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Stor 155, Section 2, Last Time

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Title: Stor 155, Section 2, Last Time


1
Stor 155, Section 2, Last Time
  • Course Organization Website
  • http//stat-or.unc.edu/webspace/postscript/marron/
    Teaching/stor155-2007/Stor155-07Home.html
  • What is Statistics?
  • Data types and structure
  • Get going in EXCEL
  • Exploratory Data Analysis
  • Bar Graphs

2
Reading In Textbook
  • Approximate Reading for Todays Material
  • Pages 14-23
  • Approximate Reading for Next Class
  • Pages 40-55

3
Stat 31, Student Poll Results
As indicated on Student Info form
Big changes from the past More Public More
diversity
4
Stat 31, Student Poll Results
  • Have you taken an AP Exam?
  • Only 10 had grades generally low
  • So dont worry if you havent

5
Stat 31, Student Poll Results
  • Female 48
  • Male 53
  • Interesting Point
  • Different from all of UNC 60 - 40
  • Lesson about which courses to take???

6
Major Concept Distributions
  • Distribution Patterns of data
  • Way data is spread
    out
  • e.g. Bar Graph is visual display of categorical
    distribution

7
Exploratory Data Analysis 2
  • Visual Display of Quantitative Distributions
  • Stem and Leaf Plots
  • (From last time) Not Recommended
  • (Main motivation was pencil and paper statistical
    analysis, but now have better graphical methods
    readily accessible)
  • A limited special case of.

8
Visual Disp Quantitative Distns
  • 2. Histograms
  • Idea Apply bar graph idea,
  • By creating categories,
  • Called class intervals or classes or bins

9
Histograms
  • Idea put numbers into bins,
  • bar heights are counts, or frequencies
  • 1.3
  • 3.6
  • 1.9
  • 3.1
  • 1.5

10
Histograms
  • Idea put numbers into bins,
  • bar heights Class Intervals
  • 1.3 (0,1, (1,2,
    (2,3, (3,4
  • 3.6
  • 1.9
  • 3.1
  • 1.5 0 1 2 3
    4

11
Histograms
  • Idea put numbers into bins,
  • bar heights are counts, or frequencies
  • 1.3
  • 3.6
  • 1.9
  • 3.1
  • 1.5 0 1 2 3
    4

12
Histograms
  • Idea put numbers into bins,
  • bar heights are counts, or frequencies
  • 1.3
  • 3.6
  • 1.9
  • 3.1
  • 1.5 0 1 2 3
    4

13
Buffalo Snowfall Data
  • Buffalo, N. Y. (Annual) Snowfall Data
  • Raw Data
  • http//stat-or.unc.edu/webspace/postscript/marron/
    Teaching/stor155-2007/Stor155Eg2Raw.xls
  • 63 years, ranging from 30 - 120
    (inches)
  • Histogram Analysis (pre-done)
  • http//stat-or.unc.edu/webspace/postscript/marron/
    Teaching/stor155-2007/Stor155Eg2Done.xls

14
Buffalo Snowfall Data, I
  • A. EXCEL default (of bin edges)
  • Unround numbers for bin edges
  • Harder to interpret
  • Data centered around 90
  • Most data between 50 and 130
  • Assymetric Distribution

15
Buffalo Snowfall Data, II
  • B. Smaller bins
  • Chosen by me
  • Binwidth 5, ltlt 13 from EXCEL default
  • Nicer edge numbers
  • Data centered around 84 (now more precise)
  • Bar graph rougher (fewer points in each bin)
  • Suggests 3 main groups
  • (called modes or clusters)
  • (cant see this above bin width is important)

16
Buffalo Snowfall Data, III
  • C. Larger bins
  • Chosen by me
  • Binwidth 30, gtgt 13 from EXCEL default
  • Bar graph is smooth
  • (since many points in each bin)
  • Only one mode (cluster)???
  • Quite symmetric?
  • (different from above bin width is important)

17
Buffalo Snowfall Data, IV
  • Whats under the hood (how to do this)
  • Tools ? Data Analysis ? Histogram ( Chart Out)
  • (may need Data Analysis Add-in)
  • Massage pic (especially bar width)
  • Sigma ? min, max
  • Bin range create first two drag
  • Histogram, using input bin edges

18
Histogram HW
  • HW 1.33
  • Use Excel and histograms
  • Get data from CDrom
  • Do both
  • Excel Default bins
  • Bins set to 0,10,20,,240
  • Which gives answers closer to answers in back of
    book?
  • Turn in only one page

19
And now for something completely different
  • Is this class too monotone?
  • Easier to understand?
  • Calm environment enhances learning?
  • Or does it induce somnolence?
  • What is somnolence?
  • Google definition
  • Sleepiness, a condition of
  • semiconsciousness approaching coma.

