For each ight in the sample, data was collected on two variables: its date and its departure delay (in minutes), which is computed as the difference between the actual and scheduled departure times. A negative value for the departure delay means that the flight departed early. Use the DataView tool to obtain the mean and standard deviation of the departure delays. The mean departure delay is minutes. The standard deviation of the departure delays is minutes. (Hint: Click one of the Variable sliding panels on the left side of the tool screen, and select the variable named Departure Delay. Then click on the Statistics button. You will see a screen showing different statistics calculated for the variable.) For any set of data, Chebysheff's theorem tells you that at least of the data values must lie within 1.70 standard deviations of the mean. Use the DataView tool to determine the proportion of data values within 1.70 standard deviations of the mean. (Hint: In the tool, click the Variable panel for Departure Delay. Under the heading Filter: Include observations between ..., enter the appropriate values for the elds Minimum and Maximum to lter out observations that are more than 1.?0 standard deviations from the mean. Remember to erase these values when you want to use the tool with unltered data.)- For the departure delays in this data set, of the values lie within 1.70 standard deviations of the mean. This is the proportion specied by Chebysheff's theorem. when a data set has a symmetrical mound-shaped or bell-shaped distribution, the Empirical Rule tells you that of the data values will be within 1 standard deviation of the mean and will be within 2 standard deviations of the mean. Use the DataView tool to examine the shape of the distribution of departure delays. The distribution of the departure delays is . Therefore, the Empirical Rule hold for this distribution