1. Implications of Psychological research and the economy

2. Economic implications from Psychological research: Spec states:
No extra teaching is required here. It is expected that students will be able to use content from topics they have covered elsewhere on the Specification. They would need to be able to explain the economic implications of the research.

3. For the exam….
You must be able to identify how psychological research: influences, affect, benefit or devalue economic prosperity.
You should be able to explain how at least two examples of psychological research have implications for the nations economy.
You could be able to apply your own research findings and discuss as a group how this impacts the economy.

4. Some statistics:
What on average does absence from work cost the British Economy every year?
£ 15 Billion

5. What are a third of all absences due to ?
Depression
Anxiety
Stress

6. How many days are lost on average each year by a person suffering with stress, anxiety and depression?
The average days lost per case for stress, depression or anxiety is 24 days

7. What is the estimated cost of absence from work due to Mental Health?
In the world of work, one study estimates that sickness absence due to mental ill health costs around £8 billion per year (70 million working days missed each year, or an average of 2.8 days per year per UK employee).
Lost productivity where mental health issues lessen work performance, costs £15 billion, and replacing staff who leave their posts because of mental illness costs employers £2 billion.

8. What percentage of mothers work full time?
29%

9. What is the percentage of mothers working part time?
37.4% How could more women be encouraged to join the work force?

10. How could you be asked this in the exam?
Why is psychological research vital for the economy,
How has research into attachment helped women back into work?
How can research help people with mental illness get back into employment?
How can research into EWT and the Cognitive interview help the economy?
How can research into minority influence help with the environmental issues that affect the economy?

11. AS examples Attachment Research:
There are opportunities for extended discussion of economic implications here.
Bowlby’s WHO report in the 1950s was taken to suggest that babies needed the constant care of the mother for healthy psychological development. This led to ‘stay at home’ mothering.
Later evidence has shown that good substitute care childcare either in nurseries or by other family members e.g. father does not have a detrimental effect on social development.
As an example then, this means that mother can happily return to work after having a child, remaining economically active.

12. AS examples Psychopathology Research:
Anything to do with treatment and people’s ability to work and contribute as effective members of society would be relevant.
For example, studies often compare the effectiveness of different therapies. If research shows that people with a disorder such as depression are less likely to suffer a relapse after having cognitive therapy then, even though cognitive therapy might initially be more expensive than drug therapy, in the long-term it might be more economically sound to offer cognitive therapy as people would have less time off work.

13. AS examples
Memory Research: Any evidence relating to more efficient use of public money would be relevant. For example, research showing the cognitive interview facilitates accuracy of eyewitness reporting enables better use of police time and resources.

14. Exam Question
Using examples briefly discuss the implications for psychological research for the economy (6 marks)
Top tips: the question says examples you must use two !
Use research,
Time 8 minutes.
PEEL Point, evidence, explain, link back to the question.
Two paragraphs.
Refer to the words implications for the economy throughout.

15. Mark scheme only one piece of research is used the maximum mark is 3
Level
Marks
Description 3
5–6
The implications of two pieces of research and its implications for the economy is generally detailed, clear and coherent. There is effective use of terminology 2
3–4
The implications of two pieces of research and its implications for the economy is mostly clear but some detail is missing or not fully elaborated .Some effective use of terminology 1
1–2
The implications of two pieces of research and its implications for the economy lacks detail and clarity.. Terminology is either minimal, absent or inappropriately used
No relevant content
only one piece of research is used the maximum mark is 3

16. Inferential Statistics
Introduction to…
Inferential Statistics

17. A2: what you need to cover
Reliability across all methods of investigation. Ways of assessing reliability: test-retest and inter-observer; improving reliability.
Types of validity across all methods of investigation: face validity, concurrent validity, ecological validity and temporal validity. Assessment of validity. Improving validity.
Content analysis
Features of science: objectivity and the empirical method; replicability and falsifiability; theory construction and hypothesis testing; paradigms and paradigm shifts.
Reporting psychological investigations. Sections of a scientific report: abstract, introduction, method, results, discussion and referencing.

18. A2: what you need to cover
Inferential testing
Students should demonstrate knowledge and understanding of inferential testing and be familiar with the use of inferential tests.
Introduction to statistical testing; the sign test.
Probability and significance: use of statistical tables and critical values in interpretation of significance; Type I and Type II errors.
Factors affecting the choice of statistical test, including level of measurement and experimental design. When to use the following tests: Spearman’s rho, Pearson’s r, Wilcoxon, Mann-Whitney, related t-test, unrelated t-test and Chi-Squared test.

