unit 5 practical Flashcards
1
Q
independent variable definition
A
the variable for which the values are selected by the investigator
2
Q
dependent variable definition
A
the variable for which the values change when the independent variable is changed
3
Q
controlled variable definition
A
a variable which may affect the outcome of the investigation and therefore should be kept constant
4
Q
range definition
A
the maximum and minimum values of the independent or dependent variables. this shouldnt be too big or too small
5
Q
valid conclusion definition
A
a conclusion supported by valid data, obtained from an appropriate experimental design and based on sound reasoning
6
Q
validity of experimental design definition
A
- suitability of investigative procedure to answer the question being asked.
- strategies to ensure validity include fair test and controls that aim to isolate the effect of the independent variable on the dependent variable
7
Q
resolution definition
A
this is the smallest change in the quantity being measured by a measuring instrument that can be observed
- e.g +/- 1mm on a 1m ruler
8
Q
anomaly definition
A
value in a set of results which is judged not to be part of the inherent variation
9
Q
true value definition
A
this is the value that would be obtained in an ideal measurement
10
Q
uncertainty definition
A
the interval within which the true value can be expected to lie
e.g the temperature is 20°C +/- °C
11
Q
measurement error definition
A
the difference between a measured value and the true value
12
Q
systematic error definition
A
- these cause readings to differ from the true value by a consistent amount each time a measurement is made
- systematic errors can include the influence of the environment, the methods of observation or the instruments used
- the effect of systematic errors cannot be reduced by increasing repeats
13
Q
random error definition
A
- these occur due to results varying in an unpredictable way from one measurement to the next
- the effect of random errors can be reduced by taking more measurements and calculating a mean
14
Q
accuracy definition
A
a measurement result is considered accurate if it is judged to be close to the true value
15
Q
precision definition
A
- this shows the closeness of agreement between measured values
- it gives no indication of how close results are to the true value
16
Q
repeatability definition
A
the precision obtained when repeat readings are obtained by a single learner/group
17
Q
repeatable definition
A
- a measurement is repeatable, if repetition by a single learner/group using same method and equipment, obtains the same or similar results
18
Q
reproducability definition
A
the precision obtained when repeat readings are obtained by a different learner/group
19
Q
reproducible definition
A
- a measurement is reproducible if repetition by different learners/groups obtains the same or similar results
- this could include using different equipment/methods
- this is a harder test of the quality of data
20
Q
hazard definition
A
- a chemical or piece of apparatus that could cause harm
- it is expected that in risk assessments the nature of the hazard is also specified
21
Q
risk definition
A
an action involving a hazard that might result in danger
22
Q
control measures definition
A
something that can be done to reduce or prevent a risk while allowing you to carry out the experiment
23
Q
what are the 3 types of specified practical work in the spec?
A
- investigative work
- microscopy
- dissection
24
Q
in an experimental design, you should be able to:
A
- identify the independent variable - the factor that tests/changes
- identify the dependent variable - the factor that you are measuring
- identify the controlled variables - the factors that you need to keep constant
- use the correct units for all your variables
- identify a suitable range for your independent variable, this would normally be at least five values
- explain why repeat readings would be needed - a mean is more reliable than an individual reading and it will help identify anomalous results
- design a suitable control experiment
- assess the main risks of your experiment
25
your table of results should have:
- correct column headings
- appropriate units in headings (not in body of table)
- columns for sufficient repeats
- appropriate recording of readings, time to the nearest second, same number of decimal places throughout table except 0
26
your graph should have:
- the independent variable plotted on the x-axis
- the dependent variable plotted on the y axis
- the axes labelled correctly
- used at least half of the grid on both axes
- the correct units on both axes
- a suitable linear scale used on each axis, including a figure at the origin for both axes
- all plots accurately plotted
- the points accurately joined with a suitable line with no extrapolation. point to point using a ruler through centres is advised for most graphs
- range bars correctly drawn
27
analysis of results should be able to:
- identify a trend in the results
- comment on the consistency of the readings
- comment on the accuracy of the readings
- suggest improvements for any inaccuracies identified
- give an explanation of results using relevant and sound biological knowledge
- draw a suitable valid conclusion
28
magnification equation
magnification = image size / actual size
29
cm x 10 = mm
mm x 1000 = µm
µm x 1000 = nm
30
light microscope vs electron microscope
light vs electron
- beams of light vs beams of electrons
- longer wavelength vs shorter wavelength
- small vs large and non portable
