chapter1 - Displaying data with graphs PSLS chapter 1 2009...

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Unformatted text preview: Displaying data with graphs PSLS chapter 1 2009 W.H. Freeman and Company Objectives (PSLS chapter 1) Picturing Distributions with Graphs Individuals and variables Two types of data: categorical and quantitative Ways to chart categorical data: bar graphs and pie charts Ways to chart quantitative data: histograms, dotplots and stemplots Interpreting histograms Time plots Individuals and variables Individuals are the objects described by a set of data. Individuals may be people, animals, or things. Freshmen, 6-week-old babies, golden retrievers, fields of corn, cells A variable is any characteristic of an individual. A variable can take different values for different individuals. Age, gender, blood pressure, blood type, leaf length, flower color Two types of variables A variable can be either quantitative Something that can be counted or measured for each individual. We can then report the average of all individuals measured. Age ( in years ), blood pressure ( in mm Hg ), leaf length ( in cm ) or categorical Something that falls into one of several categories. We can then report the count or proportion of individuals in each category. Gender ( male, female ), blood type ( A, B, AB, O ), flower color ( white, yellow, red ) How do you decide if a variable is categorical or quantitative? Ask: What are the n individuals examined (in the sample or population)? What is being recorded about those n individuals? Is that a number ( quantitative) or a statement ( categorical)? Individuals in sample DIAGNOSIS AGE AT DEATH Patient A Heart disease 56 Patient B Stroke 70 Patient C Stroke 75 Patient D Lung cancer 60 Patient E Heart disease 80 Patient F Accident 73 Patient G Diabetes 69 Quantitative Each individual is attributed a numerical value Categorical Each individual is assigned to one of several categories Ways to chart categorical data When a variable is categorical, the data in the graph can be ordered any way we want (alphabetical, by increasing value, by year, by personal preference, etc.). Most common ways to graph categorical data: Bar graphs Each category is represented by a bar that represents the counts of individuals in that category or their relative frequency (percent of all categories shown). Pie charts Each category is represented by a slice of the whole pie that represents its relative frequency. Peculiarity: The slices must represent the parts of one coherent whole. Example: Top 10 causes of death in the United States, 2001 Rank Causes of death Counts Percent of top 10s Percent of total deaths 1 Heart disease 700,142 37% 29% 2 Cancer 553,768 29% 23% 3 Cerebrovascular 163,538 9% 7% 4 Chronic respiratory 123,013 6% 5% 5 Accidents 101,537 5% 4% 6 Diabetes mellitus 71,372 4%...
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This note was uploaded on 10/07/2011 for the course BSTT 400 taught by Professor Sallyfreels during the Fall '11 term at Ill. Chicago.

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chapter1 - Displaying data with graphs PSLS chapter 1 2009...

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