Creating and Interpreting Histograms

To find the number of students scoring between 80 and 89, count them directly. If 9 students fall within this range, the correct answer is A. Each student scoring in this interval contributes to the total of 9.

The interval 80-89 has the most data points. For example, if 25 data points fall in this range, compared to 10 in 70-79, 5 in 90-99, and 15 in 60-69, it clearly has the tallest bar.

To find the number of students in the 70-79 range, review the data. Count each student who scored between 70 and 79. The total adds up to 8, confirming option D as correct.

Most scores fall between 80 and 99, indicating a concentration of higher test scores, which signifies a positive performance trend among test-takers.

The peak indicates that the number of students scoring in the 80-89 range is higher than any other score range, emphasizing this interval as the most populated.

A histogram visualizes data distribution by grouping values into intervals (bins). This allows us to see how data is spread out, identifying patterns such as skewness or normality.

In a histogram, each bar's height shows how many data points fall within that interval. For example, if a bar reaches 5, it means there are 5 data points in that range. This represents the frequency of data in that specific interval.

Histograms display continuous data, and the bars must touch to show intervals of data. This indicates that data points fall within ranges, reinforcing the connection of values across the scale.

The height of the 10-19 bar represents the count of individuals in that age range. Since the bar shows 12, it indicates that there are 12 people whose ages fall between 10 and 19.

In a histogram, the x-axis represents the intervals or bins of data, which categorize the data points. This allows for a visual representation of how data is distributed across different ranges.

The range includes 7, 8, and 9 books. Counting these gives us 3 possibilities. If the total number of students reading is 9, then 9 is the answer.

The interval 0–3 typically contains fewer data points, resulting in a shorter bar. To find the shortest, compare the frequencies of each interval; the lowest frequency indicates the shortest bar.

The data set enumerates each student listed. Counting them reveals a total of 25 students, making option D the correct choice.

The similar heights of the 4–6 and 7–9 intervals indicate that the number of students in these ranges is about the same. This suggests a comparable interest in reading books within these two counts.

The gap indicates that no temperatures were recorded between 60-69°F, as this range shows a lack of data in the histogram. An average temperature or thermometer issues would not create a gap.

Using equal width intervals ensures all data points are represented consistently, allowing for accurate comparison. This approach helps in visualizing the distribution clearly and avoids misleading interpretations that can arise from uneven intervals.

A cluster refers to a group of data points that are closely packed together. In this histogram, the tallest bar at 52-55 indicates many students have heights within this range, forming a cluster. This highlights where most data points concentrate.

Histograms display continuous data, represented by adjacent bars, while bar graphs represent distinct categories with gaps between bars. This distinction helps in understanding data types.

A bimodal distribution has two peaks, indicating two clusters of data. Here, the tallest bar at 52–55 suggests a concentration of heights, confirming the presence of two modes.

To find the frequency for the interval 7–8, count how many values fall within this range. The values are 7, 7, 7, and 8. Therefore, there are 4 occurrences of 7 or more, which gives a frequency of 3 for 7 specifically.