Genera Certificate of Education Advanced Leve Examination June 2010 Human Bioogy HBI6T/P10/task Unit 6T A2 Investigative Skis Assignment Task Sheet The effect of temperature on the rate of photosynthesis Introduction Agae are singe-ceed organisms that photosynthesise. You are going to measure their rate of photosynthesis at different temperatures. You wi be suppied with ge beads containing agae. This ge does not harm the agae. You wi put the ge beads in hydrogencarbonate indicator soution. As the agae photosynthesise, they take up carbon dioxide from the soution. This causes the indicator to change coour from yeow to red as the carbon dioxide concentration fas. You can use the coour change to measure the rate of photosynthesis. You wi find the mean rate of photosynthesis at two different temperatures. You wi do this by recording how ong it takes yeow hydrogencarbonate indicator to change coour to red. Your teacher wi suppy you with yeow indicator to use in your experiments. You wi aso be given red indicator to use to determine when the coour change has taken pace. Materias You are provided with ge beads containing agae a arge beaker to use as a waterbath or access to an eectric waterbath thermometers amps hydrogencarbonate indicator soutions (yeow and red) sma specimen tubes, or simiar, which can be capped test tubes graduated pipettes marker pen 10 cm 3 measuring cyinder or syringe timer distied water. You may ask your teacher for any other apparatus you require.
2 Outine Method Read these instructions carefuy before you start your investigation. 1. Rinse a test tube with 1 cm 3 of the yeow indicator. 2. Put 5 cm 3 of the yeow indicator soution into your rinsed tube. Labe it tube A. 3. Rinse your aga beads in 1 cm 3 yeow indicator soution. Put 10 aga beads into a specimen tube. Labe it tube B. 4. Stand both tubes A and B in a water bath at 30 ºC. 5. Leave the tubes in the water bath for 10 minutes. 6. Meanwhie, set up a amp so that the ight fas on the waterbath. Pace the amp between 20 cm and 30 cm from the tubes in the waterbath. 7. Take tube A with the indicator soution and add the contents to the specimen tube B containing the aga beads. Cap and shake the tube. 8. Immediatey return tube B to the water bath and start the timer. 9. Leave the tube in the waterbath under the ight, shaking the tube genty every few minutes. 10. You have been suppied with a tube containing red indicator. Compare the coour of the iquid in your tube with the red indicator. 11.Record the time it takes for the coour of your indicator in tube B to change to the coour of the red indicator. 12.Repeat steps 1 11 as many times as necessary to coect enough data to carry out a suitabe statistica test. 13.Repeat steps 1 12 using a waterbath at 40 ºC. You wi need to decide for yoursef how to te when the coour change of the hydrogencarbonate indicator soution is compete how many repeats to carry out which statistica test to carry out.
3 ISA HBI6T/P10 Candidate Resuts Sheet: Stage 1 The effect of temperature on the rate of photosynthesis Centre Number Candidate Number Candidate Name... Record your data in a tabe in the space beow. (3 marks) Hand in this sheet at the end of each practica session. Turn over
4 ISA HBI6T/P10 Candidate Resuts Sheet: Stage 2 The effect of temperature on the rate of photosynthesis Centre Number Candidate Number Candidate Name... Use the space beow to anayse your data with a suitabe statistica test. You may use a cacuator and the statistica sheet that has been provided to perform this test. (6 marks) You shoud state your nu hypothesis give your choice of statistica test give reasons for your choice of statistica test
5 carry out the test and cacuate the test statistic interpret the test statistic in reation to the nu hypothesis being tested.
