module 1

I/AM where I is image size A is actual size and M is magnification

the factor by which the rate of reaction increases for every 10 degrees rise in temperature (celcius or kelvin - units must match) there are no units 10/(T2-T1) Q10 = R2 R1 were R is rate and T is temperature usually between 2-3

SA is 4pi r^2 V is 4/3 pi r^3

Used in chromatography to indicate how polar a molecule is. it is the distance moved by compound/distance moved by solvent we can compare the Rf value to a known table of values in order to identify the unknown

the stroke volume x heart rate stroke volume is the volume of blood pumped out of the left ventricle with each systolic contraction

circumference of a circle

area of a circle

biomass transferred/ biomass intake x100

the respiratory quotient carbon dioxide exhaled / oxygen inhaled

number of polymorphic gene loci/ total number of loci

number of readings x uncertainty of the scale / reading x100 where the uncertainty of the scale is half of the smallest interval increase the resolution (use more precise equipment with smaller intervals) use a greater amount of something

random error - this is when the results are not likely to be reliable as the don’t have high resolution (they are not close together/ round the mean) the best way to deal with this is to reduce the effects by completing more readings so it has a higher repeatability and reduces the chance of anomalies. systematic error - this is usually due to equipment not working and can lead to results repeatedly occurring in predictable ways. this can be reduced by recalibrating the equipment

one decimal place greater then the raw score. if you do anymore you will lose the mark for inappropraite use of dp

• when you have two dependent variables (measured) ie height and weight. involves using a spearman’s rank in order to test whether there is a correlation between them • represent continuous data when there is no independent or dependent variable ie women’s height in inches . the bars should touch. • discontinuous data is presented on a bar chart where the lines do not touch. ie the percent of populations blood types • continuous data independent variable is on the x axis and the dependent variable is on the y axis.

it tells you have spread out the data is around the mean a small value indicates that the values are close to the mean so your results are precise and has high repeatability if SD is high then the results have low repeatability, the values are not around the mean so results are less precise it can be shown on a graph using error bars. the greater the overlap in error bars between two sets of data, the less confident you can be in the overall trend - as many of the same values are present in both data sets. a small overlap is more confidence in your results as fewer datasets are being sharing results values.

it should be used when your trying to measure the difference between an observed value and the expected results. a null hypothesis should be used stating that there is no significance between an observed or expected results

unpaired - when comparing the means of two different unrelated groups under different scenarios ie mean leaf length of group of plants in shade and in sun. paired - when comparing the mean of the same group in the two different scenarios ie the effect of drug on one group of people before and after

when you want to compare two sets of data and whether they are significant to each other - ie comparing the means. a null hypothesis is needed which assumes that there is no significant difference between the means.

this would be a spearmans rank test to test for a positive or a negative correlation between two dependent variables. it will only tell you IF there is a correlation - it will not tell you what is causing the relationship.