Final answer:
The distribution of daily high temperatures in the Dominican Republic in August, given the sample data, is skewed due to an outlier of 95 degrees. The outlier causes the data set to deviate from a normal distribution. Most temperatures cluster around a lower range with one much higher value.
Step-by-step explanation:
In the context of the Dominican Republic in August, the distribution of daily high temperatures based on the provided data set appears to be skewed. The temperatures are mostly grouped within a certain range, but there is a marked outlier, which is the temperature of 95 degrees. This outlier skews the data set from what might have been a normal distribution to one that is skewed. If we were to create a histogram of this data, we would see most of the temperatures piling up on the lower end with only a single instance of a much higher temperature.
It's important to recognize that the terms normal, skewed, uniform, and bimodal are descriptive of the shape of the data when graphed. In this case, most of the temperatures cluster around the 60s to 70s with an outlier in the 90s, which creates a skewed distribution.
As for the question regarding the distribution described by the example of people running distances, the correct answer is exponential distribution because as the distance increases the number of people able to run that far decreases at an exponential rate.