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(Also, how to do it right, and MOST IMPORTANTLY,how to tell the difference!)
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How does Statistics and Graphical Displays(truthful or not) matter in a computer scienceclass???Data and information are so prevalentin our lives today, that it is knownas the Information Age
Being literate today means not just beingable to read, but being able to understand themassive amount of information thrown at usevery day much of it on the computer.
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In order to analyze andinterpret data, we mustfirst collect it.
The data that is collectedis known as a sample .
The sample is collectedfrom a population .
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We wanted to analyzeSan Diego oceantemperatures in CSE3.Our population was theocean off the coast ofSan Diego.
Our sample , was thetemperatures recordedby Buoy100 over thelast 9 years.
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If we were to claim thatour results wererepresentative of:
California coastal watersSouthern California coastalwatersSan Diego coastal waters
Or even La Jolla coastalwaters
That would be called
Biased SamplingAnd we could use it to lie,
cheat, manipulate, ormislead the general
public.
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If we were to claim that our findings wereapplicable to the entire California coast, or
even just the San Diego coast, we would beguilty of perpetrating an area bias .The area of your sample needs to berepresentative of the study population.When reading news stories or scientificarticles, make sure you verify that there is noarea bias in the study.
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The World Wildlife Fund (WWF) haswritten on the threats posed to polarbears from global warming.However, also according to them, about20 distinct polar bear populations exist,accounting for approximately 22,000polar bears worldwide.
Only 2 of the groups are decreasing.10 populations are stable.2 populations are increasing.The status of the remaining 6 populations isunknown.
If you only looked at the 2 groups thatare decreasing, it would be easy to saythat Polar Bear Population isDecreasing. You need to look at thewhole picture to get the whole story.
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In Self-Selection Bias , aparticipants' decision toparticipate may be
correlated with traitsthat affect the study,making the participantsa non-representativesample.
For example:If you were to set up a
booth to ask people
about their groominghabitsThe people who respond
are more likely to bethose who take moretime to primp in themorning than those who just throw on somethingand head out the door.
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If you have a survey that asks:Dont you think that CSE3 TAs are paid
too little?A) Yes they should earn moreB) No they should not earn moreC) No opinion
You are suggesting by the tone of the questionwhat you believe the answer should be. That willbias your results (is it always bad?)
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If you ask people in a survey about how oftenthey shower, or how often they recycle, your
data is going to be biased bythe fact that nobody wants toadmit to doing something thatis considered sociallyundesirable.
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Adding in a Sampling bias into your datacollection is an important tool if you want to
lie, cheat, manipulate, or mislead with yourstudy results!
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Data analysis is a process of gathering,modeling, and transforming data with the
goal of highlighting useful information,suggesting conclusions, and supportingdecision making.
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We saw in lab that if you werent careful, youcould accidentally miscalculate the trendline
for the water temperature readings byincluding uneven data:
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65
7075
80
1/30/2001 1/30/2002 1/30/2003 1/30/2004 1/30/2005 1/30/2006 1/30/2007 1/30/2008 1/30/2009
T e m p e r a t u r e
( F )
Date
Mean Ocean Temperature
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What if you were a real-estate agent and youwere trying to convince people to move into a
particular neighborhood.You could, with perfect honesty andtruthfullness tell different people that theaverage income in the neighborhood is:
a) $150,000b) $35,000c) $10,000
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The $150,000 figure is the arithmetic mean of theincomes of all the families in the neighborhood.The $35,000 figure is the median.
The $10,000 figure is the mode.This particular neighborhood is lucky enough to be near
a cliff and the ONE home with an ocean view is agiant mansion on 50 acres that is owned by aHollywood Star. With gates. And spikes. And securityto keep out the riff raff of the rest of theneighborhood of poor people and the few middleclass that live nearby.
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One Celebritymaking
$4,465,000 FiveProfessionals
making$150,000
14 peoplemaking$50,000
One poorschmuckmaking$35,000 20 people
making$10,000
MeanMedian Mode
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Interpreting data ofteninvolves displaying it insome useful way.To interpret our WaterTemperature data, wecreated charts tovisualize theinformation.Charts are a type ofGraphical Display.
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1/1 2/1 3/1 4/1 5/1 6/1 7/1 8/1 9/110/111/112/1
T e m p e r a t u r e
( F )
Day
Daily Ocean Temperature Statistics2001-2009
Min
Max
Average
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If your goal is to lie, cheat, manipulate, ormislead, Graphical Displays are your friend
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The principals of Graphical Excellence (GE) are:GE is the well-designed presentation of interesting data a matter of substance , of statistics , and of design .GE consists of complex ideas communicated withclarity, precision , and efficiency.GE is that which gives to the viewer the greatest
number of ideas in the shortest time with the least inkin the smallest space .To lie, cheat, manipulate, or mislead, do NOTfollow this advice!!!
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This is real data. The top graph shows the cosmic radiation rate inneutrons per hour. The lower is the temperature change since 1975 whenit started. All from the BBCs website. They werent trying to lie, cheat,manipulate, or mislead! No sirree.
+20
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Here, the data is thesame but by changingthe axis labels,someone was able toreally suggest that thedifference inpopulation was muchgreater than it was.
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Once again, both of these charts show the sameinformation if you ONLY look at the HEIGHT ofthe frogs. The volume of an image is a great wayto lie, cheat, manipulate, or mislead
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Easy to readLots of usefulinformationWell labeled!Correctcomparison ofpercentagesrather thannumbers!Scary results!
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Napoleoninvades Russiawith 422,000
men
ReachedMoscow with
100,000 men
Returnedwith only10,000 men
Six variables are plotted: The size of the army Its location on a 2D surface Direction of army movement Temperature on variousdates during the retreat
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Look at the sources. If none are given, do NOTtrust the information.Check to see if there are any obvious sources of
bias in the data. Look at how the data wascollected and where it was collected from.Look very closely at the data axis and legend.
And finally, do NOT believe everything you areshown just because it is Science and Data.Try to figure out if the source has some ulteriormotive to manipulate your opinion.
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How to Lie with StatisticsBy Darrell Huff, Norton, New York, 1954
The Visual Display of QuantitativeInformation
By Edward Tufte, Graphics Press, February 1997
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