Practical revision

1m= 1000mm 1mm= 1000 um 1um=1000nm

1m= 1000mm 1mm= 1000 cm 1mm=1000nm

1dm^3=10,000cm^3 1cm^3=1000mm^3

1dm^3=1000cm^3 1cm^3=1000mm^3

Seconds abbreviated to s Use minutes if no. seconds is so big human brain cannot grasp them

Seconds abbreviated to s Use minutes if seconds is more than 60

The factor you choose to change- you decide its values so they are fixed and do not depend on anything else that is going on- must say explicitly- the IV is... then must give a minimum of 5 values for it- 1 value can be 0- still a value- must state

A factor that occurs naturally, the values are not fixed, this allows use to see the effects of unique circumstances

This is what you plot on your graph- what you count or measure or what you calculate from your counts or measurements- DV depends on IV- when stating- must say units it's measured in- if it's rate of reaction= s^-1- graph has rate of reaction on y axis and always say rate never say time if this is the case

A variable that isn't the IV and is not controlled, affects all ppts- must state units it's measured in

A factor that affects some ppts in an experiment but not all, this can harm the validity of your study

In an experiment, the only thing you want to change to get readings is the IV- everything else is about your experiment stays the same so you have to control them. State units factor is kept at and how controlled variable is kept constant. When doing field work MUST say it's not possible to control the environment- so choose sites where environmental factors are as similar as you can get them - then measure to make sure of that- while unlikely to be as identical as lab conditions- similar enough so DV isn't significantly effected

Enzyme concentration Enzyme volume Substrate concentration Substrate volume Temperature pH

Enzyme concentration Enzyme volume Light intensity Substrate volume Size of the test tubes pH

Taking away the most significant element - then when you run the experiment you get no change in results- can see that the change in results (DV) is directly due to change of the IV- state exactly HOW you control- eg pepsin solution was boiled for 10 minutes to denature the enzyme and it was cooled before use

A control experiment is when the IV measurements are kept at equal intervals and the dependent variable has no outliers. ALSO- don't forget to say cool an enzyme before using it

Accuracy- consistency of the results in the experiment- accuracy of readings depends on accuracy of equipment- can think about this 2 ways- objective readings, subjective readings

Accuracy- how true your readings are- At Alevel assumed students know how to use apparatus is used correctly- so we can't blame human error- so accuracy of readings depends on accuracy of equipment- can think about this 2 ways- objective readings, subjective readings

Objective readings-Have an element of your personal judgement eg deciding when a solution has changed colour- people judge in different ways- limits accuracy of exp Subjective readings-are made when you read off a scale and anyone making the reading will get the same answer eg volume in a measuring cylinder, time on a stop clock

Objective readings- are made when you read off a scale and anyone making the reading will get the same answer eg volume in a measuring cylinder, time on a stop clock Subjective readings- Have an element of your personal judgement eg deciding when a solution has changed colour- people judge in different ways- limits accuracy of exp

When you complete an experiment using a different method and gain the same results

How close your repeat are to each other- replicability can also be used- but not often

Very small differences in set up or timing can alter the result- so we do repeats and calculate a mean result- more repeats= more reliable mean 3 is best number- if you have not done 3 explain why under table- sometimes teachers may provide results for repeats- be verry clear which results have been given to you

Very small differences in set up or timing can alter the result- so we do repeats and calculate a mean result- more repeats= more accurate mean

Reliability is about getting the same answer each each time- accuracy is about getting a true answer

In a reliable experiment the IV is not controlled, unlike an accurate experiment

The number of decimal places you use depends on how the apparatus is graduated- using a data logger- you can sensibly choose your own dp- if using a scale graduates in mm or seconds- round to nearest whole number. Using the mean from repeated results- you can use 1 more d.p than the results- but keep the same for each mean

The number of decimal places you use depends on how the apparatus is graduated- using a data logger- you can sensibly choose your own dp- if using a scale graduates in mm or seconds- round to 2dp. Using the mean from repeated results- you can use 1 more d.p than the results- but keep the same for each mean