19. Just a recap …. On your whiteboards.. On your own…
What is the IV?
What is the DV?
What is a directional hypothesis?
What is a non-directional hypothesis?
What is the mean?
What is the median?
What is the mode?
What are these 3 tests called?
What we manipulate
What we measure
Prediction – direction
Usually based on previous research
Prediction – no direction
Average
Middle value
Most common
Descriptive statistics

20. Why do we need to conduct statistical tests?
Statistical tests tell us the significance of a set of findings- did the IV really effect the DV or were the findings a fluke?!
The more significant a finding is the more effect the IV had on the DV
With an experiment looking at differences between conditions, we need to establish the probability that the results are significant, in other words, that two sets of data are different enough to conclude that the IV has made the changes occur in the DV

21. Probability, significance and the null hypothesis

22. Hypothesis Two hypothesis are formulated at the beginning of a study:
The experimental/alternative hypothesis (H1)
Predicts that there will be a significant difference
Directional or non directional (one tailed or two tailed)
The null hypothesis (HO)
predicts that there will not be a significant difference

23. What is a null hypothesis and why do we need one?
The null hypothesis predicts that any difference between two or more sets of data will have occurred through chance alone
When carrying out research, we ALWAYS work from the null hypothesis.
If the null hypothesis is rejected we say our results are statistically significant (a difference was found)
If the null hypothesis is accepted we say that are results are NOT significant.
Why do we focus on the null hypothesis?
We focus on the null hypothesis because it eliminates bias from the research by forcing the researcher to consider the view that any difference found between the two sets of data has occurred through chance alone

24. A team of psychologists was interested in studying the effects of alcohol on peoples' reaction times. Earlier research suggested that an increase in reaction time was due to the alcohol rather than peoples' expectations of alcohol. The psychologists recruited two groups of volunteers (an independent groups design) from a local university. Each participant's reaction time was measured by using a computer game.
The participants were then given a drink. The first group received a drink containing a large measure of strong alcohol; the second group received an identical drink without alcohol, but with a strong alcoholic smell. Finally, all participants were required to play the computer game again to assess their reaction time. Once they had completed the task, they were then thanked for their time and allowed to leave.
What is the IV?
whether the participants have had an alcoholic drink or one that is not alcoholic but smells as if it is
What is the DV?
reaction times on a computer game
Null hypothesis:
There will be no difference between the university students‘ reaction times on a computer game between those who have had an alcoholic drink or one that is not alcoholic but smells as if it contains alcohol; any differences are due to chance factors.

25. Probability:
We need to use inferential statistics to tell us if the result that we have found is due to chance or not
To establish if our results are reliable we have to look at the probability of a result being due to chance or not
This is known as: level of significance (p value)
The minimum accepted level of probability commonly used in psychology is 5%, this is represented as 0.05
If the level of significance achieved from a test is equal to or less 0.05 than the results are said to be significant
This would mean that we are 95% sure that the IV caused the change in the DV

26. Probability: Can be expressed as:
A proportion: for example - a 1 in 5 chance.
As a percentage: for example - 20%
More commonly expressed as a decimal in psychology: 0.2.
In psychology the most common significance levels are:
10%=0.10
5%=0.05
1%=0.01
0.1%=0.001
To go from % to decimal move the percentage sign and move the decimal point two spaces to the left.

27. Observed value:
Every time you perform a statistical test you get an OBSERVED/CALCULATED VALUE This observed value tells you the extent to which your results are valid. You then have to compare this observed value to a table of CRITICAL VALUES to see if your results are significant or not Each statistical test has a different critical values table. Depending upon the test, the observed value should be greater or less than the critical value to be significant.

28. Interpreting results:
Usually in psychology if the results are significant it means that the probability of the result being due to chance is 5% or less
We express our results in terms of the Null Hypothesis.
If a result is statistically significant we can reject the null hypothesis and accept the experimental hypothesis
In psychology we write this as: P<0.05
This means that the results are significant. The probability of our results being down to chance in less than 5%. Therefore we would reject the null hypothesis and accept the experimental hypothesis.

29. Interpreting results:
P is used to represent “the probability that is due to chance”
> =means greater than
< =means less than
≥ means greater than or equal to
≤ means less than or equal to
SO………………
P<0.05 means that the probability that the result is due to chance is less than 5%

30. Type 1 and type 2 errors:
The 5% level of significance has been accepted as it represents a reasonable balance between the chances of making a type 1 or type 2 error
These can occur because:
Level of probability accepted is either too lenient (too high) or too stringent (too low)

31. Type 1 and type 2 errors Type 1 error: Type 2 error:
This can happen if the accepted level of probability is set TOO LENIENT
Significance level set at 20% (0.2)
Occurs when we conclude that there IS a significant difference when there is NOT
So we reject the null hypothesis and accept the alternative hypothesis
Type 2 error:
This can happen if the probability level is TOO STRINGENT (we are too careful)
Significance level set at 1% (0.001)
Occurs when we reject the experimental hypothesis and accept the null when there IS a difference
So we accept the null hypothesis and reject the alternative hypothesis

32. RECAP: Quiz
Outline the difference between descriptive statistics and inferential statistics?
The null hypothesis predicts that there will be a significant difference? True/false.
Shorthand for the null hypothesis is Ho? True/false
What are Inferential statistics?
Why is it necessary to have a Null hypothesis?

