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. time (minutes) frequency 0 - 14 15 - 29 30 - 44 45 - 59 60 - 74 75 - 89 (type whole numbers)

Explanation:

Step1: Count data in 0 - 14

Go through the 45 commute - time data values and count how many fall within the 0 - 14 minute range.

Step2: Count data in 15 - 29

Repeat the process for the 15 - 29 minute range.

Step3: Count data in 30 - 44

Repeat for the 30 - 44 minute range.

Step4: Count data in 45 - 59

Repeat for the 45 - 59 minute range.

Step5: Count data in 60 - 74

Repeat for the 60 - 74 minute range.

Step6: Count data in 75 - 89

Repeat for the 75 - 89 minute range.

Since the actual data values are not provided here, we can't give the exact frequencies. But the general process is as above. To check for a normal distribution, if the frequency distribution has a bell - shaped curve (symmetric about the mean, with most of the data in the middle classes and fewer data in the extreme classes), it may be considered approximately normal. To identify unique aspects, look for outliers (data values far from the rest), or any unusual clustering or gaps in the data.

Answer:

Without the actual data values, we can't fill in the frequency values in the table. For the normality check and uniqueness identification, follow the above - described procedures once the data is available.