Locate Dataset, Variable, and Station 
 Select the "Datasets by Catagory" link in the blue banner on the Data Library page.
 Click on the "Atmosphere" link.
 Select the
NOAA NCDC GDCN dataset.
 Click on the "searches" link to the right of the map.
 In the Name text box under the Searches subheading, enter Sherbrooke.
 Click the Search NOAA NCDC GDCN button.
 Click on the number "7028120", the first entry that appears below the search text box.
CHECK
You have selected the station identification number for Sherbrooke. To get
general information on finding station ID's, click the following link
to the tutorial: How
to Find A Station ID
 Scroll down the page and select the "Min Temperature" link under the Datasets and Variables subheading. CHECK

Select Temporal Domain 
 Click on the "Data Selection" link in the function bar.
 Enter the text 1 Jan 1920 to 1 Jan 1970 in the Time text box.
 Press the Restrict Ranges button and then the Stop Selecting button.
CHECK

Compute Yearly Mean Minimum Temperature 
 Click on the "Expert Mode" link in the function bar.
 Enter the following line under the text already there:
T 365 boxAverage
 Press the OK button. CHECK
This command computes the mean minimum temperature for each year by taking a 365day average of the minimum daily temperature.
This is not an exact yearly average because every 4 years is a leap year, with one extra day.
Every four years, the 365day range will start one day earlier. This being ignored, we are still left with a good approximation of the mean minimum temperature per year.

View Yearly Mean Minimum Temperature Time Series 
 To see the result of this operation, choose the time series viewer. CHECK
Time Series of Average Minimum Temperature for Sherbrooke
A gradual upward trend is noticeable over the selected
time range. The increase in temperature may have been caused
by urbanization in the region surrounding the observing station. Has the
urbanization made a sufficient impact on the data so that it may no longer
be considered homogeneous over this time period?
To answer this question, it is necessary to analyze the distribution of the
data around the median.

Subtract Median From Dataset 
 Return to the dataset page by clicking on the rightmost link in the blue source bar at the top of the page. CHECK
 Enter into Expert Mode and type the following command under the text already there.
[T] 1 medianover
 Press the OK button. CHECK
The median should be located below the expert mode text box in bold: 0.8683567 degrees Celsius. Take note of this value.
The medianover function is further explained in the Measures of Central Tendency section.

In the source bar, click on the T 365 0.0 boxAverage link. CHECK
This will undo the medianover command.
 Click on the Expert Mode link in the function bar if the text box is not shown.
 In the Expert Mode text box, enter the following line under the text already there:
0.8683567 sub
 Press the OK button. CHECK
The above command subtracts the median (0.8683567° Celsius) from each value in the dataset.

Analyze Homogeneity of Data 
 Select the "Tables" link in the function bar.
 Read the licensing agreement and click the "I agree" button to continue.
 Select the columnar table link. CHECK
A table will appear with Time in one column and (Min Temp  0.8683567) in the other column. The day in the Time column changes every four years
because of the leap year issue mentioned earlier.
 Count how many times the data will make a run above or below the median.
For example, if the value in the right column remains negative for three years and then becomes positive in the fourth year, those three years would be considered one run.
If in the fifth year the value becomes negative again, then the fourth year is considered another separate run.
Homogeneity can be tested by noting how many runs were present in the sample compared to how many total elements were in the sample.

Use the significance table below to help decide whether the minimum temperature data at Sherbrooke is homogeneous.
The table lists the number of runs for a given number above (N_{A}) and below (N_{B}) the median.
For a 40 year series, for example, N_{A} = N_{B} = 20. If the number of runs falls between the .10 and .90 significance limits, there is a high probability that the data is homogeneous.
Other significance tables can be obtained for sample sizes not contained in the table.
N_{A }= N_{B}

.10 significance level

.90 significance level

10

8

13

11

9

14

12

9

16

13

10

17

14

11

18

15

12

19

16

13

20

17

14

21

18

15

22

19

16

23

20

16

25

25

22

30

30

26

36

35

31

41

40

35

47

45

40

52

50

45

57

Oliver, John E. Climatology: Selected Applications. p 7.
There are 18 runs in the Sherbrooke data from 1920 to 1970. The total number of elements that make up the sample is 50 (each yearly mean minimum temperature constitutes one element).
According to the table, at a .10 significance limit there should be at least 22 runs.
We can therefore conclude, with 90% confidence, that this data is not homogeneous. Is this inhomogeneity caused by a largescale climatic change or by an inconsistancy in the area surrounding the observing station?
To answer this question, we analyze the mean minimum temperature at another station only a few miles away.
