Practical Skills in BiologyExperimental Design SkillsPractical SkillsPresentationInterpretation and EvaluationCommunication

Experimental skills are examinable in the final examination

Consult the syllabus (handout given out)

HYPOTHESISThe starting point of any experiment – want to find out something.An idea which experiments are designed to testA testable statement (cause and effect)A statement that connects the independent and dependent variable

e.g. 1. Light intensity will affect the growth of plants

2. An increase in temperature will affect the rate of enzyme action

Independent VariableAlso referred to as the experimental variableThe variable which is deliberately changedShould be plotted on x-axis of a graph

e.g. light intensity, temperature

Dependent VariableThe variable which may change as a result of changes to the independent variablePlotted on y-axis of the graph

e.g. growth rate, rate of enzyme action

Fair TestingFactors to be held constantAll factors that are kept the same during an experimentAn experiment can only have one independent variable.All other variables must be kept the same, this ensures a fair testEnables fair comparisone.g. light, temperature, amount, source, pH, concentration of enzymes etc

ControlA control is an additional experimental trial or run. It is a separate experiment, done exactly like the others. The only difference is that no experimental variables are changed. A control is a neutral "reference point" for comparison that allows you to see what changing a variable does by comparing it to not changing anything.

ResolutionResolution is the smallest increment measurable by an instrumentResolution is a property of the measuring instrumentIt is determined by the number of digits from the measuring instrument (this should match the number of significant figures you use in your data)Resolution relates to individual measurements

e.g. high resolution = 0.001g (electronic balance)Low resolution = 1.0g (kitchen scale)

Presentation of ResultsAll observations and measurements need to be recordedConstruct tables with headings and appropriate unitsDraw graphs with a title which clearly connects the independent and dependent variablese.g. “The effect of varying enzyme concentration on the rate of respiration”Describe the results, do not explain them.e.g as the enzyme concentration increased from 20 mM to 50 mM the rate of respiration increased. Concentrations above 55 mM resulted in a decreased rate of respiration”.

TablesEnzyme Concentration (mM)

Rate of Respiration (mLs-1)

5

10

15

20

45

50

55

0

12

24

32.9

42

45

0

Note headings and units for the table

Which piece of data isinconsistent?Why?

Drawing GraphsAxes labelled with units and appropriate title

An appropriate scale (uniform/use most of the axis

Accurate plot of points

Line of best fit

GraphThe effect of varying enzyme concentration on the rate of

respiration

-10

0

10

20

30

40

50

60

5 10 15 20 45 50 55

Enzyme Concentration (mM)

Ra

te o

f R

es

pir

ati

on

(m

Ls

-1) Series1

Linear (Series1)

Log. (Series1)

Average results werePlotted

Note choice of axes,Scales, and units

Which is the most appropriate line?

10 20 30 40

Random ErrorsRandom errors are caused by any factor that randomly affects the measurement variableThe amount of random error is indicated by the amount of scatter in the dataAn increase in sample size allows averages to be calculated- this reduces the effect of random errorsMeasurements are never perfect- therefore random errors are always presente.g. inconsistent reading of scales/use of timer

Systematic ErrorsSystematic errors are present when measured values consistently differ from their true valueUsually due to faulty apparatus/equipment or experimental designTend to be consistent throughout practical so an average does not rectify the problem.However repeating experiment may identify a systematic error (need to use other equipment)Consistent results indicate the conclusion(s) drawn are likely to be validBalance not calibrated, contaminant in a solution

Sample SizeThe number of samples in the experimental groupIncreasing the number of samples allows averages to be calculatedReduce the effect of random errorsData will be more consistent and reliablei.e. for each concentration of enzyme you may do replicates of 3.

ReliabilityRefers to the extent which an experiment yields the same result on repeated trails under the same conditions Achieve reliability by minimising random errorsUse large number of samplesBe careful with measurements during the practical

To repeat or not to repeat?Repeating the experiment with same procedure and apparatus at different times helps to identify systematic errorsRepeat experiment to validate the results, experimental design and be confident in our conclusionsUseful to repeat with different equipment, solutions etc… Are the results still the same?

ValidityRefers to the degree to which an assessment method measures what it is supposed to measure.It is increased by:

1. appropriate experimental design (testing what it is meant to

test)2. repeating the experiment

Precision and Accuracy

Low precision,high accuracy (fluke)

Low precision,low accuracy

Low precision,high accuracy (fluke)

Low precision,low accuracy

High precision,low accuracy

High precision, high accuracy

PrecisionPrecision depends on how well random errors are minimisedRandom errors are present when there is scatter in the measured values

High scatter = low precisionLow scatter = high precision

AccuracyRefers to how close the result of the experiment is to the true value

Systematic errors need to be detected if the result is to be accurate

Detected by repeating experiment

Precise or Accurate? Student A Student B

4.3 4.55.0 4.64.9 4.64.4 4.54.7 4.5

Mean 4.6 4.5

Resolution and Precision

The resolution of the stopwatch is 0.01s but the precision of the data does not match this.

Distance (cm)

time (s) mean (s) range(s)

40 0.9 0.98 0.93 0.95 0.94 0.08

80 1.25 1.29 1.27 1.21 1.26 0.08

119.5 1.54 1.54 1.44 1.41 1.48 0.13

Resolution and Precision

The resolution of the stopwatch is now 0.1s

Distance (cm)

time (s) mean (s) range(s)

40 0.9 1 0.9 1 1 0.1

80 1.3 1.3 1.3 1.2 1.3 0.1

119.5 1.5 1.5 1.4 1.4 1.5 0.1

Interpretation of Data (Discussion)Written in the third person (stated objectively)Inferences can be made when interpreting the dataAn inference is a reasoning based on observation and experience. To infer is to arrive at a decision or opinion by reasoning from known factse.g. “an increase in enzyme concentration influenced the rate of respiration as more enzyme was available for the reaction.”

Analysis and Evaluation of the ExperimentIdentify sources and distinguish between random and systematic errorsList ways to improve procedures of the experiment (possibly give reasons why)Comment on suitability and importance of the sample sizeComment on the accuracy and precision of the experimentComment on the value of repeating the experiment

ConclusionA brief statement that relates to the hypothesisShould be written at the end of each experimentSupports or refutes the hypothesisExperiments do not prove the hypothesisConfidence in the conclusions will depend on the validity (design) of your experiment and the care in execution.e.g. “this experiment indicates that enzyme concentration does have an affect on the rate of respiration” or “no conclusion can be drawn from tis experiment due to the large number of uncontrolled factors”

Other things to consider..In the Materials and Methods, list the materials/equipment you actually used, and the method you used. It needs enough detail so that someone else could repeat exactly what you did. (Especially in a Design Practical)Write in Past Tense (Impersonal) Drawings may be used in the Results sectionIntroduction- a brief review of the theory, state the aim and hypothesis of experiment.

HAPPY EXPERIMENTING AND WRITING