Describing Data Using Graphs and Tables
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OVERVIEW 2.1Graphs and Tables for Categorical Data 2.2Graphs and Tables for Quantitative Data 2.3Further Graphs and Tables for Quantitative Data 2.4Graphical Misrepresentations of Data Chapter 2 Vocabulary Chapter 2 Review Exercises Chapter 2 Quiz |
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Criminal Justice in New York City
Is it safer to walk the streets in New York City than it was, say, in the 1990s? In the Chapter 2 Case Study, Criminal Justice in New York City, we examine whether rates of crime have fallen in the past couple of decades, along with many other questions.
In Section 2.1, we examine a bar chart of the various misdemeanor offenses that occurred throughout all police precincts of the city, and ask which category of misdemeanors is the most common. We also explore, in the Your Turn examples, tables and graphics regarding a random sample of traffic violations in Manhattan and Brooklyn.
In the Section 2.1 exercises, we compare bar graphs for the number of petit (“petty”) larcenies that took place in 2000 and 2013, and ask whether the results represent good news.
In Section 2.2, we construct a stem-and-leaf display for the number of misdemeanor dangerous weapons cases in 20 Manhattan precincts. We also examine a comparison dotplot of third-degree assault and criminal trespass cases across all the police precincts of New York City. Then, we note that a histogram of the criminal trespass data represents a right-skewed distribution.
In the Section 2.2 exercises, we compare the frauds taking place in Brooklyn in 2000 and 2013, using distributions, histograms, and a comparison dotplot, and ask whether the difference in the graphs represents welcome news. We also construct a frequency polygon, a stem-and-leaf display, and a dotplot of the 2013 Brooklyn fraud data. Then, we compare the number of petit larceny cases city-wide for 2000 and 2013, using the previously named graphs. At the end of the section we ask which graph is preferable, depending on the objective of the analysis.
In Section 2.3, we construct a time series plot of the murder rate in New York City from 1990 to 2014, and we find some truly good news in the results.
Finally, in the Section 2.3 exercises, we construct time series plots of the number of third-degree assaults city-wide and describe the patterns we see.
THE BIG PICTURE
Where we are coming from and where we are headed . . .
In Chapter 1, we learned the basic concepts of statistics, such as population, sample, and types of variables, along with methods of collecting data.
Here, in Chapter 2, we learn about graphs and tables for summarizing qualitative data and quantitative data, and we examine how to prevent our graphics from becoming misleading.
Later, in Chapter 3, we will learn how to describe a data set using numerical measures instead of graphs and tables.