1. Mathematical requirements in the NEW 2015 A Level Psychology
Deb Gajic
(CPsychol, AFBPsS)
Head of Psychology
The Polesworth School
Thursday 24th September 2015

2. Mathematical Requirements
What’s changed?
10% mathematical requirement at at least level 2 (GCSE) (take calculator into examination) – See specifications and maths appendix
OFQUAL requirements refer to ALL specifications
ds/attachment_data/file/446829/A_level_science_subje ct_content.pdf
Focus on the mathematical skills which are new or which in my opinion people will find most challenging.

3. Mathematical Requirements
Changing mindsets
Making I can’t become I can
Why does Maths have this effect?
People go to great lengths to hide illiteracy, but seem to have no problem saying ‘I can’t do maths’
The challenge: - make maths relevant to psychology, unthreatening, meaningful and active

4. Mathematical Requirements
Changing mindsets
Making I can’t become I can
Being good at mental maths is not being a great mathematician

5. Mathematical Requirements
Recommended texts
Simple Statistics by Francis Clegg
ISBN-13:
Research Methods & Statistics in Psychology by Hugh Coolican
ISBN-13:

6. D.0 Arithmetic and Numerical Computation

7. D.0.1 Recognise and use expressions in decimal and standard form
Standard form is a way of writing down very large numbers easily. E.g = 103 (13 x10 = 103)
Small numbers can also be written in standard form. However, instead of the index being positive (in the above example, the index was 3), it will be negative. E.g = 5 × 10-2
The rules when writing a number in standard form are that first you write down a number between 1 and 10, then you write × 10 (to the power of a number)

8. D.0.1 Recognise and use expressions in decimal and standard form
The mean number of neurons in the human brain is 100,000,000,00. Express this in standard form
One neuron may be as narrow as centimeters in diameter. Express this in standard form

9. D.0.1 Recognise and use expressions in decimal and standard form
e.g. Move the decimal point 11 places or 11 zeros
2) = 4x10-3
e.g. Move the decimal point 3 places or 3 zeros.

10. D.1 Handling Data

11. D.1.4 Understand Simple Probability
Complete the probability activity
This activity also covers D.0.2 – Use ratios, fractions and percentages

12. D.1.4 Understand Simple Probability
Type I Error
False Positive. Rejecting the null hypothesis, when there is a possibility that the results were due to chance. Often caused by using a significance level that is too lenient e.g. 10%, 0.10, 1 in 10, p≤ Not being cautious enough.
Type II Error
False Negative. Accepting the null hypothesis, when there is a possibility that the results were significant. Often caused by using a significance level that is too strict e.g. 1%, 0.01, 1 in 100, p≤ Being over cautious.

13. D.1.4 Understand Simple Probability

14. D.1.6 Understand the terms mean, median and mode
Haribo Sweet Activity
Useful for understanding population and sampling and sample sizes, as well as calculating mean, median and mode

15. D.1.8 Use a statistical test
Sign Test
This test simply involves counting up the number of positive and negative signs.
Example: -
A study was conducted to discover if students changed their attitude towards the death penalty after watching ‘The Green Mile’.
Experimental Hypothesis: - Watching the film ‘The Green Mile’ will influence student’s attitudes to the death penalty. (non- directional – two-tailed)
AQA Test of choice at AS

16. D.1.8 Use a statistical test

17. D.1.8 Use a statistical test
Sign Test
Add the number of times the least frequent sign appears. In this case the + sign, so S = 1.
Look at the critical value tables to obtain the critical value for S, number of score = 9 (as pairs of scores with no change are omitted).
Critical Value for a two tailed test = 1, therefore the Null hypothesis can be rejected the test result was statistically significant (most people did change their opinion after watching the film)

18. D.1.8 Use a statistical test
Sign Test
A researcher wished to find out if participants had a more positive image of statistics after they had been taught an introductory course.
Experimental Hypothesis: - Participants will rate statistics more positively once they have been taught an introductory course. (1-tailed)
NB Ratings are ordinal data, but we are analyzing them at a nominal level, hence the sign test.