Rate of hydrolysis of hydrogen peroxide by catalase= collect oxygen by displacement of water in inverted measuring cylinder or syringe Investigating rate of digestion of casein in milk by trypsin- how long it takes for milk to clear- can use colorimeter/ eyes Measuring rate of respiration in yeast- time indicator takes to decolorise

Rate of hydrolysis of hydrogen peroxide by catalase= collect oxygen by displacement of water in inverted measuring cylinder or syringe Investigating rate of digestion of casein in milk by trypsin-time indicator takes to decolorise Measuring rate of respiration in yeast- how long it takes for milk to clear- can use colorimeter/ eyes

Rate of hydrolysis of hydrogen peroxide by catalase= time indicator takes to decolorise Investigating rate of digestion of casein in milk by trypsin- how long it takes for milk to clear- can use colorimeter/ eyes Measuring rate of respiration in yeast- collect oxygen by displacement of water in inverted measuring cylinder or syringe

Measuring rate of photosynthesis of Elodea (pond weed)- - volume of oxygen produced by a given mass of elodea in a given time- volume (cm^3) collected is a measure of photosynthesis

Measuring rate of photosynthesis of Elodea (pond weed)- - volume of carbon dioxide produced by a given mass of elodea in a given time- volume (dm^3) collected is a measure of photosynthesis

If you’re calculating rate of reaction using a reciprocal (dividing 1 by a given quantity)- round to first dp that is not a 0

If you’re calculating rate of reaction using a reciprocal (dividing 1 by a given quantity)- may have zeroes after decimal point- acceptable to multiply all results eg x10^2- indicate what you’ve done in column headings

% increase= actual increase/ initial value x100 Actual increase= final value- initial value

% increase= actual increase/ initial value x1000 Actual increase= final value- initial value

When investigating the effect of temperature on the rate of an enzyme controlled reaction - you’ll plot a graph- theory tells us it should equal about 2- closer your calculated value is to 2- more accurate it is Draw line of best fit using only points where rate is increasing- read rate at 2 temperatures 10 degrees apart Q10= rate at (t+10) degrees C/ rate at t degrees C

When investigating the effect of temperature on the rate of an enzyme controlled reaction - you’ll plot a graph- theory tells us it should equal about 1- closer your calculated value is to 1- more accurate it is Draw line of best fit using only points where rate is increasing Q10= rate at (t+10) degrees F/ rate at t degrees F

Rf= Distance moved by x- distance moved by solvent front

Rf= distance moved by x/ distance moved by solvent front

Same principles of considering variables, accuracy and reliability apply- but are certain issues you need to think about due to being less able to control significant environmental factors- also because organisms show variation- one must interrogate data with statistical tests to properly understand what results mean

Same principles of considering variables, accuracy and reliability apply- no alterations needed

variables are controlled by selecting a random number of organisms from each species and placing them in a controlled environment- monitoring the controlled variables to ensure only the IV impacts the DV

In a lab exp- only want IV to change- but in field you can’t control the environment- so have to choose sites for exp that are as similar as possible in every way other than IV- then have to monitor most important factors to ensure they seem relatively stable between conditions

When experiment is along an environmental gradient you would use a belt transect- further you go along the transect= further along the gradient you are

The selection of individuals from a population which allows you to estimate the characteristics of the whole population When experiment is along an environmental gradient you would use a quadrant- closer to the edge of the quadrant- further you are along the gradient

1)Divide the area to be sampled into a grid using measuring tapes placed at right angles to each other. 2)Use random numbers to generate coordinates within the grid on which to place the quadrats. 3)Place a quadrat at each coordinate same corner of quadrat place at coordinate 4)Count the numbers/estimate percentage cover of each species in each quadrat. 5)Use a key to identify each species. 6)Record results in a table. Calculate the average of each species.

