Alright, let's determine how to match this data to the appropriate histogram. Here are the steps to follow:
1. Organize the Data into Ranges:
First, we need to think about how to group the life expectancy values into intervals (or bins). This is a common step when creating histograms.
Let's say we group these values in 2-year intervals:
- 74 - 75.9
- 76 - 77.9
- 78 - 79.9
- 80 - 81.9
- 82 - 83.9
2. Count the Frequencies:
Next, count how many states fall into each of these intervals.
- 74 - 75.9: [West Virginia (74.1)] → 1 state
- 76 - 77.9: [Tennessee (77.9)] → 1 state
- 78 - 79.9: [South Carolina (78.3), Oklahoma (78.2), Illinois (78.6), Kansas (78.6)] → 4 states
- 80 - 81.9: [Vermont (80.4), California (80.9), Georgia (80.1), Nevada (81.3)] → 4 states
- 82 - 83.9: [Utah (82.2)] → 1 state
3. Create the Histogram:
Match the data to a histogram that displays these counts:
- 74 - 75.9: 1 state
- 76 - 77.9: 1 state
- 78 - 79.9: 4 states
- 80 - 81.9: 4 states
- 82 - 83.9: 1 state
In conclusion, the correct histogram would have:
- 1 bar reaching up to the value of 1 for the interval 74 - 75.9.
- 1 bar reaching up to the value of 1 for the interval 76 - 77.9.
- 1 bar reaching up to the value of 4 for the interval 78 - 79.9.
- 1 bar reaching up to the value of 4 for the interval 80 - 81.9.
- 1 bar reaching up to the value of 1 for the interval 82 - 83.9.
By analyzing the values and their respective frequencies, you should be able to match these to the correct histogram visually.
