A pie chart typically represents numbers in percentages, used to visualize a part to whole relationship or a composition. Pie charts are not meant to compare individual sections to each other or to represent exact values (you should use a bar chart for that).

In general, pie charts work well when the goal is to emphasize simple fractions, such as one-half, one-third, or one-quarter. They also work well when we have very small datasets. A single pie chart, as in Figure 10.1, looks just fine, but a single column of stacked bars, as in Figure 10.2a, looks awkward.

In a pie graph, each slice of the pie represents a share of the total, or a percentage.

Best types of charts for comparing

• Use a bar or column chart to compare independent values.
• Use a bubble chart to compare independent values with clear outliers.
• Use a pie chart to compare parts of a whole (composition)
• Use a stacked bar or stacked column chart to compare the compositions of multiple values.

If you want to compare values, use a pie chart — for relative comparison — or bar charts — for precise comparison. If you want to compare volumes, use an area chart or a bubble chart. If you want to show trends and patterns in your data, use a line chart, bar chart, or scatter plot.

Choosing a graphing style by data type When comparing values, use column, bar, line and scatter-plot charts. When showing the distribution of data, use scatter-plot, line, column and bar charts. When analyzing trends in data, use line and column charts.

Answer. 1)Pie charts: Pie charts present a bunch of proportional items and it’s always not possible to gather any worthy data from the results.

Bar graphs show data with blocks of different lengths, whereas line graphs show a series of points connected by straight lines.

Line graphs are used to track changes over short and long periods of time. When smaller changes exist, line graphs are better to use than bar graphs. Line graphs can also be used to compare changes over the same period of time for more than one group.

Don’t use a bar graph to compare items that require different scales. Because that will complicate your message. You should also avoid using bar graphs to show percentages that add up to a whole if they aren’t broken down over time. Because those would be…

A bar chart is a graph with rectangular bars. The graph usually compares different categories. For example, if you had two houses and needed budgets for each, you could plot them on the same x-axis with a grouped bar chart, using different colors to represent each house. See types of bar graphs below.

Bar graphs are one of the many techniques used to present data in a visual form so that the reader may readily recognize patterns or trends. Bar graphs usually present categorical and numeric variables grouped in class intervals. They consist of an axis and a series or labeled horizontal or vertical bars.

Bar graphs are an extremely effective visual to use in presentations and reports. They are popular because they allow the reader to recognize patterns or trends far more easily than looking at a table of numerical data.

Graphs are a common method to visually illustrate relationships in the data. The purpose of a graph is to present data that are too numerous or complicated to be described adequately in the text and in less space.

Line graphs are useful in that they show data variables and trends very clearly and can help to make predictions about the results of data not yet recorded. They can also be used to display several dependent variables against one independent variable.

What Are the Disadvantages of A Line Graph?

• Plotting too many lines over the graph makes it cluttered and confusing to read.
• A wide range of data is challenging to plot over a line graph.
• They are only ideal for representing data made of total figures such as values of total rainfall in a month.

The following pages describe the different parts of a bar graph.

• The Title. The title offers a short explanation of what is in your graph.
• The Source. The source explains where you found the information that is in your graph.
• X-Axis. Bar graphs have an x-axis and a y-axis.
• Y-Axis.
• The Data.
• The Legend.

Explanation: Line graphs consist of two axes: x-axis (horizontal) and y-axis (vertical), graphically denoted as (x,y). Each axis represents a different data type, and the points at which they intersect is (0,0). The x-axis is the independent axis as its values are not dependent on anything measured.

The following pages describe the different parts of a line graph.

• The Title. The title offers a short explanation of what is in your graph.
• The Legend. The legend tells what each line represents.
• The Source. The source explains where you found the information that is in your graph.
• Y-Axis.
• The Data.
• X-Axis.

Some of the strengths of line graphs are that: They are good at showing specific values of data, meaning that given one variable the other can easily be determined. They show trends in data clearly, meaning that they visibly show how one variable is affected by the other as it increases or decreases.

A double line graph is a line graph with two lines. A graph that compares two different subjects over a period of time. A double line graph shows how things change over a period of time.

Double-click the “Chart Title” text box on the graph. Highlight the text, and then type over it with your line graph’s title.

Rational curves

• Circle. Unit circle.
• Ellipse.
• Parabola.
• Hyperbola. Unit hyperbola.

Real-Life Applications of Straight-Line Graph Straight line graphs are used in the research process and the preparation of the government budget. Straight line graphs are used in Chemistry and Biology. Straight line graphs are used to estimate whether our body weight is appropriate according to our height.

Straight Line Graphs play an important part in our modern lives. They are used extensively in Sales and Marketing, Economics, Business, Psychology, Science and Medicine. Moore’s Law is expected to continue this straight line pattern until at least 2015 or 2020. …

Graphs highlight the salient features of the data. They can show relationships that are not obvious from studying a list of numbers. They can also provide a convenient way to compare different sets of data.