1)Divide the area to be sampled into a grid using measuring tapes placed at right angles to each other. 2) Decide on your own coordinates within the grid on which to place the quadrats. 3)Place a quadrat at each coordinate -different corner of quadrat place at coordinate 4)Count the numbers/estimate percentage cover of each species in each quadrat. 5)Use your own knowledge to identify each species. 6)Record results in a table. Calculate the average of each species.

- On tree trunks- draw on grid with marked pen - stream- griddled quadrat -% cover- large open quadrat % frequency of plants along belt transect - 0.5m point frame quadrat If you can't decide on area of quadrat- start with small quadrat- keep doubling area until counts of species don't increase along with the area- optimum - keep doing quadrats with running mean- each time you add quadrat do another mean value- as soon as you have 2 matching means in a row- do one more then done

- On tree trunks- grid printed onto acetate- bend around trunk and see through- greater accuracy - stream- solid, open frame quadrat -% cover- gridded quadrat= best % frequency of plants along belt transect - 0.5m point frame quadrat-frame shaped like a T. The bar of the T has ten holes in it, and to sample vegetation a long pin much like a knitting needle is stuck through each hole. The different plants that the pin ‘hits’ as it is pushed towards the ground are identified and counted. If you can't decide on area of quadrat- start with small quadrat- keep doubling area until counts of species don't increase along with the area- optimum - keep doing quadrats with running mean- each time you add quadrat do another mean value- as soon as you have 2 matching means in a row- do one more then done

%frequency=number of quadrats in which the species is found/ total number of quadrats ×100 Local frequency=total number of hits of a species total number of pindrops×100 Local composition=% frequency of a community/ % frequency of all communities×100

%frequency=total number of hits of a species/ total number of pindrops×100number of quadrats in which the species is found total number of quadrats ×100 Local frequency=number of quadrats in which the species is found total number of quadrats ×100 Local composition=% frequency of a community % frequency of all

In exp will be measuring effect of abiotic factor on animals or plants- measurements of abiotic factors eg soil pH, temperature= likely to be accurate- will be using properly calibrated equipment- biotic data will limit accuracy- can vary hugely depending on exp- potentially not count hidden organisms/ misidentify

W/ lab readings- have to take multiple readings and calculate a mean- in field can find mean for collective quadrat or block sample readings but along a transect only have 1 point at each distance- could put a quadrat at either side of line or depending on conditions- could lay 3 transects parallel and close to one another to calculate mean

Aquatic organisms- stings/ low body temperature, sunburn, misinterpreting organisms- all habitats

sunburn for whatever habitat, bites/ stings and trips/ falling branches- terrestrial habitat, Weil's disease from bacterium Leptospira- aquatic habitat- wear gloves- also drowning

Line graph- A line graph is used in the situation where both variables are quantitative (numerical) and continuous (any numerical value is possible, not just whole numbers); and to determine the nature of a causal link between an independent variable and a dependent variable -Points should be notated with a saltire cross or a dot- join up dots to show trends/ see anything important between readings Scatter graph- is a tool for analyzing relationships between two variables for determining how closely the two variables are related. One variable is plotted on the horizontal axis and the other is plotted on the vertical axis. The pattern of their intersecting points can graphically show relationship patterns. Bar chart-Bar charts are used to compare categories when you have at least one categorical or discrete variable12. Each bar represents a summary value for one discrete level, where longer bars indicate higher values. Kite diagram- show clearly the abundance and distribution of species along a transect - but no.s rounded so accuracy lost compared to table data

Line graph- is a tool for analyzing relationships between two variables for determining how closely the two variables are related. One variable is plotted on the horizontal axis and the other is plotted on the vertical axis. The pattern of their intersecting points can graphically show relationship patterns. Scatter graph- is used in the situation where both variables are quantitative (numerical) and continuous (any numerical value is possible, not just whole numbers); and to determine the nature of a causal link between an independent variable and a dependent variable -Points should be notated with a saltire cross or a dot- join up dots to show trends/ see anything important between readings Bar chart-Bar charts are used to compare categories when you have at least one categorical or discrete variable12. Each bar represents a summary value for one discrete level, where longer bars indicate higher values. Kite diagram- show clearly the abundance and distribution of species along a transect - but no.s rounded so accuracy lost compared to table data

