Frequency polygons

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  • When you have completed this chapter, you will be able to: Organize raw data into frequency distribution; produce a histogram, a frequency polygon, and a cumulative frequency polygon from quantitative data; develop and interpret a stem-and-leaf display; present qualitative data using such graphical techniques such as a clustered bar chart, a stacked bar chart, and a pie chart; detect graphic deceptions and use a graph to present data with clarity, precision, and efficiency.

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  • Chapter 2 - Describing data: Frequency tables, frequency distributions, and graphic presentation. When you have completed this chapter, you will be able to: Organize qualitative data into a frequency table, present a frequency table as a bar chart or a pie chart, organize quantitative data into a frequency distribution, present a frequency distribution for quantitative data using histograms, frequency polygons, and cumulative frequency polygons.

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  • Chapter 2 - Describing data: Frequency tables, frequency distributions, and graphic presentation. After completing this unit, you should be able to: Organize qualitative data into a frequency table, present a frequency table as a bar chart or a pie chart, organize quantitative data into a frequency distribution, present a frequency distribution for quantitative data using histograms, frequency polygons, and cumulative frequency polygons.

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  • Statistics has evolved into a very important discipline that is applied in many fields. In the modern age of computing, both statistical methodology and its applications are expanding greatly. Among the many areas of application, we (Friis and Cher- nick) have direct experience in the use of statistical methods to military problems, space surveillance, experimental design, data validation, forecasting workloads, predicting the cost and duration of insurance claims, quality assurance, the design and analysis of clinical trials, and epidemiologic studies. ...

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  • Chapter 2 - Descriptive statistics: Tabular and graphical methods. After mastering the material in this chapter, you will be able to: Summarize qualitative data by using frequency distributions, bar charts, and pie charts; construct and interpret Pareto charts (Optional); summarize quantitative data by using frequency distributions, histograms, frequency polygons, and ogives;...

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  • The learning objectives for this chapter include: Explain the concept of the normal curve; look for evidence of normally distributed data when you read research reports; read a frequency distribution and polygon; describe the differences among mean, median, and mode; explain how the standard deviation affects interpretation of the mean; accurately interpret tables that report data as frequencies and percentages.

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  • Chapter 9 - Descriptive statistics, significance levels, and hypothesis testing. After reading this chapter, you should be able to: Explain the concept of the normal curve, assess data for its distribution and compare it to the normal curve, create a frequency distribution and polygon for each variable in a dataset, compute and interpret the mean, median, and mode for each variable in a dataset,...

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