practical Flashcards
(25 cards)
sources of error
systematic or random
systematic errors
- don’t differ throughout investigation
built in errors in measuring equipments
due to limitations in reading scales
due to lack of accuracy+precision of measuring instruments
may not affect trend in results
random errors (uncontrolled variables, subjectivity in perception) affects trends
due to difficulties controlling standardised variables
due to difficulty measuring dependent variables
differ throughout investigation
e.g. maintaining steady water bath temperature, difficulty judging colour, difficulty counting bubbles
examples of improvements
- thermostatic controlled water bath instead of beaker and bunsen burner
- repeat exp at least 3 times to improve reliability
- use graduated pipette instead of syringe
- colourimeter instead of judging end point with naked eyes
- buffer maintain pH
- use equal volumes
- materials from same sources
- slow motion camera used for bubble counting
- micropipette instead of syringe
justify suggested improvements
- will increase accuracy of results so improve confidence in data
size of uncertainty error
half the value of the smallest division on the measuring scale
total error
sum of the errors for each reading
If your recorded result involves measuring two values – for example, if you have measured a starting temperature and then another temperature at the end, and have calculated the rise
in temperature – then this error could have occurred for both readings.
Your final value for the change of temperature you have measured would then be written: 18.0°C + 1.0°C.
control measures
- pH
- temp
- light intensity
- humidity
- biological materials
- buffer
- use of thermostatically controlled water bath, heater/air conditioner/incubator
- same watts lamp at same distance
- hygrometer
- from same organism
identify the concentration of a reducing sugar by use of
semi-quantitative benedict’s test
- make serial dilution of glucose
- test diff concentrations of glucose with Benedict’s solution
- make colour chart
- use colour chart to estimate concentration of reducing sugar in unknown solution
- use colourimeter to increase sensitivity of reducing sugar test
accuracy
closeness to true value- better insturments
precision
closeness to repeated readings- control all variables
reliability
confidence in results- repeat readings+take mean
validity
agreement between hypothesis and investigation- check relation between key+derived variables
benedicts test (procedure)
incl if non-reducing
2cm^3 benedicts + 2cm^3 glucose -> heat to 90°C
2cm^3 HCL + 2cm^3 sucrose + heat at 90°C
neutralise with NaOH
2cm^3 benedicts + 2cm^3 glucose -> heat to 90°C
explanation of benedicts
reducing sugar reduces Cu2+ to Cu+ (forms a precipitate)
explanation of benedicts non-reducing sugar rest
acid hydrolyses the non-reducing sugar into reducing sugar
which reduces Cu2+ to Cu+
benedict’s results colours of intensity
blue -> green -> yellow -> orange -> brown -> brick red
iodine test + exp
add few drops iodine solution into starch solution
starch+iodine form a complex
biuret test
2cm^3 biuret+2cm^3 albumin?
biuret exp
N atoms in peptide bonds+Cu2+ form peptide complex
emulsion test
1 drop of oil + 5cm^3 ethanol -> shake
then fill test tube with distilled water
emulsion test exp
lipid insoluble in water but soluble in alcohol
why do we repeat experimental procedure
improve ACCURACY of results
With reference to your estimate in (a)(vii), suggest how you would modify this procedure
to obtain a more accurate value for the concentration of protease in fruit extract U
- use more concentrations with narrower intervals
- states concentrations both sides of the estimate