33. 6. If the null hypothesis is retained, this means that the result is…
6. If the null hypothesis is retained, this means that the result is….. 7. What is the chosen p value also known as? 8. When does a type one error occur? 9. When does a type 2 error occur? 10. Which p value would you use if you were conducting a piece of research that is socially sensitive?

34. 1. Outline the difference between descriptive statistics and inferential statistics?
Summarising data vs. allowing you to see whether the research hypothesis or null hypothesis is retained
2. The null hypothesis predicts that there will be a significant difference? True/false.
False
3. Shorthand for the null hypothesis is Ho? True/false
True
4. What are Inferential statistics?
Tests designed to assess whether we reject or retain the null hypothesis.
5.Why is it necessary to have a Null?
Eliminates bias. Forces researcher to accept the view that the two sets of data has occurred through chance. Means there is no other conclusions that can be made

35. 6. If the null hypothesis is retained, this means that the result is not significant.
7. What is the chosen p value also known as? Level of significance
8. When does a type one error occur?
reject the null hypothesis and accept the hypothesis
9. When does a type 2 error occur?
retain the null hypothesis even thought the hypothesis is correct
10. Which p value would you use if you were conducting a piece of research that is socially sensitive?
1% (P=0.01) – there is a 1% chance that we wrongly reject the null hypothesis.

36. Levels of measurement
Type of data

37. RECAP: Quiz
Outline the difference between descriptive statistics and inferential statistics?
The null hypothesis predicts that there will be a significant difference? True/false.
Shorthand for the null hypothesis is Ho? True/false
What are Inferential statistics?
Why is it necessary to have a Null hypothesis?

38. 6. If the null hypothesis is retained, this means that the result is…
6. If the null hypothesis is retained, this means that the result is….. 7. What is the chosen p value also known as? 8. When does a type one error occur? 9. When does a type 2 error occur? 10. Which p value would you use if you were conducting a piece of research that is socially sensitive?

39. Why do I need to know about the levels of measurement?
most appropriate descriptive statistic to calculate
which graph to use
which inferential test to use
Levels of measurement relate to quantitative data.

40. Levels of measurement
Nominal (category) data
This is the most simplest method of classifying information.
Involves counting frequency data
We must only be able to place each item/person into one category
Only classifies each person as ‘tall’ or ‘short’; no distinction at all between ‘tall’ people.
Mode is used for >>> Nominal data – as it is category based (we would only want to be able to find out the most common category

41. Levels of measurement
Ordinal data:
This level of measurement involves ranking data into place order, with rating scales often being used to achieve this.
These intervals cannot be considered equal
They do not tell us about distances between positions
We convert raw scores to ranks for statistical testing (1st ,2nd,3rd) and it is the ranks and not the scores that are used in the calculations.
Median and Range
Median is used for >>> Ordinal data  – as it is ranking based (we would only want to know the middle value / piece of data)

42. Levels of measurement
Interval data: Data is defined as being a specific measure, this can be measured on an instrument, there are equal intervals between each piece of data. E.g. We can record the exact temperature using a thermometer. (can be minus) Standardised measurements units like time, weight and temperature are interval data Most informative and accurate form of measurement Increments on the scale can be measured, and they are equidistant. Tell us how many intervals on the scale each person is from anyone else. Mode, Median and Range. Mean and SD if metric Mean is used for >>> Interval data – as it is scaled data (we would only want to know the average reaction time)

43. Activity
Colour code, which statements below refer to each level of measurement
Which level of measurement: Identify whether the data in each statement is nominal, ordinal or interval.
Complete activity C and D.
Levels of measurement in dogs

44. Which type of inferential test should be used?

45. What is the criteria that it depends on?
whether the researcher is testing for differences between groups (experiment) or a correlation between two co- variables.
Level of measurement (nominal, ordinal interval)
Experimental design (independent groups, matched pairs, repeated measures)

46. Can you remember the 7 statistical tests?
The seven tests that you can be asked about (but won’t have to calculate) in the exam: Chi-squared (χ2) Wilcoxon T Mann-Whitney U Spearman’s Rho Unrelated t-test Related t-test Pearson’s r How do you know which test to use? You need to learn the following criteria, but there is no need for you to understand why this is the case

