statistics with computer analysis statistics math 1551 instructor robert barber

Statistics with Computer Statistics with Computer AnalysisAnalysis

Statistics Math 155 1

Instructor Robert Barber

Use of Course InformationUse of Course Information

This course material is intended solely for the use by the instructor and students enrolled in an approved course. This material is only for educational purposes and is not to be packaged and sold. Use of this material by others is not permitted without the express approval of this instructor.

Credit is given to the authors of McClave and Sincich for their text, A First Course in Statistics (Ninth Edition), and Brase and Brase for their text, Understandable Statistics (Eighth Edition), and related materials upon which much of this presentation was based.Statistics Math 155 2

Important Course Important Course InformationInformationAll course information is on the

MyClasses website, which can be reached at myclasses.salisbury.edu

The website includes, syllabus, class policies, tentative class schedule, grades, and homework assignments

The website also includes my office hours and office phone number and e-mail address.


Major Course Major Course RequirementsRequirementsThe statistical software package

Mini-Tab will be used. Buy it for home use or find it on the computers in the school computer labs.

A graphing calculator will be used for in-class tests, quizzes and exercises. The TI-83 or TI-84 is preferred because of extensive text reference. Statistics Math 155 4

Keys to successKeys to success

Commit to excellenceAttend and participate in classSeek help from me during my office

hoursTake advantage of free tutoring

servicesDo your homework. Work other

problemsAsk questions about areas you do not

understand. E-mail me at [email protected]

Read the textbookGet in a study group. Invite me

sometimes.


Course ObjectiveCourse Objective

To introduce the concepts of statistical inference by way of both non-parametric and classical parametric methods.


What is statistics?What is statistics?

Statistics is the science of collecting, classifying, organizing, describing, summarizing, analyzing, and interpreting numerical information for the purpose of making informed inferences about an unknown population(s) and to assist in the decision-making process regarding the population(s) of interest.


Course PlanCourse Plan

Step 1- Give you an understanding of the process of statistical analysis.

Step 2- Relate the chapters in the textbook to the process and provide you with an understanding of why we are discussing each topic area.

Step 3- Begin in chapter one and follow the sequence, i.e., the process, as we navigate through the text.


Why do we do Statistics?Why do we do Statistics?A business wants to know if there

is a market for a new product they developed.

The government wants to know if it is safe to approve a new drug.

You want to know which investment has the least risk.

We want to predict the weather.Someone makes a claim and we

want to test to see if the claim is believable.


Statistics usually involves Statistics usually involves drawing a sample from a drawing a sample from a large population, analyzing large population, analyzing the sample, and then the sample, and then drawing inferences about drawing inferences about the overall population. the overall population.


Reasons for sampling!Reasons for sampling!

We cannot afford to measure the whole population.

We may not be able to find the whole population even if we could measure it.

We may not have the time to measure it all.


Chapter 1Chapter 1Statistics,Data, and Statistics,Data, and Statistical ThinkingStatistical ThinkingWhat is the process for doing statistical

analysis?What are the different types of data?How is data collected?What is the difference between a

population and a sample ?What is the difference between

descriptive and inferential data?Why is probability theory involved?



STATISTICAL ANALYSIS PROCESS

Population

SampleDescriptive

Statistics

Probability

Inferential Statistics

Parametric Nonparametric


STATISTICAL ANALYSIS PROCESS(Interfaces)

Population

SampleDescriptive

Statistics

Probability

Inferential statistics


data

statistics

test results

confidence intervals

Reliability

Measures


STATISTICAL ANALYSIS PROCESS(Chapters)

Population

SampleDescriptive

Statistics

Probability

Inferential Statistics


Chapter 1

Chapter 2

Chapters 3&4

Chapters 5,6&7

Important DefinitionsImportant Definitions

Population- set of individuals, items, units of interest.

Sample- a subset of individuals, items, units drawn from the population.

Representative sample- a sample that fairly represents the diversity of the population and obtained through random sampling


Definitions(continued)Definitions(continued)Experimental unit- the object in

the population about which data is collected.

Variable- a characteristic or property of the experimental unit

Important DefinitionsImportant Definitions(continued)(continued)

Descriptive Statistics- the processes of :◦ using numerical and graphical

methods to look for patterns in the collected data.

◦ determining summary measures which describe the data set for use in subsequent analysis.

◦ presenting data in a convenient understandable form.


Important DefinitionsImportant Definitions(continued)(continued)Inferential statistics- the processes

used to make estimates, predictions, draw conclusions, or other generalizations about an unknown population(s) based on an analysis of the collected sample data.

Statistical Inference- the estimate, prediction, conclusion, or other generalization made about a population(s).


Food for thought!Food for thought!

How much evidence is required to either accept or

reject the claim of another?


What is it that we What is it that we measure?measure?A characteristic of interest about

each individual or object we measure.◦e.g., Height, color, GPA, temperature


Types Of DataTypes Of Data

Data- the information collected or measured for each member of the sample.◦Qualitative data- information that

cannot be found on a numeric scale, e.g., colors.

◦Quantitative data- information that can be found on a numeric scale, e.g., heights.


Measurement ScalesMeasurement Scales(Levels of Measurement)(Levels of Measurement)Levels of Data Measurement

◦Nominal- Categorical data. Data such as names, places, things. Mathematical operations are meaningless.

◦Ordinal- Information that has a logical sequence or order. Data such as class rank, consumer opinions. Mathematical operations are meaningless.


Measurement ScalesMeasurement Scales(Levels of Measurement)(Levels of Measurement)(continued)(continued)

◦Interval- numeric measured data where the interval between measurements is meaningful but division is not. e.g., Temperature. Data with no true zero.

◦Ratio- measured numeric data where interval and ratios are meaningful. e.g., height. Data with a true zero.


How is data obtained?How is data obtained?Published documents, such as

journals.Surveys, such as consumer

questionnaires.Designed Experiments, such as

tests on new medicines.Observational studies, such as

observing and recording migration habits of birds.


Difference Between Difference Between ExperimentExperimentand Observationand ObservationExperiment- some treatment is

imposed on some or all of the individuals.◦Some patients are given a drug while

others are given a placebo.

Observation- no treatment is imposed.◦Count the number of different colored

cars in a parking lot. Statistics Math 155 27

Another Form of Data Another Form of Data CollectionCollectionSimulation- a model or facimile of

a real world phenomenon.Done when it is impractical to

measure the real world.◦The effects of a nuclear blast.


Samples are reliable if:Samples are reliable if:

They are representative of the underlying population from which they are drawn, i.e., there are no selection bias errors.

Measurement errors are minimizedCare is taken when recording

sample data


How can you get a random How can you get a random sample?sample?Use a Random Number Table.

Use a Random Number Generator in MiniTab and the TI83/84.


Different Sampling Different Sampling TechniquesTechniquesStratified- items of interest are put

into layers, e.g., seniors, juniors, etc.

Systematic- every nth item is measured.

Cluster- clusters a randomly picked and every item in a cluster is measured.

Convenience- individuals are measured as they come along.


Inferences are made in the Inferences are made in the context of a measure of context of a measure of reliabilityreliabilityA measure of reliability is a

statement about the degree of certainty or uncertainty associated with a statistical inference.

Probability theory is a fundamental part of statistical analysis and the development of measures of reliability.


statistics with computer analysis statistics math 1551 instructor robert barber

Documents

understandable statistics

course material

course objective

approved course

important course information

instructor robert barber

course plan step

major course requirements