Question

the accompanying data are 45 commute times to work in minutes for workers of age 16 or older in chicago. construct a frequency distribution. use a class width of 15 minutes and begin with a lower class limit of 0 minutes. do the data amounts appear to have a normal distribution? examine the data and identify anything appearing to be unique. click the icon to view the commute times. construct the frequency distribution:

commute time (minutes)	frequency

( type whole numbers. )

Explanation:

To construct the frequency distribution, we first need the actual commute time data (which is referenced as "Click the icon to view the commute times" but not provided here). However, assuming we have the data, here's the general step - by - step process:

Step 1: Define the classes

The class width is 15 minutes and the first class has a lower limit of 0 minutes. So the classes will be:

• \(0 - 14\) (since the class width is 15, the upper limit of the first class is \(0 + 15- 1=14\))
• \(15 - 29\) (lower limit = 15, upper limit=\(15 + 15-1 = 29\))
• \(30 - 44\)
• \(45 - 59\)
• \(60 - 74\)
• \(75 - 89\)
• \(90 - 104\) (and so on, depending on the maximum value in the data set)

Step 2: Count the frequency for each class

For each class, we go through the 45 commute time data points and count how many data points fall within each class interval. For example, if a data point is 10, it goes into the \(0 - 14\) class; if it is 20, it goes into the \(15 - 29\) class, etc.

Since the actual data is not provided, we can't give the exact frequency values. But once you have the data, you can follow the above steps to fill in the frequency column in the table.

To determine if the data has a normal distribution, we would check the following:

• The frequency distribution should be approximately symmetric around the mean (the middle class should have the highest frequency, and frequencies should decrease gradually as we move away from the middle class in both directions).
• The shape of the frequency distribution (when plotted as a histogram) should be approximately bell - shaped.

If we assume that we have the data and after constructing the frequency distribution, we can analyze the symmetry and the shape of the distribution to see if it is normal.

Since the data is not provided, we can't give the final frequency distribution table with numbers. But the process to construct it is as described above.

Answer:

To construct the frequency distribution, we first need the actual commute time data (which is referenced as "Click the icon to view the commute times" but not provided here). However, assuming we have the data, here's the general step - by - step process:

Step 1: Define the classes

The class width is 15 minutes and the first class has a lower limit of 0 minutes. So the classes will be:

• \(0 - 14\) (since the class width is 15, the upper limit of the first class is \(0 + 15- 1=14\))
• \(15 - 29\) (lower limit = 15, upper limit=\(15 + 15-1 = 29\))
• \(30 - 44\)
• \(45 - 59\)
• \(60 - 74\)
• \(75 - 89\)
• \(90 - 104\) (and so on, depending on the maximum value in the data set)

Step 2: Count the frequency for each class

For each class, we go through the 45 commute time data points and count how many data points fall within each class interval. For example, if a data point is 10, it goes into the \(0 - 14\) class; if it is 20, it goes into the \(15 - 29\) class, etc.

Since the actual data is not provided, we can't give the exact frequency values. But once you have the data, you can follow the above steps to fill in the frequency column in the table.

To determine if the data has a normal distribution, we would check the following:

• The frequency distribution should be approximately symmetric around the mean (the middle class should have the highest frequency, and frequencies should decrease gradually as we move away from the middle class in both directions).
• The shape of the frequency distribution (when plotted as a histogram) should be approximately bell - shaped.

If we assume that we have the data and after constructing the frequency distribution, we can analyze the symmetry and the shape of the distribution to see if it is normal.

Since the data is not provided, we can't give the final frequency distribution table with numbers. But the process to construct it is as described above.