1. Lesson objectives the different types of variation
To include intraspecific and interspecific variation AND the differences between continuous and discontinuous variation, using examples of a range of characteristics found in plants, animals and microorganisms AND both genetic and environmental causes of variation.
An opportunity to use standard deviation to measure the spread of a set of data and/or
Student’s t-test to compare means of data values of two populations and/or
Spearman’s rank correlation coefficient to consider the relationship of the data.

2. Variation
The presence of variety
(of differences between individuals)

3. Variation within species

4. Variation between species
Usually obvious.
Variation used to classify one species from another.

5. Continuous & Discontinuous
Continuous variation:
A full range of intermediate phenotypes between two extremes.
Discontinuous variation:
Discrete groups of phenotypes with no or very few individuals in between

6. What causes variation?

7. Inherited / genetic variation
Genes (inherited from parents)
Alleles (versions of these genes)
Sexual reproduction – random shuffling of alleles – new combinations of parental alleles in offspring
Mutations – “mistakes” in the DNA change base sequence and may bring about a new version of the gene (i.e. a new allele)

8. Mutations
When cells divide they need new chromosomes to fill the nucleus.
The chromosomes replicate and sometimes a mistake is made, causing a change in a gene on that chromosome.
This is called a mutation.
We all inherit some mutations but usually we aren’t aware of them as we have 2 copies of each gene.

9. Can mutations have other Causes?
Radiation can increase the number of mutations. This includes any high energy rays such as
ultra violet
X rays
Ionising radiation
Some chemicals can also lead to mutations such as Mustard Gas which has been used in chemical warfare.

10. Are Mutations Always Bad?
Mutations provide variation
For the individual mutations can be bad, good or neutral.
Without them there would be no differences between individuals, and this would mean everyone would be equally likely to survive or die.
Mutations create variation which leads differences in success at surviving which leads to natural selection and therefore the possibility of evolution.

11. Attached earlobes
(recessive
Free earlobes
(dominant)

12. Environmental causes of variation

13. A combination of both?
Environmental and genetic variation are linked. E.g. Height
Not all genes are active at any one time. Changes in the environment affect which genes are active.

14. Question to try:
For each of these examples of variation between sunflower plants, suggest whether they are caused by genes alone, environment alone, or an interaction between both.
The height of the plant
The colour of the plant petals
The diameter of the mature flower
The percentage of seeds that develop after fertilisation

15. Look at the following data
50 petals for the flowers of a rush (Luzula sylvatica)
3.1
3.2
2.7
3.0
3.3
2.9
3.4
2.8
3.5
Calculate the mean petal length of this sample
Count up the number of petals of each length. Draw a histogram to display these results.
What is the mode for these results?
What is the median petal length?

16. Standard Deviation This measures the spread of the data from the mean.
There is more variation in leaf length so leaves in this group varies a lot from the mean.
There will be a large standard deviation
There is less variation in leaf length so overall each leaf is closer to the mean
There will be a small standard deviation

17. Displaying the data
These leaf lengths can be drawn as histograms and the spread of the data compared
Number of leaves
Number of leaves
Leaf length (mm)
Leaf length (mm)

18. Calculating the Standard deviation
This means the sum of
This the symbol for mean
n is the number of values

19. Worked Example Tree Height (m) A 22 B 27 C 26 D 29
Tree
Height (m) A 22 B 27 C 26 D 29
Adding and subtracting the standard deviation to the mean will include 68% of the data.

21. Error Bars These can be drawn onto a graph.
They’re drawn by adding 1SD to the value and subtracting 1SD from the value.
They can be added to line or bar graphs.
From our example on tree height
Mean = 26
SD = 2.9
= 28.9
= 23.1 30 28 26 24 22 20 18
Mean Height (m)

22. Produce a list of human characteristics to fill the following table
Produce a list of human characteristics to fill the following table. For each state if it is environmental / inherited or both. State whether it is continuous or discontinuous.
Inherited
Environmental
Both

23. Students T Test
This is a statistical test to determine whether 2 sets of data are statistically different.
A continuous characteristic such as length, height, width, mass can be measured and compared between 2 different groups
eg males and females
lower shore and upper shore
sun and shade leaves

24. Null Hypothesis This is a negative statement.
Usually it will state that there is no link between 2 factors.
eg There is no similarity between 2 sets of data

25. To be able to use the T Test, the data must be normally distributed.
The mean height is likely to be close to the peak of the curve
frequency
Height of men (cm)

26. When comparing the distributions for male and female height there is a difference in the position of the mean but there is also a lot of overlap.
Are they statistically different?

27. Collate and display the data as histograms to determine whether each set is normally distributed
Numbers
We need to know whether the data is significantly different from each other by comparing the means and the spread of the data, so we will need to calculate:
The means of each set
The standard deviations of each set
Length (mm)
Numbers
Length (mm)

28. The Student T Formula This compared the means
This compares the standard deviations squared (known as the variances

29. Understanding What The value of t means
The value of t which is calculated must be compared to the table of values.
Work out the number of degrees of freedom
(n1+ n2 )- 2
If the value of T is equal to or more than the critical value there is significant difference between the two sets of data
Probability 
0.05
0.025
0.01
Degrees of freedom 1
6.3138 2
2.9200
4.3026
6.9646 3
2.3534
3.1824
4.5407 4
2.1319
2.7764
3.7470 5
2.0150
2.5706
3.3650 6
1.9432
2.4469
3.1426 7
1.8946
2.3646
2.9980 8
1.8595
2.3060
2.8965 9
1.8331
2.2621
2.8214 10
1.8124
2.2282
2.7638 11
1.7959
2.2010
2.7181 12
1.7823
2.1788
2.6810 13
1.7709
2.1604
2.6503 14
1.7613
2.1448
2.6245 15
1.7530
2.1314
2.6025 16
1.7459
2.1199
2.5835 17
1.7396
2.1098
2.5669 18
1.7341
2.1009
2.5524 19
1.7291
2.0930
2.5395 20
1.7247
2.0860
2.5280
T table