Chap 2-1 Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chapter 2 Describing Data: Graphical Statistics for Business and Economics 6 th Edition

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-2 Chapter Goals After completing this chapter, you should be able to: Identify types of data and levels of measurement Create and interpret graphs to describe categorical variables: frequency distribution, bar chart, pie chart, Pareto diagram Create a line chart to describe time-series data Create and interpret graphs to describe numerical variables: frequency distribution, histogram, ogive, stem-and-leaf display Construct and interpret graphs to describe relationships between variables: Scatter plot, cross table Describe appropriate and inappropriate ways to display data graphically

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-3 Types of Data Data CategoricalNumerical DiscreteContinuous Examples: Marital Status Are you registered to vote? Eye Color (Defined categories or groups) Examples: Number of Children Defects per hour (Counted items) Examples: Weight Voltage (Measured characteristics)

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-4 Measurement Levels Interval Data Ordinal Data Nominal Data Quantitative Data Qualitative Data Categories (no ordering or direction) Ordered Categories (rankings, order, or scaling) Differences between measurements but no true zero Ratio Data Differences between measurements, true zero exists

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-5 Graphical Presentation of Data Data in raw form are usually not easy to use for decision making Some type of organization is needed Table Graph The type of graph to use depends on the variable being summarized

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-6 Graphical Presentation of Data Techniques reviewed in this chapter: Categorical Variables Numerical Variables Frequency distribution Bar chart Pie chart Pareto diagram Line chart Frequency distribution Histogram and ogive Stem-and-leaf display Scatter plot (continued)

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-7 Tables and Graphs for Categorical Variables Categorical Data Graphing Data Pie Chart Pareto Diagram Bar Chart Frequency Distribution Table Tabulating Data

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-8 The Frequency Distribution Table Example: Hospital Patients by Unit Hospital Unit Number of Patients Cardiac Care 1,052 Emergency 2,245 Intensive Care 340 Maternity 552 Surgery 4,630 (Variables are categorical) Summarize data by category

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-9 Bar and Pie Charts Bar charts and Pie charts are often used for qualitative (category) data Height of bar or size of pie slice shows the frequency or percentage for each category

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-10 Bar Chart Example Hospital Number Unit of Patients Cardiac Care 1,052 Emergency 2,245 Intensive Care 340 Maternity 552 Surgery4,630

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-11 Pie Chart Example (Percentages are rounded to the nearest percent) Hospital Number % of Unit of Patients Total Cardiac Care 1, Emergency 2, Intensive Care Maternity Surgery 4,

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-12 Pareto Diagram Used to portray categorical data A bar chart, where categories are shown in descending order of frequency A cumulative polygon is often shown in the same graph Used to separate the vital few from the trivial many

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-13 Example: 400 defective items are examined for cause of defect: Source of Manufacturing ErrorNumber of defects Bad Weld34 Poor Alignment223 Missing Part25 Paint Flaw78 Electrical Short19 Cracked case21 Total400 Pareto Diagram Example

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-14 Step 1: Sort by defect cause, in descending order Step 2: Determine % in each category Source of Manufacturing ErrorNumber of defects% of Total Defects Poor Alignment Paint Flaw Bad Weld Missing Part Cracked case Electrical Short Total400100% Pareto Diagram Example (continued)

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-15 Pareto Diagram Example cumulative % (line graph) % of defects in each category (bar graph) Step 3: Show results graphically (continued)

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-16 Graphs for Time-Series Data A line chart (time-series plot) is used to show the values of a variable over time Time is measured on the horizontal axis The variable of interest is measured on the vertical axis

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-17 Line Chart Example

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-18 Numerical Data Stem-and-Leaf Display HistogramOgive Frequency Distributions and Cumulative Distributions Graphs to Describe Numerical Variables

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-19 What is a Frequency Distribution? A frequency distribution is a list or a table … containing class groupings (categories or ranges within which the data fall)... and the corresponding frequencies with which data fall within each class or category Frequency Distributions

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-20 Why Use Frequency Distributions? A frequency distribution is a way to summarize data The distribution condenses the raw data into a more useful form... and allows for a quick visual interpretation of the data

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-21 Class Intervals and Class Boundaries Each class grouping has the same width Determine the width of each interval by Use at least 5 but no more than intervals Intervals never overlap Round up the interval width to get desirable interval endpoints

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-22 Frequency Distribution Example Example: A manufacturer of insulation randomly selects 20 winter days and records the daily high temperature 24, 35, 17, 21, 24, 37, 26, 46, 58, 30, 32, 13, 12, 38, 41, 43, 44, 27, 53, 27

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-23 Sort raw data in ascending order: 12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58 Find range: = 46 Select number of classes: 5 (usually between 5 and 15) Compute interval width: 10 (46/5 then round up) Determine interval boundaries: 10 but less than 20, 20 but less than 30,..., 60 but less than 70 Count observations & assign to classes Frequency Distribution Example (continued)

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-24 Frequency Distribution Example Interval Frequency 10 but less than but less than but less than but less than but less than Total Relative Frequency Percentage Data in ordered array: 12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58 (continued)