All chi-squared tests are concerned with counts of things (frequencies) that you can put into categories. For example, you might be investigating flower colour and have counted the numbers (frequencies) of red flowers and white flowers (categories). The test looks at the frequencies you obtained when you counted them and compares them with the frequencies you might expect to get in order to determine whether the difference is significant or not- null hypothesis=“there is no significant difference between the observed and expected frequencies.” 3 requirements make it valid- each set of data= normally distributed- bell graph, have at least 15 samples of data, using raw data not manipulated data

check this-

g

h

Aim- To show the effect of temperature on rate of reaction of amylase digesting starch IV- Temperature DV- Rate of digestion- 1/ time taken to complete starch digestion s^-1 or min^-1 CV- Enzyme concentration 0.1g/100cm^3 or starch concentration 1.0g/100cm^3 Control- Boil potato discs in water for 10 mins- cool for experiment at each pH

Aim- To show the effect of temperature on rate of reaction of amylase digesting starch IV- pH DV- Rate of digestion- 1/ time taken to complete starch digestion s^-1 or min^-1 CV- Enzyme concentration 0.2g/100cm^3 or starch concentration 2.0g/100cm^3 Control- Freeze amylase for 10 mins- heat for experiment at each temperature

Aim- To show the effect of pH on the volume of oxygen produced releases carbon dioxide IV-enzyme concentration DV- Volume of oxygen produced in 5 minutes/cm^2 CV- Concentration of Catalase by having same no. potato discs- 30 discs/ Hydrogen peroxide concentration- 20 vol Control- Boil trypsin for 10 mins- cool for experiment at each temperature

Aim- To show the effect of pH on the volume of oxygen produced releases carbon dioxide IV- pH DV- Volume of oxygen produced in 5 minutes/cm^3 CV- Concentration of Catalase by having same no. potato discs- 30 discs/ Hydrogen peroxide concentration- 20 vol Control- Boil trypsin for 10 mins- cool for experiment at each temperature

Aim- To show the effect of casein concentration on the rate at which trypsin digests it IV-casein concentration provided by different concentrations of milk powder DV- Rate of digestion 1/ time for milk to change from white to clear min^-1 or s^-1 CV- Temperature/ Trypsin concentration= 0.5g/100cm^3 Control- Boil trypsin for 10 mins- cool for experiment at each temperature

Aim- To show the effect of casein concentration on the rate at which trypsin digests it IV-trypsin concentration provided by different concentrations of milk powder DV- time digestion takes 1/ time for milk to change from white to clear min^-1 or s^-1 CV- Temperature/ Trypsin concentration= 0.5g/100cm^3 Control- Boil trypsin for 1hr- cool for experiment at each temperature

IV-lactase concentration provided by different numbers of immobilised lactate balls DV- Concentration of sucrose /moldm^3 CV- Temperature/ amylase concentration= 4g/100cm^3 Control- Boil lipase for 10 mins- cool before making balls- perform experiment at each ball number

IV-lactase concentration provided by different numbers of immobilised lactate balls DV- Concentration of glucose /moldm^3 CV- Temperature/ milk concentration= 4g/100cm^3 Control- Boil lactase for 10 mins- cool before making balls- perform experiment at each ball number

- Must say what experiment is designed to find out- identify IV and DV eg To investigate the effect of potato disc on volume of oxygen produced by catalase in hydrogen peroxide breakdown if writing abt enzyme exp- use both names of enzyme and substrate in the name Aim needs to refer exactly to what's plotted on graph