47. LOOKING FOR A CORRELATION REPEATED MEASURES DESIGN
What test to use?
Looking for a difference
LOOKING FOR A CORRELATION
DATA LEVEL
INDEPENDENT
GROUPS DESIGN
REPEATED MEASURES DESIGN
NOMINAL
Chi-square
Sign Test
Chi square
ORDINAL
Mann-Whitney U test
Wilcoxon test
Spearman’s
rho
INTERVAL OR RATIO
Unrelated t test
Related t test
Pearsons r

48. Test of difference or correlation
At Interval level
At Interval level
Nominal or at least ordinal level data?
At ordinal level
Pearson’s r
Repeated measures
Independent groups design
Spearman’s Rho
Related t test
Chi square
Chi can also be association.
Correlation between chewing gum and having nice breadth.
independent groups design?
Repeated measures/matched pairs or independent groups design?
Mann-Whitney U Test
Wilcoxon T
Related t test

49. Chi-Squared
Chi-Squared = nominal data = independent groups design

50. Independent groups Design
Mann-Whitney U Test-
Independent women
Rank first in the charts
Independent groups Design
Ordinal data

51. Wilcoxon T Test
Wilcoxon T Test Repeated measures- At least ordinal (1st in the race)
Cok sits at the front. Repeating movement. Want to come first.

52. Spearmans Rho
There is a correlation between spearmints chewing gum and fresh breath

53. Unrelated t-test
When you are single, you are independent and Unrelated to a partner, so you have an interval from household chores

54. Related t-test
Back with your partner…. The interval is over… Being related to someone else means…. Repeatedly having to do the household chores

55. Pearson’s r
Brighton Pear is correlational to the west pier. The interval between is made up of a pebbly beach and too many tourists in the summer.

56. Test of difference or correlation
At Interval level
At Interval level
Nominal or at least ordinal level data?
At ordinal level
Pearson’s r
Repeated measures
Independent groups design
Spearman’s Rho
Related t test
Chi square
Chi can also be association.
Correlation between chewing gum and having nice breadth.
independent groups design?
Repeated measures/matched pairs or independent groups design?
Mann-Whitney U Test
Wilcoxon T
Related t test

57. Which test to choose. Activity
Have a go at trying to draw the diagram yourself on mini whiteboard.

58. LOOKING FOR A CORRELATION REPEATED MEASURES DESIGN
What test to use?
Looking for a difference
LOOKING FOR A CORRELATION
DATA LEVEL
INDEPENDENT
GROUPS DESIGN
REPEATED MEASURES DESIGN
NOMINAL
Chi-square
Sign Test
Chi square
ORDINAL
Mann-Whitney U test
Wilcoxon test
Spearman’s
rho
INTERVAL OR RATIO
Unrelated t test
Related t test
Pearsons r

59. Exam questions

60. Now you need to justify each test
Fill in the gaps
The Spearman’s Rho was used because the data can be treated as at least 1)_______________ and the researchers were studying a possible 2)_________________ between two co-variables
1 = Ordinal 2 = Correlation (or relationship)

61. Now you need to justify each test
Fill in the gaps
The Chi-Square test was used because the data can be treated as 1)_______________ and the researches had hypothesised that there will be 2)___________________ between conditions when using the 3) _________________________ design.
1 = Nominal 2 = a difference 3 = Independent groups
(please note that the Chi-square is also used as a test of association)

62. Now you need to justify each test
Fill in the gaps
The Wilcoxon T test was used because the data can be treated as 1)_______________ and the researches had hypothesised that there will be 2)___________________ between conditions when using the 3) _________________________ design.
1 = ordinal 2 = a difference 3 = Repeated Measures (please note that the Wilcoxon T is also used for a matched-pairs design)

63. Now you need to justify each test
Fill in the gaps
The Mann-Whitney U test was used because the data can be treated as 1)_______________ and the researches had hypothesised that there will be 2)___________________ between conditions when using the 3) _________________________ design.
1 = ordinal 2 = a difference 3 = independent groups

64. Test your understanding!
Using your newly found knowledge identify the test that would be suitable for the following:
An experiment with nominal data and an independent groups design
Ordinal data on both measures in a study to see if two measures are associated
An experiment with and independent groups design in which the DV is measured on a ordinal scale
A study using a correlational technique in which one measure is interval and the other is ratio.
An experiment in which all participants were tested with alcohol and without alcohol on a memory test
An experiment in which reaction time was tested using an independent subject design

65. ANSWERS
An experiment with nominal data and an independent groups design
chi-squared test
Ordinal data on both measures in a study to see if two measures are associated
Spearman’s rank correlation / Rho
An experiment with and independent groups design in which the DV is measured on a Ordinal scale
Mann-Whitney U test
A study using a correlation technique in which one measure is interval and the other is ratio
Pearsons r
An experiment in which all participants were tested with alcohol and without alcohol on a memory test
Wilcoxon’s T test
An experiment in which reaction time was tested using an independent subject design
Unrelated T-Test