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Biology_A-level_Cie

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  1. 1-1-the-microscope-in-cell-studies
    5 主题
  2. 1-2-cells-as-the-basic-units-of-living-organisms
    5 主题
  3. 2-1-testing-for-biological-molecules
    3 主题
  4. 2-2-carbohydrates-and-lipids
    8 主题
  5. 2-3-proteins
    6 主题
  6. 2-4-water
    2 主题
  7. 3-1-mode-of-action-of-enzymes
    5 主题
  8. 3-2-factors-that-affect-enzyme-action
    8 主题
  9. 4-1-fluid-mosaic-membranes
    4 主题
  10. 4-2-movement-into-and-out-of-cells
    12 主题
  11. 5-1-replication-and-division-of-nuclei-and-cells
    6 主题
  12. 5-2-chromosome-behaviour-in-mitosis
    2 主题
  13. 6-1-structure-of-nucleic-acids-and-replication-of-dna
    4 主题
  14. 6-2-protein-synthesis
    5 主题
  15. 7-1-structure-of-transport-tissues
    4 主题
  16. 7-2-transport-mechanisms
    7 主题
  17. 8-1-the-circulatory-system
    7 主题
  18. 8-2-transport-of-oxygen-and-carbon-dioxide
    5 主题
  19. 8-3-the-heart
    4 主题
  20. 9-1-the-gas-exchange-system
    6 主题
  21. 10-1-infectious-diseases
    3 主题
  22. 10-2-antibiotics
    3 主题
  23. 11-1-the-immune-system
    4 主题
  24. 11-2-antibodies-and-vaccination
    6 主题
  25. 12-1-energy
    5 主题
  26. 12-2-respiration
    11 主题
  27. 13-1-photosynthesis-as-an-energy-transfer-process
    8 主题
  28. 13-2-investigation-of-limiting-factors
    2 主题
  29. 14-1-homeostasis-in-mammals
    8 主题
  30. 14-2-homeostasis-in-plants
    3 主题
  31. 15-1-control-and-coordination-in-mammals
    12 主题
  32. 15-2-control-and-coordination-in-plants
    3 主题
  33. 16-1-passage-of-information-from-parents-to-offspring
    5 主题
  34. 16-2-the-roles-of-genes-in-determining-the-phenotype
    7 主题
  35. 16-3-gene-control
    3 主题
  36. 17-1-variation
    4 主题
  37. 17-2-natural-and-artificial-selection
    7 主题
  38. 17-3-evolution
    2 主题
  39. 18-1-classification
    5 主题
  40. 18-2-biodiversity
    7 主题
  41. 18-3-conservation
    6 主题
  42. 19-1-principles-of-genetic-technology
    11 主题
  43. 19-2-genetic-technology-applied-to-medicine
    4 主题
  44. 19-3-genetically-modified-organisms-in-agriculture
    2 主题
  45. 1-1-the-microscope-in-cell-studies
  46. 1-2-cells-as-the-basic-units-of-living-organisms
  47. 2-1-testing-for-biological-molecules
  48. 2-2-carbohydrates-and-lipids
  49. 2-3-proteins
  50. 2-4-water
  51. 3-1-mode-of-action-of-enzymes
  52. 3-2-factors-that-affect-enzyme-action
  53. 4-1-fluid-mosaic-membranes
  54. 4-2-movement-into-and-out-of-cells
  55. 5-1-replication-and-division-of-nuclei-and-cells
  56. 5-2-chromosome-behaviour-in-mitosis
  57. 6-1-structure-of-nucleic-acids-and-replication-of-dna
  58. 6-2-protein-synthesis
  59. 7-1-structure-of-transport-tissues
  60. 7-2-transport-mechanisms
  61. 8-1-the-circulatory-system
  62. 8-2-transport-of-oxygen-and-carbon-dioxide
  63. 8-3-the-heart
  64. 9-1-the-gas-exchange-system
  65. 10-1-infectious-diseases
  66. 10-2-antibiotics
  67. 11-1-the-immune-system
  68. 11-2-antibodies-and-vaccination
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Spearman’s rank correlation

  • Spearman’s rank correlation test can be used to determine whether there is correlation between variables when:

    • Data is not quantitative, e.g. an abundance scale has been used rather than a count of individuals

    • A visual inspection of data suggests a non-linear correlation

    • Data may not be normally distributed

  • Method:

    • Step 1: Create a scatter graph and identify possible linear correlation

    • Step 2: State a null hypothesis

    • Step 3: Use the following equation to work out Spearman’s rank correlation coefficient r

Spearmans rank equation, downloadable AS & A Level Biology revision notes

Where:

  • rs = Spearman’s rank coefficient

  • D = difference in rank

  • n = number of samples

  • Step 4: Refer to a table that relates critical values of rs to levels of probability

  • If the value calculated for Spearman’s rank is greater than the critical value for the number of samples in the data ( n ) at the 0.05 probability level (p), then the null hypothesis can be rejected, meaning there is a correlation between two variables

Worked Example

A group of students conducted an experiment using quadrats to measure the abundance of different plant species in a neglected allotment. They wanted to see if there was correlation between the abundance of species C and D. When they looked at their data and plotted a scatter graph they saw some correlation.

Investigate the possible correlation using Spearman’s rank correlation coefficient.

Scatter plot of species interaction, showing a positive correlation between individuals of species C (x-axis) and species D (y-axis).
Scatter graph showing the correlation between the abundance of species C and species D

Because the data was not normally distributed they decided to use Spearman’s rank correlation coefficient.

Null hypothesis: there is no correlation between the abundance of species C and species D.

  • n = 10 because there are 10 quadrat samples

Quadrat

No. of individuals of species C

Rank for species C

No. of individuals of species D

Rank for species D

Difference in rank (D)

D2

1

36

7

25

6

1

1

2

1

1

4

1

0

0

3

23

5

8

4

1

1

4

51

10

32

9

1

1

5

26

6

27

7

-1

1

6

8

2

5

2

0

0

7

43

9

35

10

-1

1

8

12

3

6

3

0

0

9

20

4

10

5

-1

1

10

41

8

29

8

0

0

 

 

 

 

 

 

∑D2 = 6

Step 1: Rank each set of data (rank 1 being the smallest data figure)

Step 2: Find the difference in rank between the two species, D

Step 3: Square the difference in rank, D2

Step 4: Add up the values of D2 to give ∑D2 (= 6)

Step 5: Substitute the appropriate numbers into the equation (remember n = 10)

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