Lecture 01 - ST361 Introduction

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Statistics 361

Statistics for Engineers

Introduction

Kimberly Weems

[email protected]

5260 SAS Hall


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Stat 361

Intro to Stats for EngineersPrerequisites: College Algebra

Topics include descriptive statistics, sampling,

experimental design, estimation, testing, regression


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Syllabus Issues

Contact info on top of page

Required Text:Applied Statistics for Engineers

and Scientists, 2nd ed. Author: Jay Devore and

Nicholas Farnum. Publisher: Thomson

Brooks/Cole. ISBN: 0-534-46719-9, year 2005.

Calculator needed: TI83/84 is often used


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Grades

Grades:ITEM Percentage

Exam 1 20%

Exam 2 20%

Exam 3 20%

Homework 15%Final Exam 25%

Up to plus/minus, you need 90% for A, 80% for B,70% for C, 60% for D. Less than 60% is F. IN grades

are given only as specified in University regulations.


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Homework

Assigned weekly Due at beginning of class. Late HW accepted

with penalty

May work together, but do not copy. The lowest HW will be dropped.


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Exams

3 exams (closed notes, closed book). Seesyllabus for exam dates.

No web-enabled devices may be used.

One 8 x 11 page of notes is allowed. Statistical tables will be provided.

Exams are not cumulative


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Missed Exams

Make-up exams are strongly discouraged. If you are aware of a conflict, inform me

before the exam.

Make-up exam will only be given if Suitable documentation is provided within 2 days

Student takes make-up within 1 week


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Final Exam

Final exam is cumulative. Basic rules for other exams also hold for the

final.

One 8 x 11 page of notes is allowed. See syllabus for University-scheduled final

exam time


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Class Web PageSyllabus, Course Outline

& Lectures

Moodle ( http://moodle.wolfware.ncsu.edu) Check often for updates

Notes/note outlines will be posted at least 24 hours in

advance. Please print and bring them to class with you.

Links for

StatCrunch (http://statcrunch.stat.ncsu.edu/)
http://moodle.wolfware.ncsu.edu/http://statcrunch.stat.ncsu.edu/http://statcrunch.stat.ncsu.edu/http://moodle.wolfware.ncsu.edu/


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Policies

Arrive on time. Bring handouts & calculator.

Turn cell phones off.

Mutual respect creates an ideal learningenvironment for everyone.


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Laptop Policy

May be used for viewing ST 361 materialsonly

There may be times when laptops are not

allowed. Laptop use may be discontinued at any time.


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Important links

Academic Misconduct Disability Services for Students

Class Evaluations

NCSUcheck in case of inclement weather.

Also check your Unity account regularly for

announcements.
http://www.ncsu.edu/policies/student_services/student_conduct/POL445.00.1.htmhttp://www.ncsu.edu/provost/offices/affirm_action/dss/https://classeval.ncsu.edu/http://www.ncsu.edu/http://www.ncsu.edu/https://classeval.ncsu.edu/http://www.ncsu.edu/provost/offices/affirm_action/dss/http://www.ncsu.edu/policies/student_services/student_conduct/POL445.00.1.htm


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A few questions for you

What do you hope to get out of this class? We live in a society that collects volumes upon

volumes of data. Are people looking at the data? Are

they interpreting the data properly?

How do we turn raw data into information?


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What is Statistics?

The discipline of Statistics isthe science of data

the study of variability

Note statistics has also a different meaning.

Statistics = plural of statistic . A statistic is a

numerical fact, or summary. Examples: the size of the

data describing some population; or its birth rate, orits crime rate.


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What is Statistics?

Statistics provides a framework for describing thevariability in a system and for learning the impact of

various factors on a system.

Example: Different tanks of gas yield different mpgs.

Gasoline mileage depends on many factorstype of driving (city vs highway)

weather conditions

tire inflationengine compression

valve wear, the octane of the gasoline used, etc.


