+ Chapter 1: Exploring Data Section 1.2 Displaying Quantitative Data with Graphs The Practice of Statistics, 4 th edition - For AP* STARNES, YATES, MOORE

+ Chapter 1 Exploring Data Introduction: Data Analysis: Making Sense of Data 1.1Analyzing Categorical Data 1.2Displaying Quantitative Data with Graphs 1.3Describing Quantitative Data with Numbers

+ Section 1.2 Displaying Quantitative Data with Graphs After this section, you should be able to… CONSTRUCT and INTERPRET dotplots, stemplots, and histograms DESCRIBE the shape of a distribution COMPARE distributions USE histograms wisely Learning Objectives

+ 1)Draw a horizontal axis (a number line) and label it with the variable name. 2)Scale the axis from the minimum to the maximum value. 3)Mark a dot above the location on the horizontal axis corresponding to each data value. Displaying Quantitative Data Dotplots One of the simplest graphs to construct and interpret is adotplot. Each data value is shown as a dot above its location on a number line. How to Make a Dotplot Number of Goals Scored Per Game by the 2004 US Women’s Soccer Team

+ Oops! We lost the ball Here are the numbers of turnovers for the2009 Oakland Raiders football team duringtheir 16 regular-season NFL games: 3, 0, 3, 3,3, 2, 4, 1, 2, 3, 1, 0, 2, 3, 2. Make a dotplot ofthis data.

+ Examining the Distribution of a Quantitative Variable The purpose of a graph is to help us understand the data. Afteryou make a graph, always ask, “What do I see?” In any graph, look for the overall pattern and for striking departures from that pattern. Describe the overall pattern of a distribution by its: Shape Center Spread Note individual values that fall outside the overall pattern. These departures are called outliers. How to Examine the Distribution of a Quantitative Variable Displaying Quantitative Data Don’t forget your SOCS!

+ Examine this data The table and dotplot below displays the EnvironmentalProtection Agency’s estimates of highway gas mileage in milesper gallon (MPG) for a sample of 24 model year 2009 midsizecars. Displaying Quantitative Data Describe the shape, center, and spread of the distribution. Are there any outliers? Example, page 28

+ Smart Phone BatteryLife Here is the estimated batter life for each of nine differentsmart phones (in minutes) according to phones.toptenreviews.com/smartphones/. phones.toptenreviews.com/smartphones/ Smart PhoneBattery Life (minutes) Apple iPhone300 Motorola Droid385 Palm Pre300 Blackberry Bold360 Blackberry Storm330 Motorola Cliq360 Samsung Moment330 Blackberry Tour300 HTC Droid460 a)Draw a dot plot. b)Describe the shape, center, and spread of the distribution. Are there any outliers?

+ Displaying Quantitative Data Describing Shape When you describe a distribution’s shape, concentrate onthe main features. Look for rough symmetry or clear skewness. Definitions: A distribution is roughly symmetric if the right and left sides of the graph are approximately mirror images of each other. A distribution is skewed to the right (right-skewed) if the right side of the graph (containing the half of the observations with larger values) is much longer than the left side. It is skewed to the left (left-skewed) if the left side of the graph is much longer than the right side. Symmetric Skewed-left Skewed-right

+ Die Rolls and QuizScores Here are two dotplots for two different sets of quantitativedata. Describe the shape of these two dotplots.

+ Describing Shape Complete the Check Your Understanding onpg 31.

+ Displaying Quantitative Data Comparing Distributions Some of the most interesting statistics questionsinvolve comparing two or more groups. Always discuss shape, center, spread, andpossible outliers whenever you comparedistributions of a quantitative variable. Example, page 32 Compare the distributions of household size for these two countries. Don’t forget your SOCS! Place U.K South Africa

+ 1)Separate each observation into a stem (all but the final digit) and a leaf (the final digit). 2)Write all possible stems from the smallest to the largest in a vertical column and draw a vertical line to the right of the column. 3)Write each leaf in the row to the right of its stem. 4)Arrange the leaves in increasing order out from the stem. 5)Provide a key that explains in context what the stems and leaves represent. Displaying Quantitative Data Stemplots (Stem-and-Leaf Plots) Another simple graphical display for small data sets is astemplot. Stemplots give us a quick picture of the distributionwhile including the actual numerical values. How to Make a Stemplot

+ Displaying Quantitative Data Stemplots (Stem-and-Leaf Plots) These data represent the responses of 20 female APStatistics students to the question, “How many pairs ofshoes do you have?” Construct a stemplot Stems Add leaves Order leaves Add a key Key: 4|9 represents a female student who reported having 49 pairs of shoes.

