A. Use a dot plot for 15 customers' wait times. B. Compare distribution shapes and centers between the two restaurants.
To effectively compare the shapes and centers of the data distributions for the two restaurants (A and B), you'll need to consider the characteristics of box plots and dot plots.
A. Box Plot for Restaurant A: A box plot provides a visual representation of the distribution of a dataset. It includes the following components:
Median (Center): The line inside the box represents the median of the data.
Interquartile Range (IQR): The box represents the IQR, the range between the first quartile (Q1) and the third quartile (Q3).
Whiskers: Lines extending from the box represent the minimum and maximum values within 1.5 times the IQR from the quartiles.
Outliers: Any data points beyond the whiskers are considered outliers.
B. Dot Plot for Restaurant B:
A dot plot is a simple way to display individual data points in a dataset. Each dot represents a single observation.
Comparing Shapes:
Box Plot (Restaurant A): Look for symmetry or skewness, the spread of data (IQR), and the presence of outliers.
Dot Plot (Restaurant B): Observe the distribution of dots to identify any patterns, clusters, or outliers.
Comparing Centers:
Box Plot (Restaurant A): The median represents the center of the data distribution.
Dot Plot (Restaurant B): The overall concentration of dots can provide an indication of the center.
Suggestions for Comparison:
Shapes :Check for symmetry or skewness in the box plot for Restaurant A.
Examine the pattern of dots in the dot plot for Restaurant B.
Centers:Compare the medians of the box plot for Restaurant A and the overall concentration of dots in the dot plot for Restaurant B.
Outliers:Identify any outliers in the box plot for Restaurant A and check if there are isolated dots in the dot plot for Restaurant B.