- relatively inexpensive vs expensive
- not lot of training required to use vs training required
- see colour images vs black and white
- specimens can be alive and unharmed vs specimens must be dad
- lower resolving power vs greater resolution
- lower magnification vs greater magnification
31
because electron microscopes use beams of electrons rather than light, they can:
- produce images at higher magnification
- produce images which are clearer and with greater detail - they have greater reolution
32
- in both light and electron microscopes, staining is used to give more contrast between cell structures and make them easier to see
- but, staining kills cells so cannot be used when observing live cells
33
to calibrate the microscope:
- line up the zero of the eyepiece graticule and the zero of the stage micrometer
- make sure the lines are parallel
- look at the scales and see where they are in line again
- 1 eye piece unit = e.g 20/80 =0.0342 g 0.25 stage micrometer units
- 1 stage micrometer unit = 0.01mm
- 1 eye piece unit = 0.25 x 0.01mm
= 0.0025mm
= 2.5 µm
34
when completing low power plans (shows distribution of tissues in transverse/longitudinal section of structure) you should:
- use a sharp pencil
- not use any shading
- not draw any individual calls
- make your drawing at least half a page of A4 in size and position the labels to the side of your drawing
- make all lines clear, complete and not overlapping
- draw label lines with a ruler to the centre of the tissue layer, they should not cross each other
- ensure tissue layers are all drawn to the correct proportion
- draw a line across two tissues to give the width of this line in eyepiece units
35
some core maths skills needed in biology:
- recognise and use appropriate units in calculations
- convert between units
- use an appropriate number of decimal places in calculations
- significant figures
- standard form
- ratios, fractions and percentages
- calculate surface areas and volumes
- plotting and using information from graphs
36
1cm^2 = 100 mm^2
1 mm^2 = 1,000,000 µm^2 (1000x1000)
1 µm^2 = 1,000,000 nm^2
37
1 cm^3 = 1000mm^3 (10x10x10)
1mm^3 = 1,000,000,000 µm^3 (1000x1000x1000)
1µm^3 = 1,000,000,000 nm^3
38
significant figures rules:
- non-zero digits are always significant
- any zeros between two significant digits are significant
- a final zero or trailing zeros in the decimal portion ONLY are significant e.v 0.10050 = 5sf
- numbers must be rounded correctly
39
statistics and probablility:
- students need to understand the terms mean, median and mode as measures of dispersion
- they also need to understand how to calculate standard deviation and how to interpret standard deviation from a mean value
- in this context they also need to understand what is meant by normal distribution
- simple probability needs to be understood as a fraction or proportion of 1 but could also be expressed as percentage change e.g. allele frequencies, phenotype and genotype ratios
- they need to be able to assess the significance of differences between sets of data that show:
• continuous, normal distribution = student’s T test
• discontinuous distribution = Chi^2 test
- they need to apply their understanding of probability to interpreting the results of statistical tests of significance
40
something is not a normal distibution if:
- mean, mode and median are not the same
- distribution is not symmetrical around the mean
41
standard deviations show:
- variation from the mean / provide information about the reliability of the mean
42
a t-test would be used when you are:
- testing significance of differences in between the means of two sets of continuous / normally distributed data
- when have no expected values only observed data
(chi^2 used to test the significance of differences in discontinuous data for which you can calculate expected values)
43
logarithms:
- candidates need to understand when applicable to use values expressed as log10
• numbers increase on an order of magnitude scale i.e 10, 100, 1000
• numbers are very large or very small
- they need to be able to calculate log10 value from a given number or an actual number given the log10 value to the number
• log10 of a number is the power that 10 is raised by to produce that number
• that 10 raised to the power equal to the log10 value for that number gives the original number
• i.e if 100 = 10^2, then log10[100] = 2 and 10^2 =100 100
- read log values from a graph realising that e.g log10[10^3] = 3
44
if dependent variable time:
rate = 1 / time
OR
if dependent variable a quantity;
rate = quantity / time
45
calculating rate from data:
- the shorter the time, the higher the rate
- then apply your knowledge of the effect of pH/temperature to explain lower or higher rates
- then optimum pH/temperature is given by the shortest time/highest rates
- BUT:
- if the time/rate at two values of the independent variable are close, then the optimum is likely to be between these values
• can improve by investigating values of the IV between these two values
- if the shortest time or fastest rate is at the highest or lowest value of the independent variable, then you don’t know what would happen at values of the IV higher or lower than this
• can improve by extending the range of the IV
- if there is a large difference between two values of the independent variable, then the same points apply - you don’t know what is happening between those points so we need to investigate a range of values between them
46
how to improve reliability?
- repeat experiment
47
how to improve accuracy?
- e.g measure at smaller intervals