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-25 Histogram A graph of the data in a frequency distribution is called a histogram The interval endpoints are shown on the horizontal axis the vertical axis is either frequency, relative frequency, or percentage Bars of the appropriate heights are used to represent the number of observations within each class

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-26 Temperature in Degrees Histogram Example (No gaps between bars) Interval 10 but less than but less than but less than but less than but less than 60 2 Frequency

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-27 Histograms in Excel Select Tools/Data Analysis 1

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-28 Choose Histogram 2 3 Input data range and bin range (bin range is a cell range containing the upper interval endpoints for each class grouping) Select Chart Output and click OK Histograms in Excel (continued) (

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-29 Questions for Grouping Data into Intervals 1.How wide should each interval be? (How many classes should be used?) 2.How should the endpoints of the intervals be determined? Often answered by trial and error, subject to user judgment The goal is to create a distribution that is neither too "jagged" nor too "blocky Goal is to appropriately show the pattern of variation in the data

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-30 How Many Class Intervals? Many (Narrow class intervals) may yield a very jagged distribution with gaps from empty classes Can give a poor indication of how frequency varies across classes Few (Wide class intervals) may compress variation too much and yield a blocky distribution can obscure important patterns of variation. (X axis labels are upper class endpoints)

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-31 The Cumulative Frequency Distribuiton Class 10 but less than but less than but less than but less than but less than Total Percentage Cumulative Percentage Data in ordered array: 12, 13, 17, 21, 24, 24, 26, 27, 27, 30, 32, 35, 37, 38, 41, 43, 44, 46, 53, 58 Frequency Cumulative Frequency

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-32 The Ogive Graphing Cumulative Frequencies Interval endpoints Interval Less than but less than but less than but less than but less than but less than Cumulative Percentage Upper interval endpoint

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-33 Distribution Shape The shape of the distribution is said to be symmetric if the observations are balanced, or evenly distributed, about the center.

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-34 Distribution Shape The shape of the distribution is said to be skewed if the observations are not symmetrically distributed around the center. (continued) A positively skewed distribution (skewed to the right) has a tail that extends to the right in the direction of positive values. A negatively skewed distribution (skewed to the left) has a tail that extends to the left in the direction of negative values.

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-35 Stem-and-Leaf Diagram A simple way to see distribution details in a data set METHOD: Separate the sorted data series into leading digits (the stem) and the trailing digits (the leaves)

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-36 Example Here, use the 10s digit for the stem unit: Data in ordered array: 21, 24, 24, 26, 27, 27, 30, 32, 38, is shown as 38 is shown as Stem Leaf

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-37 Example Completed stem-and-leaf diagram: StemLeaves (continued) Data in ordered array: 21, 24, 24, 26, 27, 27, 30, 32, 38, 41

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-38 Using other stem units Using the 100s digit as the stem: Round off the 10s digit to form the leaves 613 would become would become becomes 12 2 Stem Leaf

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-39 Using other stem units Using the 100s digit as the stem: The completed stem-and-leaf display: Stem Leaves (continued) Data: 613, 632, 658, 717, 722, 750, 776, 827, 841, 859, 863, 891, 894, 906, 928, 933, 955, 982, 1034, 1047,1056, 1140, 1169, 1224

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-40 Relationships Between Variables Graphs illustrated so far have involved only a single variable When two variables exist other techniques are used: Categorical (Qualitative) Variables Numerical (Quantitative) Variables Cross tables Scatter plots

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-41 Scatter Diagrams are used for paired observations taken from two numerical variables The Scatter Diagram: one variable is measured on the vertical axis and the other variable is measured on the horizontal axis Scatter Diagrams

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-42 Scatter Diagram Example Volume per day Cost per day

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-43 Scatter Diagrams in Excel Select the chart wizard 1 2 Select XY(Scatter) option, then click Next When prompted, enter the data range, desired legend, and desired destination to complete the scatter diagram 3

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-44 Cross Tables Cross Tables (or contingency tables) list the number of observations for every combination of values for two categorical or ordinal variables If there are r categories for the first variable (rows) and c categories for the second variable (columns), the table is called an r x c cross table

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-45 Cross Table Example 4 x 3 Cross Table for Investment Choices by Investor (values in $1000s) Investment Investor A Investor B Investor C Total Category Stocks Bonds CD Savings Total

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-46 Side by side bar charts (continued) Graphing Multivariate Categorical Data

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-47 Side-by-Side Chart Example Sales by quarter for three sales territories:

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-48 Data Presentation Errors Goals for effective data presentation : Present data to display essential information Communicate complex ideas clearly and accurately Avoid distortion that might convey the wrong message

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-49 Unequal histogram interval widths Compressing or distorting the vertical axis Providing no zero point on the vertical axis Failing to provide a relative basis in comparing data between groups Data Presentation Errors (continued)

Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chap 2-50 Chapter Summary Reviewed types of data and measurement levels Data in raw form are usually not easy to use for decision making -- Some type of organization is needed: Table Graph Techniques reviewed in this chapter : Frequency distribution Bar chart Pie chart Pareto diagram Line chart Frequency distribution Histogram and ogive Stem-and-leaf display Scatter plot Cross tables and side-by-side bar charts