6 This graph paper is provided for use if you need it. Hand in this sheet at the end of the practica session.
7 Students Statistics Sheet What sort of data did you obtain in your investigation? Measurements The investigation invoved taking measurements Frequencies The investigation invoved finding the number of individuas in particuar categories Looking for associations between different measurements made from the same sampe Looking for differences between measurements from different sampes Looking for associations between measurements of two variabes Chisquared (χ 2 ) test Spearman rank correation Two sampe t test Standard error and 95% confidence imits (Pearson s) correation coefficient For use in the A2 ISA and EMPA assessment Turn over
8 Tabes of critica vaues Statistica tests and tabes of critica vaues A tabe of critica vaues is provided with each statistica test. If your cacuated test statistic is ess than, or equa to, the critica vaue, then the resut of your statistica test is significant. This means that your nu hypothesis shoud be rejected. Spearman rank correation test Use this test when you wish to find out if there is a significant association between two sets of measurements from the same sampe and you have between 5 and 30 pairs of measurements. Record the data as vaues of X and Y. Convert these vaues to rank orders, 1 for argest, 2 for second argest, etc. Now cacuate the vaue of the Spearman rank correation, r s, from the equation [ ] r s = 1 6 Σ D2 N 3 N Where N is the number of pairs of items in the sampe. D is the difference between each pair (X-Y) of measurements. A tabe showing the critica vaues of r s for different numbers of paired vaues. Number of pairs Critica vaue of measurements 5 1.00 6 0.89 7 0.79 8 0.74 9 0.68 10 0.65 12 0.59 14 0.54 16 0.51 18 0.48
9 Correation coefficient (Pearson s correation coefficient) Use this test when you wish to find out if there is a significant association between two sets of measurements measured on interva or ratio scaes the data are normay distributed. Record the data as vaues of variabes X and Y. Now cacuate the vaue of the (Pearson) correation coefficient, r, from the equation r = ΣXY [(ΣX)(ΣY)]/n {ΣX 2 [(ΣX) 2 /n]} {ΣY 2 [(ΣY) 2 /n]} Where n is the number of vaues of X and Y. A tabe showing the critica vaues of r for different degrees of freedom. Degrees of freedom Critica vaue Degrees of freedom Critica vaue 1 1.00 12 0.53 2 0.95 14 0.50 3 0.88 16 0.47 4 0.81 18 0.44 5 0.75 20 0.52 6 0.71 22 0.40 7 0.67 24 0.39 8 0.63 26 0.37 9 0.60 28 0.36 10 0.58 30 0.35 For most cases, the number of degrees of freedom is = n 2 Turn over
10 The t test Use this test when you wish to find out if there is a significant difference between two means the data are normay distributed the sampe size is ess than 25. t can be cacuated from the formua t = x 1 x 2 (s 1 2 /n 1 ) + (s 2 2 /n 2 ) Where x 1 = mean of first sampe x 2 = mean of second sampe s 1 = standard deviation of first sampe s 2 = standard deviation of second sampe n 1 = number of measurements in first sampe n 2 = number of measurements in second sampe A tabe showing the critica vaues of t for different degrees of freedom. Degrees of freedom Critica vaue Degrees of freedom Critica vaue 4 2.78 5 2.57 15 2.13 6 2.48 16 2.12 7 2.37 18 2.10 8 2.31 20 2.09 9 2.26 22 2.07 10 2.23 24 2.06 11 2.20 26 2.06 12 2.18 28 2.05 13 2.16 30 2.04 14 2.15 40 2.02 The number of degrees of freedom = (n 1 + n 2 ) 2
11 Standard error and 95% confidence imits Use this when you wish to find out if the difference between two means is significant the data are normay distributed the sizes of the sampes are at east 30. For assessment purposes, five sampes are acceptabe providing that this is acknowedged either at a convenient pace in the statistica anaysis or in the concusions. Standard error Cacuate the standard error of the mean, SE, for each sampe from the foowing formua: SE = SD n Where SD = the standard deviation n = sampe size 95% confidence imits In a norma distribution, 95% of datapoints fa within ± 2 standard deviations of the mean. Usuay, you are deaing with a sampe of a arger popuation. In this case the 95% confidence imits for the sampe mean is cacuated using the foowing formua 95% confidence imits = x ± 2 SD OR x ± 2 SE n Turn over
12 The chi-squared test Use this test when the measurements reate to the number of individuas in particuar categories the observed number can be compared with an expected number which is cacuated from a theory, as in the case of genetics experiments. The chi-square (χ 2 ) test is based on cacuating the vaue of χ 2 from the equation χ 2 = Σ (O E) 2 E Where O represents the observed resuts E represents the resuts we expect. A tabe showing the critica vaues of χ 2 for different degrees of freedom. Degrees of Critica vaue freedom 1 3.84 2 5.99 3 7.82 4 9.49 5 11.07 6 12.59 7 14.07 8 15.51 9 16.92 10 18.31 The number of degrees of freedom = number of categories 1