Introduction
STATISTICAL ANALYSIS WITH SOFTWARE
APPLICATIONS
1st Semester 2021-2022
RENE N. ARGENAL, MS
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Instructor
RENE N. ARGENAL
■ Office: Math Department
■ Phone: 2300100 local 553, 149
■ Email: ren_argenal@yahoo.com
Office hours: MW 2:30- 4:30 pm.
09322177798
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(Other times by appointment)`
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Introduction
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What we learn in this course:
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Obtaining, presenting, and organizing statistical
data
measures of location, dispersion, & skewness
the Normal distribution
sampling and sampling distributions
estimation and confidence intervals
hypothesis testing
interference for simple linear regression analysis
use of computers to visualize and analyze data.
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Introduction
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Statistics is the science of data. It is concerned
with the scientific method for collecting,
organizing, summarizing, presenting, &
analyzing data as well as drawing valid
conclusions and making reasonable decisions on
the basis of such analysis.
Why need statistics?
- Many jobs in industry, government, medicine,
and other fields require you to make data-driven
decisions, so understanding these methods
offers you important practical benefits.
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Introduction
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Who Uses Statistics?
Statistical techniques are used extensively by
marketing, accounting, quality control,
consumers, professional sports people,
hospital administrators, educators, politicians,
physicians, etc...
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Introduction
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The collection and study of data are important
in the work of many professions, so that
training in the science of statistics is valuable
preparation for variety of careers. , for
example economists and financial advisors,
businessmen, engineers, farmers
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Introduction
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Statistics means “numerical descriptions” to
most people.
Examples:
-Proportion of male students in this classroom
-monthly unemployment figures.
-the failure rate of a business.
-the proportion of female executives.
-the number of van sales.
-monthly orange juice prices.
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Introduction
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An example:
I want to produce pens to sell.
How much should I produce?
* If too much, I can not sell all.
* If too little, I can not earn profit.
Try different quantities at each week.
After one month, compare profits.
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Introduction
Week
Quantity
Gain
Cost
Profit
1
12
$36
-$26
$10
2
14
$44
-$28
$16
3
24
$48
-$36
$12
4
36
$52
-$44
$8
….
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Introduction
Two Branches of Statistics
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Introduction
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DESCRIPTIVE - DEFINITION
Methods of organizing, summarizing, and
presenting data in an informative way.
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EXAMPLE: According to Consumer Reports,
Whirlpool washing machine owners reported 9
problems per 100 machines during 1999. The
statistic 9 describes the number of problems out of
every 100 machines.
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Introduction
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Inferential Statistics
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A decision, estimate, prediction, or generalization about a
population, based on a sample .
A population
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A collection of possible individuals, objects, or
measurements of interest.
A sample
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A portion, or part, of the population of interest.
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Introduction
Inferential Statistics
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EXAMPLE :
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The accounting department of a large firm
will select a sample of the invoices to
check for accuracy for all the invoices of
the company.
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Introduction
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Common Terms:
Data –are numbers or measurement collected as a result of observations.
~ e.g. age, weight, income, gender, grade, race, degree…
* Population
* Sample
* Parameter – any characteristic of a population which is measurable
* Statistics – any characteristics of a sample which is measurable
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Introduction
Variable – any phenomenon which may
take on different values.
* Categorical variable-- put an individual into
one of several groups or categories
~ e.g. gender, grade, race, degree…
* Quantitative variable– use numerical values
for each variable values such that addition
and averaging make sense
~ e.g. salary, height, weight, age, price….
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An Example
Example: Information about employees of CyberStat
Corporation. Each row of data is called a case.
(Similar to Page 5 in the text)
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Example cont.
- What are the
A: Mike, Maggie, Lily,
Individuals?
Jason.
- How many variables? A: 6: age, gender,
race, ….
A: Gender, race, Job
- Which variable is
type, and degree.
categorical variable?
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Example Cont’d
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Which variable is
quantitative?
A: Age, salary
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