- Must say what experimenter thinks will happen in an exp- identify IV and DV eg To investigate the effect of potato disc on volume of oxygen produced by catalase in hydrogen peroxide breakdown if writing abt enzyme exp- use both names of enzyme and substrate in the name Aim needs to refer exactly to what's plotted on graph

Must say what your experiment is designed to find out and identify the dependent variable and independent variables

A prediction links 2 variables with direction of the effect- need to say what you think might happen- predict a trend

If using hydrogen peroxide- state its concentration in units 'vol' - decomposes to give oxygen- more hydrogen peroxide- more oxygen produced-eg 1dm^3 vol= 1dm^3 oxygen Using % when describing solution= problem- can mean 2 different things- when diluting stock solution say 10% of a stock solution as 10% could also mean 10g per 100cm^3 In field- can't give 5 values when comparing habitats- say what 2 values are and give approx values if relevant

If using hydrogen peroxide- state its concentration in units dm^3 - decomposes to give oxygen- more hydrogen peroxide- more oxygen produced-eg 1dm^3= 1dm^3 oxygen Using % when describing solution= problem- can mean 2 different things- when diluting stock solution say 10% of a stock solution as 10% could also mean 10g per 100cm^3 In field- can't give 5 values when comparing habitats- state the difference between 2 habitats - never give a value

State you're repeating the readings for each value of dependent variable and more readings taken- more valid mean is- usually 2 readings= enough but if one reading= anomalous-- may take 3- discard outlier- need to explain why repeats are being taken- diminishes uncertainty in measurements/ increases confidence in conclusions from the data- spread around the mean- shows repeatability and so reliability- will be shown by a graph by range bars or standard deviation bars for field work

State you're repeating the readings for each value of independent variable and more readings taken- more reliable mean is- usually 3 readings= enough but if one reading= anomalous-- may take 4- discard outlier- need to explain why repeats are being taken- diminishes uncertainty in measurements/ increases confidence in conclusions from the data- spread around the mean- shows repeatability and so reliability- will be shown by a graph by range bars or standard deviation bars for field work

State any hazard you perceive in the experiment State why hazard is a danger State how you would prevent any risk of the hazard occurring

Identify hazard= item that might cause harm say why it's a hazard (risk= activity that might cause harm) say what you would do to minimise risk-control measure- must say what most significant hazard is

Hazard- Allergic reaction of skin in response to foreign protein- Risk= Dispensing enzyme solution- control- avoid skin contact and wash with soap and water if contact occurs Proximity of water and electricity could cause shock- risk= using an electric water bath- control- place water bath a distance from electric socket- take care not to splash water- immediately mop up any spilt liquid Cutting potato disks with sharp scalpel could cause cuts to the skin (catalase)- risk= preparing potato discs- control- care w/ dissecting equipment- if skin cut wash with soap and water immediately Hydrogen peroxide= irritant to eyes and skin- risk=filling syringe barrel and placing it on apparatus- avoiding skin contact/ goggles

Bags left out- could cause tripping and causing spillage of boiling water- control measure- keep bags under desk

Field work coast- slipping on rocks may cause cuts, strain or sprain- risk= working on loose or algal covered rocks- control- wear suitable shoes Getting cut off by the tide coming in- risk+ working in caves or coves- control- check tide tables before beginning work- work within earshot of others

field work in bodies of water Drowning by water inhalation- risk= accessing a stream or lake- walk very carefully- work within earshot of others in case of accident Weil's disease from ingesting Leptospirosis in water- risk= taking readings in stream or lake- control- use rubber gloves- avoid contact with water- keep cuts covered

Terrestrial field work Tripping on uneven terrain or roots- risk=accessing sample sites- control- walk very carefully- work in earshot of others in case of accident Poisonous plants or animals may sting or breach skin- risk= collecting data- control- avoid ingesting any biological material- wear appropriate clothing/ keep skin covered

all of the above- just for different environments

Results= raw data= readings taken and for processed data- calculations made from readings-always say results need column for IV then 3 columns for DV - 2 for readings- 1 for mean- write units in column headings only - make sure SI units used- preferred