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What is Statistics?

Statistics is the study of how best to:(a) collect data;

(b) summarize or describe data; and

(c) draw formal inferences and practical

conclusions based on data

all the while recognizing the reality of variation.


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The Basic Paradigm.

Population Sample

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Inference

Parameters


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Why Study Statistics?

Statistics is everywhere! medicine, economy,agriculture, hydrology, engineering, etc.

It is the most important and portable subjectyou will

learn in your quantitative curriculum.

Surveys of practicing engineers consistently show

that one of their foremost academic regrets was not

learning enough statistics.


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Statistics in Engineering

Engineers solve problems byapplying scientific principles.

For example, engineers

perform tests to learn how

things behave under stress,

and at what point they mightfail.

As engineers perform

experiments, they collect data

that can be used to explain

relationshipsbetter and toreveal information about the

quality of products and

services they provide.


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Statistics in Engineering: Some Examples

1. Design of Experiments (DOE) uses statistical techniques to test and

construct models of engineering components and systems.

2. Quality control and process control use statistics as a tool to manage

conformance to specifications of manufacturing processes and their

products.

3. Time and methods engineering use statistics to study repetitive operations

in manufacturing in order to set standards and find optimum (in some

sense) manufacturing procedures.

4. Reliability engineering uses statistics to measures the ability of a system

to perform for its intended function (and time) and has tools for improving

performance.

5. Probabilistic design uses statistics in the use of probability in product and

system design.

http://en.wikipedia.org/wiki/Engineering_statistics


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Method of statistics follows a process

Preliminary: Identify the research objective Step 1: Collect the information needed to answer the

questions

Step 2: Organize and summarize the information.

Step 3: Draw conclusions from the information.


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Preliminary: Identify the research objective What are

The questions to the answered, and

The populationthe values or individuals of interest


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Step 1: Collect the information needed to answer thequestions

Population may be inaccessible

Too large

Time restrictions

Impractical

Typically consider a sample: a subset of the

population


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Step 2: Organize and summarize the information. Give descriptive statisticsnumerical and

graphical summaries of the data

To collect data, we observe and record values of one

or more variables

Want to determine each variables distributionthe

possible values of the variable and the probability

of each value occurring


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Step 2: Organize and summarize the information.(contd)

Parameterssummaries of the (distribution of the)

population

Statisticssummaries of the (distribution of the)

sample


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Step 3: Draw conclusions from the information. The information collected from the sample is

generalized to the population, and the reliability is

measured i.e. inferential statistics


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The Basic Paradigm.

Population Sample

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Inference

Parameters


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Example: SAT Scores

50 students (24 males and 26 females) matchedaccording to socio-economic background,

Study to examine the effect ofclassroom atmosphere(strict or permissive) on student performance, as

measured by SAT scores at the end of the school year. Students divided into two groups of 25 each (12

males and 13 females)

Group 1 to study under a strict atmosphere

Group 2 studies under a verypermissive atmosphere.


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Example: SAT Scores

After nine months, all students were given thesame tests: SATMath & SATVer.

Student Group Gender SATMath SATVerA Strict F 670 700

B Strict M 700 680

C Permissive F 750 730

D Permissive M 690 750


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Example: SAT Scores

This example involves data collection, dataanalysis,andstatistical inference. How?

Questions:

Does stricter classroom atmosphere increase the

average score?Is the group size 50 large enough to make a

confident conclusion?

Why were the students matched according to

socio-economicbackground?Why 12 males and 13 females pergroup?


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Example: SAT Scores

Population: all individuals in that region that take

the SAT or the SAT scores of all individuals

Sample: the 50 students selected for the study or

the SAT scores of the 50 students

Sample size: 50

Statistical inference: Based on the data from the

study, we infer whether a stricter classroom

atmosphere increases SAT scores in general.

What are examples of a parameter and a statistic?

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Lecture 01 - ST361 Introduction