1. Statistics in psychology
Describing and analyzing the data from your IA

2. Process of research in Ψ 1
A research question based on previous research → aim and hypothesis (experiment)
Choice of method to test hypothesis (Experiment)
Data collection

3. Process of research in Ψ: These are what you should be able to do according to IBO
Describe results (descriptive stats)
Analyze results → in experiments we want to know the probability that results are due to manipulation of IV (inferential stats)
Interpret results
Discuss results in the light of previous studies
Outline possible future areas of research

4. Data Raw data (what comes out of data collection)
Levels of measurement of data:
Nominal: discrete categories → e.g. the number of people who helped or not
Ordinal: Measurements that can be ranked or put in position but intervals unknown → she came in first, he came second etc.
Interval and ratio: measurements based on scales → temperature (interval) and time in seconds (ratio)

5. Levels of data: nominal (categories)
Which shows do you watch regularly?
We can put these into categories.
So lets try it….

6. Levels of Data: ordinal (placed in order)
How can we transform this in Ordinal data?
These can be put in order… in order of favorite
So lets try it…

7. Levels of ratio/interval data
A level of measurement where units of equal measurements (a scale with equal intervals) are used e.g. minutes, kilograms …etc.
Ratio data is on a scale, but has a true zero eg weight/height, time, distance.

8. Levels of data: interval/ratio
How can we transform this in ratio or interval data?
We can measure and compare the exact time because the intervals on the ruler are equal.
So lets try it…

9. Descriptive Stats
Each of you need to calculate and present ONE measure of central tendency and ONE measure of Dispersion
Each of these ‘choices’ needs to be justified
See samples and rubric for more details

10. Descriptive statistics Not all stats can be applied to all levels of data
Mode : most frequent score (nominal data)
Median: middle value when scores are placed in rank order (ordinal data)
Mean: average value of all scores (interval and ratio data)

13. Descriptive Results: What to write…
E: Results: Descriptive
There are no results or the results are irrelevant to the stated hypotheses of the student’s experimental study. Relevant descriptive statistics have not been applied to the data. There is no graphing of data. 1
Results are stated and accurate and reflect the hypotheses of the research. Descriptive statistics (one measure of central tendency and one measure of dispersion) are applied to the data, but their use is not explained. The graph of results is not accurate, is unclear or is not sufficiently related to the hypotheses of the study. Results are not presented in both words and tabular form. 2
Results are clearly stated and accurate and reflect the hypotheses of the research. Appropriate descriptive statistics (one measure of central tendency and one measure of dispersion) are applied to the data and their use is explained. The graph of results is accurate, clear and directly relevant to the hypotheses of the study. Results are presented in both words and tabular form.

14. INFERENTIAL Stats (HL ONLY)
Each of you need to calculate and present ONE Statistical Test
Your ‘choice’ needs to be justified
The Results of your test should allow you to accept/reject your hypothesis
See samples and rubric for more details

15. INFERENTIAL STATS
For HL, you need to determine the appropriate statistical test and apply it to your data.
P Value = <.05 - If your P value is less than the chosen significance level then you reject the null hypothesis i.e. accept that your sample gives reasonable evidence to support the alternative hypothesis. It does NOT imply a "meaningful" or "important" difference; that is for you to decide when considering the real-world relevance of your result.
If the hypothesis contains a prediction the test is one-tailed, If the hypothesis is non directional the test is two-tailed
Type I error: we accept a hypothesis that is not true (our test is not tight enough)
Type II error: We reject a hypothesis that is true (our test is too tight)

16. Inferential Statistics
So.....got that?
Use the diagram on the following slide to help you decide which test to do:

17. Inferential Statistics

18. Just plug it in…
This website lets you use the tests (click on the correct one and input your data): 
If you choose to use the above website, be sure to screen shot all results and include in the appendix.
Also, be sure to place a properly formatted full reference to the cite on your Works Cited page

19. Inferential Results: What to write…
F: Results: Inferential
No appropriate inferential statistical test has been applied. 1
An appropriate inferential statistical test has been chosen, but not properly applied. 2
An appropriate inferential statistical test has been chosen and explicitly justified. Results of the inferential statistical test are not complete or may be poorly stated. 3
An appropriate inferential statistical test has been chosen and explicitly justified. Results of the inferential statistical test are accurately stated. The null hypothesis has been accepted or rejected appropriately according to the results of the statistical test. A statement of statistical significance is appropriate and clear.

20. You will have two class days to complete this work and tie up any loose ends regarding your data collection and experiment. D Block: Friday, October 13 (end of class) G Block: Monday October 16 (end of class) ***NOTE: We will begin a new unit (Human Relationships)on Monday/Tuesday of the following week. Be prepared to quickly transition back into a normal course structure