Results= raw data= readings taken and for processed data- calculations made from readings- best to say readings/ calculated values- not results need column for IV then 4 columns for DV - 3 for readings- 1 for mean- write units in column headings only - make sure SI units used- preffered

If calibrations= 1 degree apart then use whole numbers eg 20C- if you go to 1 dp that indicates you can read to +/- 0.1C May use an electronic timer- gives time to 0.01s- but reaction time isn't that quick- meaningless to use this degree of accuracy- same goes for timing how long solution takes to decolourise- - colour change is gradual- round to nearest sec or min but only one unit only- not 1min 30- only seconds OR minutes Should have all units same across readings- unless need to add extra d.p to mean for clarity but explain why you've done this underneath table

If calibrations= 1 degree apart then usedecimal places eg 20.0C- if you go to 1 dp that indicates you can read to +/- 0.1C May use an electronic timer- gives time to 0.01s- but reaction time isn't that quick- meaningless to use this degree of accuracy- same goes for timing how long solution takes to decolourise- - colour change is gradual- round to nearest sec or min but only one unit only- not 1min 30- only seconds OR minutes Should have all units same across readings- unless nee to add extra d.p to mean for clarity but explain why you've done this underneath table

Bar Graph- Designed to make comparisons of data. The data represented in bar graphs are not necessarily dependent on any other variables and the groupings are usually qualitative (i.e. grouped into categories, like blood types or colour). The bars do NOT touch. Eg: Comparison of the mean reaction rate for five different enzymes

Histogram- Histograms are similar to bar graphs except the data represented in histogram is usually in groups of continuous numerical (quantitative) data. In this case, the bars do touch. Histograms are often used to show frequency data. Eg: Minimum Decibels (dBA) of sound heard by 20 people

Line graph- A line graph consists of a series of points plotted on the grid and then connected together point to point by a line. Line graphs are only used when both variables are quantitative. Line graphs show trends, such as how things change over time. Eg: Average mean temperature between the years 1900 and 2000

The points are plotted on the grid, but they are not joined point to point. A best fit line may be added to a scatter plot to show a trend. Line graphs are only used when both variables are quantitative. These graphs are useful for showing if a correlation exists between two variables, especially when it is not possible to alter either of the variables (i.e. in descriptive studies).

Intercept= Line of best fit is most suitable- line will account inaccuracy of each point- so intercept can be read more accurately than if you had only read 2 points on either side- look at p58- when best suitable- The type of graph that would have a line of best fit is a scatter plot. This graph shows the relationship between two variables by plotting individual data points, allowing for a visual representation of trends. The line of best fit helps to understand the overall direction of the data points. Predictions should only be made for values that are within the range of the given data

Line of best fit is always most suitable- line will account inaccuracy of each point- so points can be read more accurately look at p58- when best suitable- A line of best fit is created by using scattered data points. To find the scattered data points, make a scatter plot. A scatter plot uses plots on a graph to demonstrate a relationship between the two variables. Scatter plots are used to help find a pattern when these plot points are looked at as a whole- eg finding relationship. Look at this scatter plot where the x and y variables are related. The line of best fit can be used to predict the value of one variable from the other variable.Predictions should only be made for values that are within the range of the given data

Only line graphs can be used when we have data where each data point has two variables. In many experimental situations we are able to identify one of these variables as ‘independent’ and the other as ‘dependent’ – to see what effect changing the independent variable has had). In some cases data which can look superficially very similar to the line graph scenario is better presented as a scattergram. Once again we have two variables for each data point. It might also be the case that we have a variable we can identify as the independent and a variable we would call the dependent. But scattergrams are also appropriate when this is not the case. We might be interested in a possible association between two variables without being in a situation to change one variable and see what effect it has on the other variable.