19. D.1.8 Use a statistical test

20. D.1.8 Use a statistical test

21. D.1.8 Use a statistical test
Sign Test
Add the number of times the least frequent sign appears. In this case the + sign, so S = 2.
Look at the critical value tables to obtain the critical value for S, number of score = 10 (as pairs of scores with no change are omitted).
Critical Value for a one tailed test = 1, therefore the Null hypothesis must be accepted the test result was not statistically significant (most people did not change their opinion after taking the introductory statistics course)

22. D.1.9 Make order of magnitude calculation
Orders of magnitude are used to make very approximate comparisons and reflect very large differences.
For example compare 387 with 40,262,030
387 is approximately 400 and 40,262,030 is approximately 40,000,000
Therefore 40,262,030 is approximately 10,000 times bigger than 387 (40,000,00 has 5 more zeros than 400)

23. D.1.10 Distinguish between levels of measurement
Nominal data: a level of measurement where data are in separate categories (Frequencies).
Ordinal data: a level of measurement where data are ordered in some way. (Interval & Ratio data can be converted to ordinal)
Ordinal data is data that can be placed in rank order e.g. 1st, 2nd, 3rd etc.
Used in non-parametric tests

24. D.1.10 Distinguish between levels of measurement
Interval data: a level of measurement where units of equal measurements (a scale with equal intervals) are used e.g. minutes, kilograms, number of words recalled in a memory test or percentage score in an exam.
Ratio data is also on a scale with equal intervals, but has a true zero e.g. weight/height, time, distance.
Used in Parametric tests

25. D.1.11 Know the characteristics of normal and skewed distributions

26. D.1.11 Know the characteristics of normal and skewed distributions
Characteristics of a normal distribution curve, also know as a bell- shaped curve or a Gaussian curve: -
it is bell-shaped
it is symmetrical
the mean, median and mode all fall on the same central point.
The two tails never touch the horizontal axis.

27. D.1.11 Know the characteristics of normal and skewed distributions
As well as normal distributions, curves can be positively skewed, negatively skewed or bi-modal.

28. D.1.12 Select an appropriate test – Non-parametric

29. D.1.12 Select an appropriate test – parametric
Conditions for Parametric Testing: -
Data is interval or ratio
Data is normally distributed
Homogeneity of variances. (Standard deviations or variances for the two sets of data are equal)

30. D.1.12 Select an appropriate test – parametric

31. D.1.13 Use statistical tables to determine significance
Critical Value Tables
If there is a R in the name of the test the calculated value must be more than or equal to the critical value.
If there is not a R in the name of the test the calculated value must be less than or equal to the critical value.

32. D.1.14 Understand measures of dispersion, including standard deviation and range
Calculating Standard Deviation
The requirement to calculate this is hidden in the exemplification for D This also covers D.2.2 substitute values into a formula

33. D.1.14 Understand measures of dispersion, including standard deviation and range

34. D.1.14 Understand measures of dispersion, including standard deviation and range

35. D.1.14 Understand measures of dispersion, including standard deviation and range

36. D.1.14 Understand measures of dispersion, including standard deviation and range
is the variance

37. D.2 Algebra

38. D.2.1 Understand and use symbols
Required symbols
=, <, <<, >>, >,
< Less than << much less than
> Greater than >> much greater than
Approximately equal to
Proportional to
Much less/greater use with probability e.g. much less than 5%
Proportional to – Stratified sampling
Approximately equal e.g. Baron-Cohen Normal = 20.3/25 Tourettes = 20.4/25

39. D.2.3 Solve simple algebraic equations
Degrees of Freedom in a Chi-square
Number of values that are free to vary
df=(no: of rows-1)(no: of columns-1)

40. D.2.3 Solve simple algebraic equations
Example of a contingency table: -
 Piaget Conservation Experiment
Hypothesis: 7 year olds will be more likely to be able to conserve than 5 year olds. (Directional - One-tailed)

41. D.2.3 Solve simple algebraic equations
What is the df for the table?
It is a 2 X 2 contingency table (2 rows and 2 columns with data)
(2-1) X (2-1)
1 X 1 = 1
df = 1

42. D.3 Graphs

43. D.3.1 Translate information between graphical, numerical and algebraic forms
Bar Chart, Scatter graph, Line graph, Pie Chart
Sketching graphs - Remember to label all axis and put a title on it
Interpreting graphs - Say what you see, relate to stimulus

44. D.3.1 Translate information between graphical, numerical and algebraic forms
When constructing scattergraphs use mini jelly babies or smiley face stickers instead of crosses
This ensures students understand that each point on the graph represents a participant.

45. All resources can be found on http://webinars.resourcd.com
Any Questions?
All resources can be found on