Probability Of Infection And Death Lab Report Sample

The aim of this experiment is to test the relationship of how the probability of infection affects the people in the village when it is increased or decreased. This will determine whether the people in the village die or not from the epidemic. As the probability of infection is increased, the more people in the village will die. This is because the villagers are more likely to contract the disease, putting them at a higher risk of dying to the epidemic. As an example more people will survive in the village if the probability of infection is 20% than 80%.
The raw results of the table show the correlation between the probability of infection and resulting deaths. An infection rate of 60% and 100% caused the least amounts of deaths. An infection
As the probability of infection was increased by a further 20%, 47±7 villagers died, a death increase of 6.8%. The infection rate was increased by a further 20% causing the death rate to decrease to 43±10 deaths (by 9.3%), the lowest amount of deaths that occurred. With an infection rate of 80%, the highest amount of deaths occurred, being 49±4 people died an increase of 14%. A 100% probability of infection caused 43±4 individuals to die, an decrease of 14%. This infection rate also tied with a 60% infection rate for the lowest number of deaths.

This graph shows the results from the probability of infection experiment and shows the relationship of have the infection rate, affects how many of the villagers die. Each probability shows a fairly equal average, with no real standouts. There is no clear pattern or trend within the graph, because there is mixed results.

From the results of the experiment an infection rate of 60% and 100% caused the least amount of deaths, with 43 occurring. An infection rate of 80% caused the most amount of deaths, with 49 dying from the disease. The probability of 20% of infection caused 44 people to die and a 40% chance of infection caused 47 people to die. These results did not conclusively support the hypothesis of that as the rate of infection is increased so is the death rate. There is no clear relationship between the increase of infection rate and the resulting
The dependent variable of this experiment is the death rate of the villagers caused by the epidemic and it is the dependent variable. This is because it is the variable that is being tested, and it is reliant on the probability of infection. The sample size of the experiment is 3, which means every different increase of probability of infection was tested three separate times. It is desirable to increase the sample size of an experiment, because it decreases the amount of random and systematic errors made. It also provides more reliable and more accurate results, because you are testing that probability more times.

During the experiment and the write up of this practical I believe that I managed to work collaboratively and successfully work individually. I was able to work collaboratively, by gaining help with my some of my fellow classmates, exchanging ideas and looking at their result. I also talked to my teacher Mr Dundon, who let me know what I had to do in some parts of this practical report. I was also able to work individually, by processing the information the simulation and putting the results of the simulation into words in a practical