This document discusses effective methods for communicating data, including comparing and contrasting different tools for displaying data like tables, scattergrams, line graphs, pie charts, bar charts, and trend analysis. It also examines determining data quality and sources. The document lists common tools used in data analysis and presentation such as spreadsheet, word processing, presentation, statistical, and business intelligence software.

1. Effectively Communicating
Data
Chapter 8

2. CHAPTER 8 LEARNING OBJECTIVES
After studying the material in this chapter students will:
• examine methods of determining data quality, sources, and
appropriateness
• compare and contrast methods of effectively displaying data
• evaluate the types of tools used in data display and management

3. Displaying Data
 Tables are the most common way to
visually describe data.
 Scattergrams are used to show a pattern or
relationship between two variables.
 Line graphs are useful for showing
patterns over time.

4. Displaying Data Cont’d.
 Pie charts show the contribution of values to
a whole and are useful when the data is
represented in percentages.
 A three-dimensional exploded pie chart is
useful when there are several revenue
categories that are small.
 Bar and column charts are similar to pie
charts in that they are not very useful for
displaying negative numbers but it is
possible with bar charts.

5. Trend Analysis
 Trend analysis is a table that shows the
change in a variable over time and works
best for revenues and expenditures that
are stable.
 Nollenberger’s four steps to constructing a
trend analysis
 The main drawback to trend analysis is
that it cannot predict how major events or
the economy will affect revenue or
expenditure streams.

6. COMMON TOOLS USED IN DATA
ANALYSIS & PRESENTATION
• spreadsheet applications (Excel, Numbers, Libre Office, Open Office etc.)
• word processing applications (Word, Pages, Libre Office, Open Office etc.)
• presentation applications (PowerPoint, Keynote, Prezi, Sway etc.)
• statistical software (Minitab, SPSS, Matlab, SAS etc.)
• business intelligence applications (Sisense, Tableau, BIRT, Knime etc.)