1. Get That List!! (Programs) PREZ, CHEST, LISTRES

2.  We use the following to graph quantitative data › Dot Plot › Stem & Leaf › Histogram › Ogive

3.  Dot Plot › Labels, Need Spot for EACH value  Stem & Leaf Plot › Leaves are only 1 digit

4.  STAT EDIT to enter the data › Or Run “List” Program 2 nd Y= to set up a plot Xlist = L1; Freq = 1 Zoom 9 to View it A lot of times, this graph isn’t any good… You may have to make some corrections!!!

5.  Reset XSCL to a value that is easy to count in close to whole # multiples…  Lower XMIN to a multiple of XSCL  Press GRAPH  You may need to go back and change YMAX to see all of the bars…  You want between 5 and 15 bars  Trace to see X-Scale

6.  We use the following three aspects to describe all distributions in statistics › First, we’ll look at the 3 in graphical context  Center › Where most of the values are located (usually tells the average)  Shape › Tendency of the tails, symmetry, unusual patterns  Spread › The overall spread of the graph, how far the values are from the center

7.  Graphically, the center is typically where the majority of the values are located › Sometimes the center is difficult to locate graphically  We just get a general idea of the center

8.  Typically how far the values are from center  Graphically, it’s the RANGE › Highest Value – Lowest Value  This doesn’t tell you a whole lot statistically 96 – 40 = 56

9.  Most Important Characteristic taken from Graph › Symmetrical (roughly)  Graph looks similar on each side of the center › Skewed Left  Tail of graph points to left › Skewed Right  Tail of graph points to right

10.  The shape can tell you a lot about a distribution › Skewed Left  Most of values tend toward higher end of scale › Skewed Right  Most of values tend toward lower end of scale Examples 1.7

11.  Graphically, located outside of most other values  Deviate from pattern of rest of graph

12.  Percentile › Where an individual is in relation to the rest of the distribution › Pth percentile – p percent falls at or below that value  Relative Frequency Graph › Y-Scale is measured in percentage (decimal)  Cumulative Frequency Graph (Ogive) › Helps us see position of individual in relation to rest of values › Gives View of Percentiles

13.  Ogives use the relative cumulative frequency  Let’s Use a table to learn how to make an ogive ClassFreqRel FreqCum FreqRel Cum Freq 40 – 4422/432 45 – 4966/43(6+2) = 88/43 50 – 541313/43(8+13) = 2121/43 55 - 591230.2%3378.8% 60 – 64716.3%4093% 65 – 6937%43100%

14.  U then Graph it like a time plot, with the y-axis being % and the x-axis the lower end of the class ClassRel Cum Freq 40 – 442/43 45 – 498/43 50 – 5421/43 55 - 5978.8% 60 – 6493% 65 – 69100% This allows me to find individuals!!! Let’s Find Lincoln!! This means approximately 60% of US Presidents were the same age or younger than Lincoln when they were inaugurated. *Be Prepared to go from Percentile to Age as well

15.  Plots each observation of a variable against the time it was measured  Used in business for sales, look for seasonal patterns  Horizontal axis is always time

16.  Survey Project  Book Problems › #’s 23-29,30