The thesis is about seeing if there is any correlation between temperature deviation and selected variables to increase the understanding of what affects the camera. The work is an improvement method where R programs are used for mathematical solutions. 

The methods used for this include data collection and scientific research. Based on the collected input data, the result could be obtained using these methods. An additional method was to connect two or more substances such as statistics and programming in a work where prior knowledge is used, the result is verified and the acquisition of knowledge continues. 

The purpose was to use prior knowledge and software to see if there is any connection between input data that is on company’s database. The correlation between different variables is something that is used daily in society, industry and the international conventions. The correlation between two variables shows the extent to which they are related. 

The result was obtained in the form of calculations, graphs and tables. There are indications that there is a weak correlation between camera angle and temperature deviation while there is a mean correlation between position and temperature deviation. There is a very weak correlation between holding times and temperature deviation, something that needs to be verified with several measuring points. 

There are no definite results due to various factors such as the number of measuring points, although there are some indications that all camera angles except 25 ̊ can be a solution by performing several number of measuring points at both angles. The indication is largest for position in the camera's field of view. As for holding time, there is an indication that it does not affect the camera, but more measurements are needed to verify that indication. 

The spread is also interesting. If the distribution is reasonably equal in the different cases, the position of the temperature deviation can always be adjusted with the aid of the emissivity.