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I have decided to collect my data in Cambridge using two accurate instruments, a digital thermometer and a digital hygrometer. These will provide me with accurate samples of the temperature and humidity at the different survey points. I also believe that the height of the buildings (i.e. 1 story, 2 story …etc) and the type of land (grass, concrete … etc) will affect at least one of the 2 probables in my data. I suspect that collecting more than 2 sets of data will give me a wide range of things to discuss. As well as this I believe having this wide range of data may help to explain any anomalies that may occur.

The sixty survey points I am going to collect data from will be decided for me when I go on my geography trip. This is not an ideal situation however these survey points are wide ranged and have a variety of different surroundings so they should give me a wide range of results. The theoretical ideal situation would be to use a random number generator which would give 60 points on a map creating a sample which was random. However this would result in a problem as the random generator would quite often give me a co-ordinate that is inaccessible. Even though my data is not random I am collecting primary data.

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I believe collecting data from different heights will change the temperature as well as the humidity so I will record at different heights around Cambridge; this is because every 10 metres climbed the temperature drops by 1%. Pedestrian density may also affect the results due to respiration; this will make the data more biased. Cars will also affect the humidity and temperature; this will also cause a problem as the more densely populated area will have a higher temperature and humidity compared to the other survey points.

I will try to take the readings at as simultaneously as possible. I will use a digital thermometer which is accurate to 0.1%, and a digital hygrometer which is accurate to every 1%. All data will also be collected in the shade so the equipment will not be in direct sunlight. After I have collected my primary data I will collect secondary data to further test my hypothesis.I believe that the data spread has no correlation as my primary data is a much more localised resource; this means that the data is not averaged so it is much more precise.


I have decided not to do a whisker and box plot for my secondary data or indeed to compare the box plots with my earlier ones as they are based in different seasons, this would have no use at all except to find the spread of humidity and temperature which I have already worked out from the stem and leaf diagram.(as shown on page 14) SCATTER GRAPH (combined data) I have combined my primary and secondary data into one scatter graph. The hottest temperatures out of all the data have the lowest humidity and the lowest temperatures have the highest humidity.

The primary data is encircled.  The secondary data is surrounded by a square. The complete combined data when put together create a coefficient correlation of -0.9553. The samples in this study are small (based in one country at only 2 separate days during the year) however there appears to be a close correlation between temperature and humidity. If I was to study this further I would want take samples all around the globes at separate times during the year. However from the data presented in this paper it would appear that the original hypothesis holds true.

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