Dot plots display frequency of discrete data.
Histograms display frequency of continuous data in ranges.
Golf scores are discrete values.
Dot plot is best because scores are individual. Dot plot, because a small number of scores are reported individually
Explanation
Analyze the data We have data about the scores of 15 athletes in a golf competition. The scores are discrete values (1, 2, 3, 4, 5), and we know how many athletes achieved each score. We need to decide whether a dot plot or a histogram would be the best way to represent this data.
Dot plot characteristics A dot plot is great for showing the frequency of individual data points, especially when those points are discrete (separate, distinct values). Each dot represents one data point, and you can easily see how many times each value occurs.
Histogram characteristics A histogram, on the other hand, is used for showing the distribution of continuous data, where the data is grouped into ranges or bins. Histograms are useful for seeing the overall shape of the data and identifying patterns like skewness or normal distribution.
Compare data to plot types In our case, the golf scores are individual, discrete values. We aren't dealing with ranges of scores. Therefore, a dot plot is the more appropriate choice for representing this data because it directly shows the frequency of each individual score.
Conclusion Based on the analysis, a dot plot is the best way to represent the data because the scores are reported individually, not as ranges.
Examples
Imagine you're tracking the number of books students read each month. A dot plot would be perfect for showing how many students read 1 book, 2 books, 3 books, etc. Each dot represents a student, and you can quickly see the most common number of books read. This is similar to our golf scores, where each dot could represent an athlete and their score.