Line graphs and scattergrams can be used when we have data where each data point has two variables. In many experimental situations we are able to identify one of these variables as ‘independent’ and the other as ‘dependent’ – to see what effect changing the independent variable has had). In some cases data which can look superficially very similar to the line graph scenario is better presented as a scattergram. Once again we have two variables for each data point. It might also be the case that we have a variable we can identify as the independent and a variable we would call the dependent. But scattergrams are also appropriate when this is not the case. We might be interested in a possible association between two variables without being in a situation to change one variable and see what effect it has on the other variable.

Commonest type at A level= range bar- use this when each point on graph= mean value- highest and lowest readings for each in addition to the mean- cross for mean and 2 little bars for other values- p58- in field work exp may need to plot bar chart using 2 mean values- can use range bars- usually done with T-test where standard deviation has been calculated- would need to specify its range bars as you could do standard deviation bars here too- in field work with correlation- would use scatter graph- won't use error bars

Commonest type at A level= range bar- use this when each point on graph= mean value- highest and lowest readings for each in addition to the mean- dots for mean and crosses for other values- p58- in field work exp may need to plot bar chart using 2 mean values- can use range bars- usually done with T-test where standard deviation has been calculated- would need to specify its range bars as you could do standard deviation bars here too- in field work with correlation- would use scatter graph- won't use error bars

When doing fieldwork exp- may have to analyse data w/ statistical test- use statistics in field data as genetic variation between organisms and minute differences in abiotic factors prevent you from making true replicate readings- without statistics hard to draw a valid conclusion- determine whether differences between data sets are significant or if it is due to natural variation

h

https://olc.ttsonline.net/Uploads/Science/64471/20210303104814_Statistics%20booklet.pdf

go on it please for the love of god

- describe general trend- say if it appears to be a direct relationship eg straight line w/ positive gradient and say if it seems to go through the origin- or say if it's an an inverse gradient eg straight line w/ negative gradient- if gradient seems to change explain that- shown in example 3

w/ positive gradient and say that it goes through the origin- or say if it's an an inverse gradient eg curved line w/ negative gradient- if gradient seems to change explain that- shown in example 3

Null- There is no difference in the mean length of the shrimp body as the water levels of the body of water the shrimp is kept in Trend- the calculated value of t is greater than the critical value of t at 38 degrees of freedom and 0.02 probability, so the null hypothesis is rejected at the 0.02 level of significance

Null- There is no difference in the mean length of the shrimp body in deep and shallow bodies of water Trend- the calculated value of t is greater than the critical value of t at 38 degrees of freedom and 0.05 probability, so the null hypothesis is rejected at the 0.05 level of significance

Look at raw data to see how similar the replicates at each value of the DV are - basically reliability Look at replicates in results table and decide which DV value has most different

Look at raw data to see how similar the replicates at each value of the IV are - basically reliability Look at replicates in results table and decide which IV value has most similar and most different results

2 ways to use bars and relate to their length and overlap length- another way to think about consistency- shows the highest and lowest readings- mean falls between- If bar is short- not much difference between lowest and highest scores- values=repeatable/ mean= reliable- look at graph and determine which are shortest and longest range bars- shows most/ least reliable means

Also correct just needed more space lol- Range bar overlap About how truly different the means are- means plotted w/ crosses- range bars around them-look at p62- if range bars overlap - highest reading for A is higher than lowest for B- do not have confidence means for A and B are truly different- look at rest of page

Source of error= subjectivity- reading= subjective when making a value judgement eg timing exactly when the methylene blue has gone colourless- when using colour- use colorimeter - eg how long it takes for solution to reach certain absorbance- reading no.s on a scale- no personal choice= objective and so accurate

Source of error= subjectivity- reading= subjective when making a value judgement eg timing exactly when the methylene blue has gone colourless- when using colour- use colorimeter - eg how long it takes for solution to reach certain absorbance- reading no.s on a scale- no personal choice= objective and so reliable

honestly idk to write as a wrong answer here lol

Source of error involves counting- it is possible to count incorrectly - field work example= testing effect of phosphate ion concentration on the number of water shrimp- if you have a lot of water shrimp in river sample and they're swimming fast- hard to count- improvement- take a representative volume of sample eg 100cm^3 river water- count how many water shrimp are in there- then measure volume of total sample and multiply up

