Status Political Party

Eye Color

(Defined categories)

Examples:

Number of Children

Defects per hour

(Counted items)

Examples:

Weight

Voltage

(Measured

characteristics)

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Levels of Measurement and Measurement Scales

Interval Data

Ordinal Data

Nominal Data

Highest Level

(Strongest forms of

measurement)

Higher Levels

Lowest Level

(Weakest form of

measurement)

Categories (noordering or direction)

Ordered Categories

(rankings, order, orscaling)

Differences betweenmeasurements but notrue zero

Ratio DataDifferences betweenmeasurements, truezero exists

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Levels of Measurement and Measurement Scales

Interval Data

Ordinal Data

Nominal Data

Height, Age, Weekly Food

Spending

Service quality rating,

Standard & Poors bond

rating, Student letter grades

Marital status, Type of car

owned

Ratio Data

Temperature in Fahrenheit,Standardized exam score

Categories (no orderingor direction)

Ordered Categories

(rankings, order, orscaling)

Differences betweenmeasurements but notrue zero

Differences betweenmeasurements, truezero exists

EXAMPLES:

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Application Areas

Economics ForecastingDemographics

Sports Individual & TeamPerformance

Engineering Construction

MaterialsBusiness Consumer Preferences

Financial Trends

Business Statistics

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Random SampleEvery sample of size n has an equal chance of selection.

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Key Tems1. Population (Universe)

All items of interest

2. Sample Portion of population

3. Parameter

Summary measure about population

4. Statistic Summary measure about sample

P in Population

& Parameter

S in Sample& Statistic

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Activities of Statistics1. Designing the study:

First step

Plan for data-gathering

Random sample (control bias and error)

2. Exploring the data:

First step (once you have data) Look at, describe, summarize the data

Are you on the right track?

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3. Modelingthe dataA framework of assumptions and equations

Parameters represent important aspects of thedata

Helps with estimation and hypothesis testing

4. Estimating an unknown: Best guess based on data

Wrong - buy by how much?Confidence interval - were 95% sure that

the unknown is between

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5. Hypothesis testing:Data decide between two possibilities

Does it really work? [or is it just randomly

better?] Is financial statement correct? [or is error

material?]

Whiter, brighter wash?

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Probability Inverse of statistics

Statistics: generalizes from data to the world Probability: What if Assuming you know how the

world works, what data are you likely to see? Examples of probability:

Flip coin, stock market, future sales, IRS audit,

Foundation for statistical inference

The

world

You

seeProbability

Statistics

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Statistical View of the World Data are imperfect

We do the best we can -- Statistics helps!

Events are random

Cant be right 100% of the time Use statistical methods

Along with common sense and goodjudgment

Be skeptical! Statistics can be used to support contradictory

conclusions Look at who funded the study?

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Statistical Computer Packages

1. Typical Software SAS

SPSS MINITAB

Excel

2. Need Statistical

Understanding Assumptions

Limitations