1. Reading Data: Tables, Bar Graphs, and Line Graphs
GED® Data Analysis & Probability · preview lesson
Data visualization displays information in a format that is quick to understand. The GED® tests your ability to extract information from common displays.
Tables:
A table organizes data into rows and columns. Always read the header row and column labels carefully.
Example table:
\[
\begin{array}{c|c|c|c}
\text{Month} & \text{Sales} & \text{Profit} & \text{Units Sold} \\
\hline
\text{January} & \$12,000 & \$3,200 & 240 \\
\text{February} & \$15,000 & \$4,100 & 300 \\
\text{March} & \$13,500 & \$3,700 & 270 \\
\end{array}
\]
From this table, you can quickly see that February had the highest sales (\$15,000) and the highest profit (\$4,100).
Bar Graphs:
Bar graphs compare categories using rectangular bars. The height (or length) of each bar represents the value.
Key reading skills:
- Read the title to understand what is displayed.
- Check the axis labels (x-axis and y-axis).
- Use the scale to determine approximate values.
- Compare bar heights to identify trends.
Line Graphs:
Line graphs show change over time. Each point represents a value at a specific time, and connecting lines show the trend.
Advantages of line graphs:
- Show trends clearly.
- Make it easy to spot increases, decreases, and patterns.
- Can display multiple data series on the same graph.
Example interpretation: If a line graph shows temperature rising from Monday to Wednesday, then dropping Thursday to Friday, you can say temperature "increased early in the week, then decreased late in the week."
Real-world context: A store manager reviews weekly sales data from a table to identify which day sells the most. A nurse reads a patient's temperature graph to monitor fever trends.
Common mistake: misreading the scale. Always check if each grid line represents 1, 10, 100, or another unit.
💡 Tip: Before answering a question, spend 10 seconds identifying the title, labels, and scale. This prevents careless errors.
From a table showing monthly sales, how do you find the highest-selling month?
Compare the values in the relevant column.
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