+ Displaying Quantitative Data Splitting Stems and Back-to-Back Stemplots When data values are “bunched up”, we can get a better picture ofthe distribution by splitting stems. Two distributions of the same quantitative variable can becompared using a back-to-back stemplot with common stems Key: 4|9 represents a student who reported having 49 pairs of shoes. Females Males Females Males “split stems”

+ Who’s Taller? Which gender is taller, males or females? A sample of 14-year-olds from the United Kingdom was randomly selectedusing the CensusAtSchol Web site. Here are the heights ofthe students (in cm): Male: 154, 157, 187, 163, 167, 159, 169, 162, 176, 177, 151,175, 174, 165, 165, 183, 180 Female: 160, 169, 152, 167, 164, 163, 160, 163, 169, 157,158, 153, 161, 165, 165, 159, 168, 153, 166, 158, 158, 166 Make individual stemplots for male and female heights. Thenmake a back-to-back stemplot comparing male and femaleheights.

+ Let’s stop here for now. Homework pg 42: 37, 39, 41,43, 45, 47

+ 1)Divide the range of data into classes of equal width. 2)Find the count (frequency) or percent (relative frequency) of individuals in each class. 3)Label and scale your axes and draw the histogram. The height of the bar equals its frequency. Adjacent bars should touch, unless a class contains no individuals. Displaying Quantitative Data Histograms Quantitative variables often take many values. A graph of thedistribution may be clearer if nearby values are groupedtogether. The most common graph of the distribution of onequantitative variable is a histogram. How to Make a Histogram

+ Making a Histogram The table on page 35 presents data on the percent ofresidents from each state who were born outside of the U.S. Displaying Quantitative Data Example, page 35 Frequency Table ClassCount 0 to <520 5 to < to < to < to < to <301 Total50 Percent of foreign-born residents Number of States

+ NBA scoring averages TeamPPGTeamPPGTeamPPG Atlanta Hawks101.7Indiana Pacers100.8 Oklahoma City Thunder101.5 Boston Celtics99.2 Los Angeles Clippers95.7Orlando Magic102.8 Charlotte Bobcats95.3Los Angeles Lakers101.7Philadelphia 76ers97.7 Chicago Bulls97.5Memphis Grizzlies102.5Phoenix Suns110.2 Cleveland Cavaliers102.1Miami Heat96.5 Portland Trail Blazers98.1 Dallas Mavericks102Milwaukee Bucks97.7Sacramento Kings100 Denver Nuggets106.5 Minnesota Timberwolves98.2San Antonio Spurs101.4 Detroit Pistons94New Jersey Nets92.4Toronto Raptors104.1 Golden State Warriors108.8 New Orleans Hornets100.2Utah Jazz104.2 Houston Rockets102.4New York Knicks102.1 Washington Wizards96.2 The following table presents the average points scored per game (PTSG) for the 30 NBA teams in the regular season. Make a histogram representing this data.

+ Technology Corner Check out the technologycorner on pg 38! It shows you how to dohistograms on the calculator.

+ Check yourunderstanding Complete the Check YourUnderstanding on page 39.

+ 1)Don’t confuse histograms and bar graphs. 2)Don’t use counts (in a frequency table) or percents (in a relative frequency table) as data. 3)Use percents instead of counts on the vertical axis when comparing distributions with different numbers of observations. 4)Just because a graph looks nice, it’s not necessarily a meaningful display of data. Displaying Quantitative Data Using Histograms Wisely Here are several cautions based on common mistakesstudents make when using histograms. Cautions

+ Check yourunderstanding Complete the Check Your Understandingon pg 41.

+ In this section, we learned that… You can use a dotplot, stemplot, or histogram to show the distribution of a quantitative variable. When examining any graph, look for an overall pattern and for notable departures from that pattern. Describe the shape, center, spread, and any outliers. Don’t forget your SOCS! Some distributions have simple shapes, such as symmetric or skewed. The number of modes (major peaks) is another aspect of overall shape. When comparing distributions, be sure to discuss shape, center, spread, and possible outliers. Histograms are for quantitative data, bar graphs are for categorical data. Use relative frequency histograms when comparing data sets of different sizes. Summary Section 1.2 Displaying Quantitative Data with Graphs

+ Looking Ahead… We’ll learn how to describe quantitative data with numbers. Mean and Standard Deviation Median and Interquartile Range Five-number Summary and Boxplots Identifying Outliers We’ll also learn how to calculate numerical summaries with technology and how to choose appropriate measures of center and spread. In the next Section…

+ For Tonight… TB pg 45: 53, 55, 57, 59, 60, Homework…