stat12t_Chapter1

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Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights

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Lecture Slides

Introduction to Statistics for engineers

Lecturer: Dr. Long, HV

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Chapter 1Introduction to Statistics

1-1 Review and Preview

1-2 Statistical Thinking

1-3 Collecting Sample Data

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Section 1-1Review and Preview

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Preview

+ Polls, studies, surveys and other data collecting tools collect data from a small part of a larger group so that we can learn something about the larger group.

+ Common and important goal of statistics: Learn about a large group by examining data from some of its members.

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Preview

In this context, the terms sample and population have special meaning. Formal definitions for these and other basic terms will be given here.

In this section we will look at some of the ways to describe data.

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Data

� Data

collections of observations (such as

measurements, genders, survey

responses)

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Statistics

� Statistics

is the science of planning studies

and experiments, obtaining data, and

then organizing, summarizing,

presenting, analyzing, interpreting,

and drawing conclusions based on

the data

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Population

� Population

the complete collection of all

individuals (scores, people,

measurements, and so on) to be

studied; the collection is complete in

the sense that it includes all of the

individuals to be studied

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Census versus Sample


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� Census

Collection of data from everymember of a population

� Sample

Subset of members selected from a population

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Section 1-2 Statistical Thinking

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Key Concept

This section introduces basic principles of statistical thinking used throughout this book. Whether conducting statistical analysis of data that we have collected, or analyzing a statistical analysis done by someone else, we should not rely on blind acceptance of mathematical calculation. We should consider these factors:

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Key Concept (continued)

� Context of the data

� Source of the data

� Sampling method

� Conclusions

� Practical implications


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Context

� What do the values represent?

� Where did the data come from?

� Why were they collected?

� An understanding of the context will directly affect the statistical procedure used.

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Source of data

� Is the source objective?

� Is the source biased?

� Is there some incentive to distort or spin results to support some self-serving position?

� Is there something to gain or lose by distorting results?

� Be vigilant and skeptical of studies from sources that may be biased.

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Sampling Method

� Does the method chosen greatly influence the validity of the conclusion?

� Voluntary response (or self-selected) samples often have bias (those with special interest are more likely to participate). These samples’ results are not necessarily valid.

� Other methods are more likely to produce good results.

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Conclusions

� Make statements that are clear to those without an understanding of statistics and its terminology

� Avoid making statements not justified by the statistical analysis.

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Section 1-3 Collecting Sample Data

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Statistical methods are driven by the data that we collect. We typically obtain data from two distinct sources: observational studies and experiment.

Basics of Collecting Data

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� Observational study

observing and measuring specific characteristics without attempting to modify

the subjects being studied

Observational Study

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� Experiment

apply some treatment and then observe its effects on the subjects; (subjects inexperiments are called experimental units)

Experiment

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Is the study experimental or

observational?

� A marketing firm does a survey to find out how many

people use a product. Of the one hundred people contacted, fifteen said they use the product.

� A doctor performs several diagnostic tests to

determine the reason for a patient's illness.

� A clinic gives a drug to a group of ten patients and a

placebo to another group of ten patients to find out if the drug has an effect on the patients' illness.

� A sample of fish is taken from a lake to measure the

effect of pollution from a nearby factory on the fish.

� A political pollster reports that his candidate has a 10% lead in the polls with 10% undecided.

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+) A quality control specialist compares the output from a machine with a new lubricant to the output of machines with the old lubricant.+) A stock analyst selects a stock from a group of

twenty for investment by choosing the stock with the

greatest earnings per share reported for the last

quarter.+) A stock analyst compares the relationship

between stock prices and earnings per share to help

him select a stock for investment.

+) A T.V. show's executives raised the fee for

commercials following a report that the show received a "No. 1" rating in a survey of viewers

+) A T.V. show's executives commissioned a study

to gauge the impact of the show's ratings on the

sales of its advertisers

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Simple Random Sample

� Simple Random Sample

of n subjects selected in such a way that

every possible sample of the same size n

has the same chance of being chosen

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� Random Sample

members from the population are selected in such a way that each individual memberin the population has an equal chance of being selected

Random & Probability Samples

� Probability Sample

selecting members from a population in such a way that each member of the population has a known (but not necessarily the same) chance of being selected

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Random Sampling selection so that each

individual member has an equal chance of being selected

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Systematic SamplingSelect some starting point and then

select every kth element in the population

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Convenience Samplinguse results that are easy to get

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Stratified Samplingsubdivide the population into at

least two different subgroups that share the same characteristics, then draw a sample from each

subgroup (or stratum)

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Cluster Samplingdivide the population area into sections

(or clusters); randomly select some of those clusters; choose all members from selected clusters

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� Sampling error

the difference between a sample result and the true

population result; such an error results from chance

sample fluctuations

� Nonsampling error

sample data incorrectly collected, recorded, or

analyzed (such as by selecting a biased sample,

using a defective instrument, or copying the data

incorrectly)

Errors

No matter how well you plan and execute the sample collection process, there is likely to be some error in the results.

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