Final answer:
Without the specific data, the answers provided offer general methods for describing a dotplot, identifying outliers using the IQR rule, and selecting the best measure of center considering the distribution of the data and presence of outliers.
Step-by-step explanation:
To answer the student's question regarding the description of a dotplot, identification of outliers, and the best measure of center, we would need specific data points for the number of times students at Diggamole High eat fruit per week. Without the actual data, we can provide a general method for analysis.
Part A: A dotplot consists of a number line where each dot represents one occurrence of a data point. For example, if four students eat fruit three times a week, there would be four dots above the number three on the number line. This plot helps to visualize the frequency of each data point.
Part B: Outliers are data points that differ significantly from others in a dataset. To identify outliers, we could calculate the Interquartile Range (IQR) and use the rule stating that any data points less than Q1 - 1.5(IQR) or greater than Q3 + 1.5(IQR) could be considered potential outliers. Without the actual dataset, we can only provide this general approach.
Part C: The best measure of center could be the mean, median, or mode. The mean is useful when data is symmetrically distributed without outliers. The median is a good measure when the data has outliers or is skewed, as it is not affected by extreme values. The mode is helpful when the data is categorical or when we want to identify the most frequently occurring value. Considering the presence of outliers and the nature of data distribution will guide selecting the most appropriate measure.