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## Week 1 notes

1 review
by: Cassie Anderson

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# Week 1 notes 301

Cassie Anderson
Purdue
GPA 3.7
Elementary Statistical Methods

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introduction to stat. chapters 3.1-3.3
COURSE
Elementary Statistical Methods
PROF.
TYPE
Class Notes
PAGES
4
WORDS
KARMA
25 ?

## 2

1 review
"Yes YES!! Thank you for these. I'm such a bad notetaker :/ will definitely be looking forward to these"
Celia O'Hara

## Popular in Statistics

This 4 page Class Notes was uploaded by Cassie Anderson on Friday January 23, 2015. The Class Notes belongs to 301 at Purdue University taught by in Winter2015. Since its upload, it has received 102 views. For similar materials see Elementary Statistical Methods in Statistics at Purdue University.

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## Reviews for Week 1 notes

Yes YES!! Thank you for these. I'm such a bad notetaker :/ will definitely be looking forward to these

-Celia O'Hara

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Date Created: 01/23/15
STAT 301 Lecture 1 Statistics The branch of mathematics that deals with the colletion organization analysis and interpretation of numerical data Speci cally used in drawing general conclusions about a set of data from a sample of the data Three main sections 1 Producing and collecting data experimental design and ethics 2 Descriptive statisticsexamining data distributions graphing and numerical summaries reationships 3 Inferential Statisticsdrawing conclusions estimation signi cance Sources of Data 0 Anecdotal evidence individual cases not random not representative 0 Available data coected previously Producing data observational study experiments QUIZ A study is conducted to investigate the relationship between owning a pet and a person39s happiness 100 subjects are randomly chosen Subjects are asked if they own a pet and to rank their happiness scale of 110 10 being very happy This is an example of a A observational studycensus Bobservational studysurvey Cexperiment Answer B Observational study 0 Do not in uence 0 Observe and measuresurveys sample vs population Experimental Study 0 lmpose a treatment intervention confounding variables 0 Observe and measure LECTURE 2 SAMPLING DESIGN 33 Examples 1 Number of credit hours taken by students in class 0 Population students in class 0 Can survey all individuals 2 amount of money undergrads spend on food each week 0 Population undergrads Cannot observe every individual 3 weight of dogs owned by retirees Populationdogs owned by retirees Cannot observe every individual 4 life span of monkeys 0 Population monkeys Cannot observe every individual Terms Population entire group of individuals units of interest Sample subset of population examined to gather info Censuspopulationsample TYPES OF SAMPLES Convenience sampleseasy to reach not representative Ex people on street Ex newcaster turns to get person at scene opinion bias because they care Voluntary response sample 0 Member choose to answer 0 Not representative Ex response to a survey nonresponsive strongly opinionated Systematic Error BIAS Favors certain outcomes Remedy for biasRANDOM selection of units Probability Sample Utilizes some form of random selection 0 Known possible samples 0 Known probability of getting chosen 0 Random selection chosen by chance 0 Ex pick out of hat use table of random digits Simple random sample SRS Ex put available numbers in a hat and pick ve Ex read digits off a table Simplest probability Sample 0 Choose quotnquot times N individuals selected Sample size is quotnquot units big 0 Each sample has an equal chance of being chosen Systematic Sample 0 Why simple 0 Guaranteed to give units separated from each other 1 1 Determine a sampling interval population divided by size divided by sample size 2 arrange units in population in some order 3 select rst unit randomly Needs to be with in rst sampling interval 0 Select at determined interval from there WATCH OUT FOR HOW UNITS ARE ARRANGED Strati ed random sample 1 Divide population into groups of similar individuals 2 choose separate simple random samples in each stratum 3 combine all strata SRSs to form full sample Multi Stage Sample several random steps 0 cost ef cient convenient ef cient don t need to know actual units beforehand can be a combination of different sampling methods 1 primary sampling units PSU by some sampling 2 secondary sampling units SSU by some sampling 3 Choose SRS from SSU

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