Biology Practical Skills

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  • Created by: Victoria
  • Created on: 06-04-14 22:16
Independent variable
The factor you changed - goes in the first column - on the x (horizontal) axis
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A separate table should be used
to show processing
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Plot mean or rate
on the y axis
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Rules for plotting a line graph
Join points with a ruler unless intermediate points can be predicted with confidence. If you plot a line of best fit there should be the same number of points on either side of the line. Do not extrapolate. Start on first point and finish on last
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Purpose of Water Baths
Maintain a constant temperature of all solutions - solutions are placed in a water bath and left to equilibrate
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Equilibration times vary
based upon volumes of solutions and the difference between starting and target temperatures - leaving solutions for a set time may not be long enough
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Water bath and solution temperatures can be monitored by
placing a thermometer into the liquids
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Room temperature water baths could just be
beakers of water - water temperature changes more slowly than air temperature so fluctuates less
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How often do you monitor water bath temperatures and what do you do to maintain the correct temperature?
Regularly - every two minutes. Add hot or cold water to adjust the temperature quickly and stir to ensure the temperature near the test tubes is the same as the temperature near the thermometer
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Why must temperature be controlled?
It affects enzyme action - Ideally temperatures should be kept around the optimum for enzyme action: 35-40*C
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Define: Optimum temperature / pH
The temperature / pH at which an enzyme / reactions work fastest / best
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Buffer solutions
Maintain a constant pH - changes in pH can affect enzyme action
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Show that the factor being tested is responsible for the observed effect. All factors bar the one being tested are kept the same but the test factor is omitted or replaced with a harmless/inactive alternate e.g. boiled enzymes & placebos
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Allow the calculation of a more reliable mean. Allow you to identify anomalies and reduces the effect of anomalies
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Being as close to the theoretical 'correct' value. Accuracy can be increased by using a measuring device with smaller divisions e.g. mm rather than cm
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Increasing measuring time
Increases accuracy: if measuring times = short the error caused by reaction times forms a large proportion of the total time. Recording stopwatch times to more decimal places does not increase accuracy-human reaction time > more timer precision
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Standard deviation
Shows the spread from the mean, takes all data into account - not just the extremes. Reduces the effect of anomalous data. Can be shown as standard deviation bars on a graph or as a +/- sign after a mean
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If standard deviations overlap
There is no significant difference between the data
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A large standard deviation
Indicates results show a lot of variation / the results are not very reliable
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Calculating Means
Add up all the values and divide by how many there are. Mean should have same number of decimal places as the individual results
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Calculating Rate of reaction
1 / time in seconds for a timed single process e.g. time taken for solution to change colour. Distance / time e.g. distance moved by an air bubble in a capillary tube. Volume / time e.g. the amount of oxygen released from OH in 3 minutes
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Calculating percentage
Final value / (start value x100) - usually small / large x100. Useful when there are different numbers of people/test tubes in experimental groups as percentage gives you a relative proportion for each group
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Calculating Percentage change
(Difference between values/ Starting value) x100. Useful when comparing data where start values are different, it shows a proportional change.
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Calculating ratio
Divide one number by the other (usually large/small)
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Calculating Magnification
Image size / actual size
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Calculating dilutions
Calculate how many times smaller the dilution is than the stock solution. Make the required volume the same number of times smaller, and remove this from the stock solution. Make up the remainder of the required volume using water.
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Describing trends
Most data will show a change in gradient, make sure you emphasise the change in gradient so you have described the pattern fully. Use values from the table/graph to show where the change in gradient occurs
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Evaluating data - often using case studies of drug trials
Make sure your answer shows a balanced argument. Is the sample size large enough to be representative/reliable/identify anomalies? Does the trend support the conclusion? Correlation not causation. Is data incomplete? e.g. one gender
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Peer reviews
check validity of a method / data analysis / conclusions / bias. Check that the experimental data/ results can be reproduced.
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Other cards in this set

Card 2


A separate table should be used


to show processing

Card 3


Plot mean or rate


Preview of the front of card 3

Card 4


Rules for plotting a line graph


Preview of the front of card 4

Card 5


Purpose of Water Baths


Preview of the front of card 5
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