20
And now for something completely different
  • Recall last classs Student Questionnaire
  • I asked you for
  • Name
  • Major
  • Contact Info
  • Background

21
And now for something completely different
  • One response

22
And now for something completely different
  • OK, will try to send your mind in a different
  • direction
  • Hopefully, a mental break
  • (not on the Homework Assignment!)

23
And now for something completely different
  • An experiment
  • Pull out any coins you have with you
  • How many of you have
  • gt 1 penny?
  • gt 1 nickel?
  • gt 1 dime?
  • gt 1 quarter?
  • Choose most frequent denomination

24
And now for something completely different
  • Collect data (into Spreadsheet)
  • Years stamped on coins
  • (chosen denomination)
  • Many as person has
  • Enter into spreadsheet
  • Look at distribution using histogram

25
And now for something completely different
  • Predicted Answer
  • From Text Book, Problem 1.32
  • Distribution is Left Skewed
  • Works out as predicted?
  • Why?
  • Note most skewed distns seem to be
  • Right Skewed

26
Histogram Binwidths
  • Nice Example from the Webster West, U.S.C.
  • http//www.stat.sc.edu/west/applets/histogram.htm
    l
  • Control Binwidth with slider
  • Undersmoothing?
  • About right?
  • Oversmoothing?
  • (critical to visual impression)

27
Histogram Binwidth Example
  • Hidalgo Stamp Data
  • From Mexico in 1800s
  • How many sources of paper?
  • How many modes
  • 1, 2, 5, 7, 10?

28
Histogram Binwidth Example
  • How many modes (i.e. clusters)?
  • Caution Answer depends on binwidth
  • (a serious and current
  • statistical research problem)
  • Have seen all of 2,3,5,7,10 in the literature!

29
Stamps Data Histogram
  • How many modes?
  • 2nd Caution Answer also depends on bin location
  • (i.e. shift of bins)

30
Histogram Bins
  • For this course
  • Try several binwidths, to get the idea
  • Weakness of EXCEL (we will see several)
  • This process is inconvenient

31
Comparison of Histograms
  • Class Example Study Habits Data
  • Idea Compare Study Habits of Males vs. Females
    (measured by some survey score, perhaps of
    questionable value?)
  • http//stat-or.unc.edu/webspace/postscript/marron/
    Teaching/stor155-2007/Stor155Eg4Done.xls

32
Study Habits Data
  • EXCEL default histograms
  • Populations look similar???
  • Careful Binwidth very big
  • Careful Different bin ranges
  • Need smaller binwidths, and common scales

33
Study Habits Data
  • Better Choice Binwidths 10, same bins for
    both
  • Clear difference, easy to see
  • Females higher on average
  • Males are more spread
  • 1 exceptional value, really true???

34
Things to look for (in histos)
  • Population Center Point (Study Habits Data)
  • Population Spread (Study Habits Data)
  • Shape - Symmetric vs. Skewed
  • Right Skewed
  • Left Skewed
  • Modes - Unexpected clusters
  • Outliers - unusual data points

35
Histogram Data Examples
  • Textbook Applets from Publishers Website
  • One Variable Statistical Calculator
  • Data Set Service Times at a Call Center
  • Histogram
  • (hold mouse button, and slide left-right)
  • Results
  • Broad range of binwdiths (12 25 is best?)
  • Single bin is useless
  • Distribution is Right Skewed
  • Clear Outlier

36
Comparison of Histograms HW
  • HW 1.35b, 1.34, 1.17
  • Work in this order
  • Get data from CDrom
  • Use EXCEL and histograms
  • Odd answers in back
  • You choose the bins
  • (if you miss something in answers, change this)
  • Turn in at most one page for each
  • 1.31, 1.32

37
Exploratory Data Analysis 3
  • Time Plots, i.e. Time Series
  • Idea when time structure is important,
  • plot variable as a function of time
  • variable
  • time
  • Often useful to connect the dots

38
Class Time Series Example
  • Monthly Airline Passenger Numbers
  • http//stat-or.unc.edu/webspace/postscript/marron/
    Teaching/stor155-2007/Stor155Eg5Done.xls
  • Increasing Trend
  • (long term growth, over years)
  • Increasing Variation
  • (appears proportional to trend)
  • Seasonal Effect - 12 Month Cycle
  • (Peak in summer, less in winter)

39
Airline Passengers Example
  • Interesting variation log transformation
  • Stabilizes variation
  • Since log of product is sum
  • Shows changing variation propl to trend
  • Log10 is most interpretable
  • (log10(1000) 3, )
  • Generally useful trick (there are others)

40
Airline Passengers Example
  • A look under the hood
  • http//stat-or.unc.edu/webspace/postscript/marron/
    Teaching/stor155-2007/Stor155Eg5Raw.xls
  • Use Chart Wizard
  • Chart Type Line (or could do XY)
  • Use subtype for points lines
  • Use menu for first log10
  • Although could just type it in
  • Drag down to repeat for whole column

41
Time Series HW
  • HW 1.36, 1.37
  • Use EXCEL
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