4. Lesson 10: Statistics
* Define descriptive statistics
* Define inferential statistics
* Describe the types of statistics in Psychology:
- calculate measures of central tendency including mean,
median and mode
-interpret p-values and draw conclusions
-evaluate research in terms of generalizing the findings to
the population
What you need to know and be able to do
Saturday, 20 April 13
5. Generalising Results
To be able to generalise results, the following criteria
must be met:
The results show statistical significance (p<0.05)
All sampling procedures were appropriate
All experimental procedures were appropriate
All measures were valid
All possible confounding variables were controlled.
Saturday, 20 April 13
6. Types of Statistics
In psychology there are two types of
statistics
1) Descriptive Statistics, show results
2) Inferential Statistics, explains results in
relation to hypotheses.
Saturday, 20 April 13
7. Descriptive statistics
Test A -1,7,22,66,4,3,55,44,5,6,78,789,23,1,23,
Test B -67,43,67,678,33,21,45,76,89,09,3,3,23,
Who would you describe this data?
Saturday, 20 April 13
8. Descriptive statistics
Descriptive statistics are used to summarise,
organise and describe data obtained from research
Test A -1,7,22,66,4,3,55,44,5,6,78,789,23,1,23,
Test B -67,43,67,678,33,21,45,76,89,09,3,3,23,
Who would you describe this data?
Saturday, 20 April 13
9. Descriptive Statistics
1) Percentages
2) Measures of central tendency
3) Spread of scores
4) Measures of Variability
5) Graphs and tables (Later in the AOS)
Saturday, 20 April 13
10. Calculating the
percentage
Number of times score occurs DIVIDED BY
Total number of scores in data set
MULTIPLIED BY 100
E.G. The percentage of rolling a 6 would be:
13/80 = 0.1625 x 100 = 16.25%
Saturday, 20 April 13
11. Tells us how the data are clustered near the central
point of the dataset.
There are three measures of central tendency
1) Mean - average of all the scores (calculated by
adding up all the scores and dividing that total by the
number of scores)
2) Median - the score that occurs exactly halfway
between the lowest and the highest score.
3) Mode - the most commonly occurring score in the
dataset.
2) Measures of Central Tendency
(Measures in the Bell Curve)
Saturday, 20 April 13
13. 3) Spread of scores
Another way of describing data is by looking at
how the scores are spread. This is known as
variability. This can be done by
Range - The range of data can be calculated by
subtracting the lowest score from the highest
score
Standard deviation - How far is each individual
piece of data from the mean. A low standard
deviation indicates the scores cluster around the
mean
Saturday, 20 April 13
14. Complete Check your understanding questions on
page 23 (RM book) - 10 min
Saturday, 20 April 13
15. Inferential Statistics
Inferential Statistics are used once the descriptive
statistics have identified there is a difference
(variation) from the mean. (Read page 30 of RM book)
What next is to determine if this difference or
variance is significant, or is it just due to chance.
Inferential tests give a probability that the difference
is caused by chance.
This is expressed as a p value.
Generally the lower the p value the better, however
p<0.05 (that is 5 times in 100 or 5% of the time it is
due to chance) is widely accepted.
Saturday, 20 April 13
16. p = 0.03 means there are 3 chances in 100 (3%)
that this difference would be achieved by chance
alone.
If the level of significance is p<0.05 then these
results can be said to be statistically significant as it
is less then (<) 0.05
If the p value = 0.3 then the results are not
significant as 0.3 is greater then 0.05.
Saturday, 20 April 13
