Identity Theft Identity fraud occurs when someone else’s personal information is used to open credit card accounts, apply for a job, receive benefits, and so on. The following relative frequency bar graph represents the various types of identity theft based on a study conducted by the Federal Trade Commission. Approximately what percentage of identity theft was loan fraud (such as applying for a loan in someone else’s name)?

Verified step by step guidance

1. Step 1: Understand the graph's axes. The horizontal axis represents the relative frequency, which is the proportion of each type of identity theft out of the total cases, and the vertical axis lists the types of identity theft.
2. Step 2: Locate the bar corresponding to 'Loan fraud' on the vertical axis. This bar shows the relative frequency of loan fraud cases.
3. Step 3: Observe the length of the 'Loan fraud' bar and compare it to the scale on the horizontal axis to estimate its relative frequency value.
4. Step 4: Convert the relative frequency to a percentage by multiplying the relative frequency value by 100. For example, if the relative frequency is 0.05, then the percentage is \$0.05 \times 100$.
5. Step 5: State the approximate percentage of identity theft that was loan fraud based on this calculation.

Key Concepts

Relative Frequency

Relative frequency represents the proportion of times a particular event occurs compared to the total number of events. It is calculated by dividing the frequency of a specific category by the total frequency of all categories. In this context, it shows the percentage of each type of identity theft relative to all reported cases.

Bar Graph Interpretation

A bar graph visually displays data using bars of different lengths to represent values. The length of each bar corresponds to the relative frequency of each category. Understanding how to read the graph allows you to estimate the percentage or proportion of each type of identity theft, such as loan fraud.

Percentage Estimation from Graphs

Estimating percentages from graphs involves interpreting the scale and length of bars relative to the axis labels. By comparing the bar length for loan fraud to the relative frequency scale, you can approximate the percentage it represents, which is essential for answering questions about data distribution.