|x: cars/5 min|
The back-to-back holidays on Wednesday and Friday provide a week off from statistics. During this week long break the statistics class will engage in a traffic measurement exercise. During the next week find a stretch of road near wherever you happen to be.
Note the date, time, location, and name of the road - if any. For twenty-five minutes count the number of cars that pass during five minute intervals. The easiest way to do this is to simply write down the time (just the minutes will work) at which the car passes.
After twenty-five minutes, divide the data into bins of five minutes in duration each. Count the number of cars in each five minute bin and use that in your table.
Use the sample size n, sample mean x and the sample standard deviation sx to calculate a 95% confidence interval for the population mean µ number of cars per five minute periods using the student's t-distribution.
No two class members should use the exact same data. If you choose to do the same section of road, do it on a different day or a different time than other classmates.
Remember: If your 95% confidence interval for your mean includes nine, then your segment of road is NOT statistically significantly more or less busy than the one measured in test two out at Song Mahs in Pehleng, Kitti. If your interval is wholly and completely above nine, then your road is busier. If your interval is wholly and completely less than nine, then your road is less busy.
|Statistic or Parameter||Symbol||Equations||Excel|
|Chapter nine: Confidence interval statistics|
|Degrees of freedom||df||= n-1||=COUNT(data)-1|
|Find a tc value from a confidence level c and sample size n||tc||=TINV(1-c;n-1)|
|Calculate an error tolerance E of a mean for any n ≥ 5 using sx.||E||=tc*sx/SQRT(n)|
|Calculate a confidence interval for a population mean µ from the sample mean x and error tolerance E:||x-E ≤ µ ≤ x+E|