The Bureau of Transportation Statistics (BTS) collects, analyzes, and disseminates information on U.S. transportation systems, including data on airline on-time performance . Consider departure-time data for all flights of an unspecified major airline out of New York City's John F. Kennedy Airport from December 1 through 7, 2007. These data, obtained from BTS, can be viewed in the following DataView tool. Data Set Departure Sample Variables - 2 Observations - 248 Departure Statistics for a Major Airline December 1 through 7, 2007 Observations Variable V Type V Form A SUISSIW & Sanlex Observations > Date Qualitative Nonnumeric 248 Departure Delay Quantitative Numeric 248 Variable Variable Correlation Ch 03: Mastery Assignment - Descriptive Statistics: Numerical Measures For each flight in the sample, data was collected on two va between the actual and scheduled departure times. A neg es: its date and its departure delay (in minutes), which is computed as the difference negative value for the departure delay means that the flight departed early. Use the DataView tool to obtain the mean and standard deviation arture delay is 23.7 V minutes. The standard deviation of the departure delays is 54.6 V minutes. (Hint: C select the variable named Departure Delay. Then click on the Statistics bu els on the left side of the tool screen, and variable.) en showing different statistics calculated for the Observation 178 in the data set ure delay is _ which means that the departure delay is ins away from the mean ation can be considered an outlier, because it is _ than 3 standard deviations Hint: To obtain the departure delay for the flight corres observation 178, click the Data Set panel and the Observations button. Scroll down until you reach observation 178. For any set of data, Chebyshev's theorem tells you that at least of the data values must lie within 1.70 standard devia ations of the mean. Use the DataView tool to detern mean. (Hint: In the tool, click the Variable panel for Departure Delay. Under the heading Filter: Include obse es for the fields Minimum and Maximum to filter out obse ions that are more than 1.70 standard dev emember to erase these values when you want to use the tool with unfiltered data.) Use the DataView tool to determine the proportion of data values within 1.70 standard de e mean. (Hint: In the tool, click the Variable panel for Departure Delay. Under te values for the fields Minimum and Maximum to filter out observations that are more than 1.70 sta these values when you want to use the tool with unfiltered 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 specified by Chebyshev'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 de on 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