Investigating variation

• variation is the differences that exist between individuals. There is variation between species and within species
• Variation can be caused by genetic factors. Different species have different genes, which causes variation between species

  individuals of the same species have the same genes, but different alleles (versions of genes) - this causes variation within a species
• variation within a species can also be caused by differences in the environment e.g. climate, food, lifestyle
• most variation within a species is caused by a combination of genetic and environmental factors e.g. genes determine how tall an organism can grow, but nutrient availability affects how tall the organism actually grows
• Random sampling: bc sample data will be used to draw conclusions about the whole population, it is important that it accurately represents the whole population and that any patterns observed are tested to make sure they're not due to chance
• To make sure the sample isn't biased, it should be random

  e.g. if you were looking at plant species in a field you could pick random sample sites by dividing the field into a grid and using a random number generator to select coordinates
• To ensure any variation observed in the sample isn't due to chance it's important to analyse the results statistically

  This allows you to become more confident that the results are true and therefore will reflect what's going on in the whole population
• You can use the mean and standard deviation to measure how much variation there is in a sample
• the mean is an average of the values collected in a sample
• the standard deviation tells you how much the values in a single sample vary. It is a measure of the spread of values about the mean
• standard deviation is one method of calculating the dispersion of data. Another method of calculating dispersion is by looking at the range
• the range is simply the difference between the highest and lowest figures in the data
• standard deviation is more useful than the range because it takes into account all the values in the data set, whereas the range only uses 2. This makes the range more likely to be affected by an anomalous result than standard deviation
• standard deviations can be plotted on a graph or chart of mean values using error bars. Error bars extend one standard deviation above and one standard deviation below the mean (so the total length of an error bar is twice the standard deviation). The longer the bar, the large the standard deviation and the more spread out the sample data is from the mean