Paper 5 Flashcards
(24 cards)
What is a respirometer used for
We read the manometer scale to measure rate of oxygen uptake during respiration of small terrestrial invertebrates/germinating seeds
Describe how a respirometer is formed
1) Pressure and temperature must be kept constant while reading is taken
→Use thermostatic water bath
2) Use control tube with equal volume of inert material (e.g. glass beads)
→Compensate for changes in atmospheric pressure
3) Soda lime/KOH/NaOH
→Absorb carbon dioxide produced
4) Volume of air in test tube with organisms decrease=oxygen consumption
→Level of manometer fluid nearer to experimental tube increases
How do we use the respirometer to measure RQ:
- Use same apparatus twice
1) Find volume of oxygen (x cm3 min-1) consumed at a fixed temperature with soda lime
2) Repeat by setting up with the same organism at the same fixed temperature but remove chemical that absorbs carbon dioxide
→Manometer fluid is now affected by both oxygen consumption and carbon dioxide release
→ check changes to manometer scale fluid
What is the RQ value if manometer fluid (nearer to experimental tube) level does not change:
If manometer fluid 9nearer to the xtperimemtal tube0 level does not change:
→Oxygen absorbed=carbon dioxide produced
RQ=1
What is the RQ value if the manometer lowers by y cm:
→Carbon dioxide produced>oxygen absorbed
→Volume of air in respirometer increase
RQ=(x+y)/x
Where x is the initial increase in manometer fluid
What happens to the RQ value if manometer fluid increases by z cm:
→Oxygen absorbed>carbon dioxide produced
→Volume of air in respirometer decrease
RQ=(x-z)/x
Where x is the initial increase in manometer fluid increases
How can we use the respirometer to measure the effect of temperature on oxygen consumption
Take measurements at various temperatures
Plot graph of oxygen consumption against temperature
Expetted result;
Higher temperature. Higher rate of respiration
Therefore faster absorption of oxygen
How can we investigate the rate of respiration of yeast
A redox indicator for example DCPIP, methylene blue can be used to investigate the rate of respiration of yeast.
Redox indicator/ dye dries not damage cells
So can add dye to suspension of yeast cells
When reduced, the blue dye becomes colourless
Measure time taken for dye to change from blue to colourless =rate of respiration of yeast
Can measure time taken at diff temp, with diff (s) or diff substrates
To measure effect on rate of respiration
What are the two types of data?
1) Qualitative data: can be nonmina;=categoric OR ordinal = placed in an order or rank
2) Quantitive data: Can be continuous (can take any value) OR discontinuous/discrete (usually whole numbers)
What are the types of distribution?
1) Normal distribution
*Continuous data
*Bell-shapes curve
*e.g. Weight, height
2) discontinuous distribution
*Not normally distributed
* E.g. categories, discrete data
Types of data/distribution will influence what stats can be used
What is null hypothesis?
*Statement to assume
*No significant difference
*Between two sets of results/data
*Differences present:
➡️Not significant
➡️Due to random error or chance
➡️ Can be ignored
What is the Chi-squared test, X^2
*To show if the observed results (o) are significantly different from the expected results (E).
Only can be used if:
*Discrete data/nominal data
*Discontinuous distribution
To test the results of:
a) Breeding experiments
b) Ecological sampling
X^2= ∑(O-E)^2/E
How can we use the X^2 table to determine significance of difference?
1) Calculate the value of X^2 test
2) Look for critical value (value in table) at p=0.05
3)Degrees of freedom, v=c-1
(Number of classes minus 1)
4) Check if the value of X^2 calculated is higher or lower compared to critical value in X^2 table.
How can we make conclusions from chi-squared test?
1) If chi squared-test value is higher than value in table:-
*Significant difference in results
*Reject null hypothesis
➡️Differences are NOT due to random error/chance
2) If chi squared-test value calculated is lower than critical value in table:-
*No significant difference in results
*Accept null hypothesis
➡️ Differences are due to random error/chance
What is standard deviation?
*To show the spread of spread of data about the mean, x̄, in a sample that is normally distubuted.
*Indicates relaibilty of data
*If s=small value
→Data is less scattered, more consistent and reliable
*If s=large value
→Data is widely spread, results are less reliable
Other functions:
To calculate standard error, and put error bars of a graph
*To calculate t-test value
What is the formula for standard deviation?
s=√∑(X-x̄)^2/(n-1)
X=each score
x̄=the mean or average
n=number of values
∑=sum of all values
What is standard error?
*To show how close the mean of sample calculated is from the true mean of the population
*SM shows the reliability of the mean
*Used to put error bars on on graphs
*small value of standard error shows:
➡️ the sample mean value is closer to the actual mean
➡️ mean is more reliable
*SM value is between 0 and 1
What is the formula for standard error?
Sm=s/√n
Describe bar charts with error bars
Requires:
1) mean, x̄= value for y coordinates
2) Standard error, SM
3) Error bars= lines on bar charts
*To draw error bars, we use upper and lower limits of a 95% confidence interval, that is mean ± 2 SM
*Function of error bars: to see if there is significant difference between two means
Describe upper and lower limits in normal distribution curve.
95% confidence interval=
Interval where 95% of the sample data lies around the mean
*Upper and lower limits of 95% confidence interval
➡️Min and max limit of the 95% interval
➡️Ic calculated by mean ± 2SM
How do we interpret error bars results?
*Error bars overlap
-The two means are not significantly different
-Null hypothesis accepted
*Error bars don’t overlap
-the two means are significantly different
-Null hypothesis is rejected
What is a t-test?
To treat whether data from two samples are significantly different.
Requirements:
*Continuous/interval data
*Data is normally distributed
*Standard deviations are approx. the same
*Two samples have <30 values each
t=| x̄1-x̄2|| √S1^2/n1 + S2^2/n2
How can we determine significant difference in t-test?
1)Calculate total degrees of freedom for t-test
2)Calculate total degrees of freedom for t-test
➡️V=(n1-1) + (n2-1)= n1+n2-2
3)Check critical value at p=0.05
4)Check if critical value in t-test table is lower/higher compared to t-test value calculated
How can we make conclusions in t-test?
1) If t value calculated is higher than value in table:
➡️The two data sets are significantly different
➡️Reject null hypothesis
➡️Differences are NOT due to random error/chance
2) If t value calculated is lower than value in table:
➡️The means of the data are not significantly different
➡️Accept null hypothesis
➡️Any differences are due to chance/random error
How to calculate the biodiversity of a habitat?
Use simpson’s index of diveristy (D)
D=1-(∑(n/N)^2)
Where n=number of induviduals of each species present in the sample
N=total number of all induviduals of all species
The higher the index (nearer to 1), the higher the diversity
