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Polygenic Experiment

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Introduction: The purpose of this experiment was to investigate:
1) How student height varies and
2) Whether human height is a sexually dimorphic trait.

Sexual dimorphism is where the two sexes of the same species show different characteristics other than the differences in their reproductive organs. Sexual dimorphism takes place in many animals, birds, insects and plants. The main differences include secondary sex characteristics, size (height and weight), color, markings, and sometimes behavioral differences. These differences vary and may be subtle or obvious, however most differing characteristics will conform to a bell-curve distribution which can be described by the mean/average and standard deviation. Obvious size differences may occur …show more content…

skin colour is a polygenic trait which is controlled by at least 3 genes as discussed in Cambell Biology. However polygenic traits are often influence by environmental factors. i.e. in warmer, sunnier climates skin colour tends to be darker due to the suns uv rays. The more genes that contribute to a trait the greater the variation. Height is a polygenic trait in humans which accounts for the huge variation among the human population. Diet and health also play a huge role in the expression of height among people. Nilsson Ehle discovered polygenic traits through his wheat …show more content…

There were no extreme outliers in this set of data. I processed this data using excel. Here I could determine all the descriptive statistics and compare the male and female population separately and all together. I displayed my data in table form and in graph form so that I could see that height had a bell curve normal distribution. I also could display both male and female heights on one graph but make them distinguishable by means of colour to get a direct comparison making it easier to distinguish whether height is a dimorphic trait.
Unfortunately, I don’t believe that this data set is a good representation of the population as a whole. This is because everybody in the sample is of similar age (17-20 with the exception of mature students) all of whom study a science based course. Therefore the sample is not random enough and may be considered bias. Secondly the sample size is too small for it to represent a whole population. For more accurate representations of data at least 1000 heights from people of different ages and different occupations should be

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