Not wrong just need more space- when measuring mass balance may be correct to nearest 0.1g so balance that measures to 0.01g would make reading more accurate- another way of improving accuracy= top plan balance= top loading balance, is a balance with a weighing pan that is attached to the top- but if someone walks past while using balance air movements may lift balance plan- may be too small an effect to see but will give an artificially low mass- improvement= shield balance from air movements

Experiment may be totally subjective- consider accuracy of equipment- look at all measurements you've made- includes temperatures, volumes, lengths or masses- source of uncertainty is due to accuracy of calibrations - if thermometer is calibrated in degrees- only accurate to 1C- improvement= thermometer calibrated to 0.1 C-rulers and measuring cylinders= same- ruler calibrated in mm- improvement for accuracy- use callipers calibrated to 0.1mm- measuring cylinder may be calibrated in cm^3- improvement= burette- calibrated to 0.2cm^3 or syringe calibrated to 0.1cm^3

Photosynthesis- any shading from lamp or for incandescent bulbs-differential heating effect from the lamp- source when distance from light= IV - fluorescent lamp- no heat comes from the bulb= improvement or container of water between the bulb and vials- absorbs heat and not light- also to stop shading= do each vial separately

Field work- using a t-test could explain 0.05 probability contributes to acceptance or rejection of null- enhances accuracy of conclusion compared to 0.1% probability- also when using quadrats- ensure you have the right area quadrat

Enzymes- when using different temperatures or pH AND ONLY when either- optimum is between 2 values or extend range if you think gradient has reason to change improvement= take more readings- for 1st value- between 2 values that optimum was in between- for 2nd example more readings after last reading

Relate results to theoretical expectations- say if results support theory- results do not have to conform to theoretical expectations- but must be able to discuss them in major biological principles underpinning exp eg: looking at decolourisation of methylene blue by yeastt need to know biochemistry of anaerobic and aerobic respiration of yeast, effect of light on photosynthesis- need details of light dependent reactions of photosynthesis and concept of limiting factors that apply, field- need to know niche of an organism and how behaviour and characteristics relate to IV being tested, ALSO- enzymes give an equation and explain why it's physiologically important

Relate results to theoretical expectations- say if results support theory- results have to conform to theoretical expectations- must be able to discuss them in major biological principles underpinning exp eg: looking at decolourisation of methylene blue by yeastt need to know biochemistry of anaerobic and aerobic respiration of yeast, effect of light on photosynthesis- need details of light dependent reactions of photosynthesis and concept of limiting factors that apply, field- need to know niche of an organism and how behaviour and characteristics relate to IV being tested, ALSO- enzymes give an equation and explain why it's physiologically important

Statement of what you've learned : Refer back to the prediction you made at start and say if it's supported Illustrate trend by using positive or negative relationship Refer to data, graph and explanation you've given Comment on reliability and accuracy

Statement of what you've learned : Refer back to the prediction you made at start and say if it's supported Illustrate trend by making a % calculation if you observed a particular increase or decrease Refer to data, graph and explanation you've given Comment on reliability and accuracy

Give a null hypothesis State IV and DV At least 2 controlled variables stated An explanation of how you would make results reliable An explanation of how you would make results accurate

Give an alternative hypothesis State IV and DV At least 3 controlled variables stated An explanation of how you would make results reliable An explanation of how you would make results accurate

More readings to increase reliability of mean-if there's clearly an anomalous reading- justifiable to remove before calculating mean- but state what you have done and why

More readings to increase validity of mean-if there's clearly an anomalous reading- justifiable to remove before calculating mean- but state what you have done and why

h

Mark capture release- should be marked as unobtrusively as possible with a non toxic mark, should be returned as closely as possible to where you sampled them as soon as possible