1. Research Methods Chapter 14 pages 463-493

2. Measures of Central Tendencies Descriptive statistics that summarise data by identifying a score that suggests the location of the middle of the range of score. For example: if you are aware of how short or tall you are compared to all your friends then you have a good sense of what a measure of central tendency is.

3. Measures of central tendencies indicate the value of the centre of the distribution in three ways. 1.Mean (average) 2.Median (middle number when the numbers are placed in order from highest to lowest) 3.Mode (the most commonly occurring score)

4. Calculating the Mean, Median and Mode Data Set: 15,12,18,13,16,11,20,16,14,17,15,9,15,19 Mean: Add up all the numbers then divide by how many numbers there are. Data set =210 210 divided by 14= 15 (mean) Median: Arrange scores from lowest to highest 9,11,12,13,14,15,15,15,16,16,17,18,19,20 Middle number is 15 (median) Mode: The number that occurs the most= 15

5. Measures of Variability Along with measures of central tendencies measures of variability also describe the data. It describes the spread of scores in the data set. How far apart or close they are.

6. Variability Variability is expressed as a range (describes the spread of scores by subtracting the lowest from the highest score. Lowest score:10 Highest score:80 Range=

7. Variance This is also a measure of variability. It indicates to what extent all scores in the data set depart from the mean. How far the numbers are from the expected value (mean) How far away the numbers are from the mean (middle)

8. Standard Deviation Another measure of variability that indicates to what extent on average each score in the data set departs from the mean. A large SD =widely dispersed scores. Low SD= most scores are clustered around the mean. Each colour is a standard deviation. It can go from the left to the right of the mean which is the middle number (peak)

9. Distributions Distribution of data can either be; Normal: bell shaped curve. Scores arrange symmetrically. Mean, median and mode coincide in the centre. Very few scores at either extreme.

10. Distributions Skewed: asymmetrical shape. Hump on one side and a tail on the other. Can be negatively or positively skewed. Positively skewed distributions have more lower scores Negatively skewed distributions have more higher scores.

11. Distributions Bimodal: symmetrical frequency distribution with the two most frequently occurring scores on either side of the mean and median.

12. Reliability and Validity To draw meaningful conclusions from the results of a test the data must be reliable and valid. Reliability: the ability to produce consistent results. Test is reliable over time.. Validity: the test measures what it is meant to measure.

13. Reliability How to establish Reliability 1.Test-retest: comparing the results of the same test administered twice. 2.Inter-rater: comparing the scores of different expert assessors. 3.Parallel Forms: comparing the results of two subsets of the test items administered to the same participants. 4.Internal Consistency: comparing the scores of two halves of a test administered to the same participants.

14. Validity How to establish validity: 1.Content: judging whether the items on the test are appropriate for what you intend to measure. 2.Criterion-related: is the behaviour consistent with what is supposed to be measured. 3.Construct: the correlation between similar constructs. 4.External: can the results be generalised to the population/other situations

15. Cultural Bias Measuring devices must be culturally appropriate so that the results aren’t compromised by cultural bias (inability of a person to fully assess another individual due to cultural differences. For example there are two different English exams in year 12. The normal VCE one and an ESL one so those students from another culture are not disadvantaged.

16. Standardised and Non-Standardised Tests Standardised Test: a strictly administered test based on established norms that accurately position individuals within a population. Based on established population norms Reliable and valid Administered in controlled conditions Objectively assessed. If it does not comply with these requirements then it is a NON-Standardised test.

17. Experimental Research Characteristics of a psychological experiment include deliberately manipulating one variable (IV) to observe a change in another (DV). This is known as a cause and effect relationship because one variable directly influences the other. Experiments are conducted in laboratory settings.

18. Variables in Experiments Independent Variable: It is the experimental treatment and is manipulated by the experimenter. Dependent Variable: It is the variable that is expected to change in a predicted way due to the IV. It “depends” on the IV to change. This is what we measure. Extraneous Variable: any unwanted variable (participant or environment) that may influence the DV. Anything that changes in the environment that is not part of the experiment Confounding Variable: is an extraneous variable that has influenced the DV and now cannot be distinguished from the IV. Any variable (within the experiment or extraneous) that confuses the results.

19. Experiments are conducted in laboratory settings so the experimenter can control any irrelevant variables. He can therefore reduce or eliminate them.

20. Control and Experimental Groups Once your sample is selected you need to divide the sample into 2 groups. 1)Control: the group that provides a comparison measure for the experimental group. The control group has no experimental treatment. Not exposed to the IV. 2)Experimental: undergoes the experimental treatment. Given the IV. To determine if the effect of the IV on the experimental group is significant enough descriptive statistics (mean, median, mode) are calculated and compared.

21. Statistical Significance. The difference between the scores of the experimental and control group must be significantly significant in order to say that the IV caused an effect on the DV and that it was not caused by chance. If it is significantly significant then a cause- effect relationship has occurred. The IV caused a change in the DV.

22. Experimental research Experiments require: Participants are randomly allocated (lottery method or table of random numbers) to the experimental or control group. IV is applied to experimental group DV is measured. Cause and effect relationship is expected

23. Operational Hypothesis In an experiment your hypothesis (educated guess of what you predict to happen) needs to be operationalised. This means that the two variables (IV and DV) need to be described in terms of how they will be administered and measured You must include: Population of interest IV DV The direction. (will something increase or decrease as a result of the IV.)

24. Hypothetical Experiment Research question: Video games increase aggressive behaviour. How would we construct a hypothesis? Remember it needs to be operationalised...

25. It is hypothesised that boys aged between 8 and 10 years old from Thomastown West Primary school who play violent video games for half an hour every day for a week will display significantly more aggressive behaviours than boys who have played non violent video games. IV: video games (violent/non violent) DV: amount of aggressive behaviour SAMPLE: 8-10 yr old boys from TWPS

26. What would be the control and experimental group?

27. Control: boys playing non violent video games for 30min a day Experimental: Boys playing violent video games for 30min a day. How would the experimenter determine who goes in each group? What method of random allocation?

28. How can we control for other variables that may influence the dependent variable?

29. Conditions should be identical for each group Location should be the same Time of day Type of food and drinks consumed before hand

30. Measuring the dependent variable How are we going to measure aggressive behaviour?

31. Behaviour of both groups need to be observed and recorded.

32. Is there a cause and effect relationship? If there is a difference in the behaviour of the boys. If the boys who played the violent video game are significantly more aggressive then the boys who played the non violent game then there is a cause and effect relationship. The hypothesis is therefore supported.

33. Drawing conclusions From your results can you draw any conclusions?

34. It can now be concluded that there is evidence that boys exposed to violent video games were influenced to behave aggressively.

35. Making Generalisations Can your results be generalised?

36. Only if the sample is representative of the population.

37. What we have done.. 1.Identified a research question and population 2.Made a hypothesis 3.Selected a sample 4.Allocated the sample into either a control or experimental group 5.Applied the IV to the experimental group 6.Measured the DV in both groups 7.Compared what was measured in both groups 8.Checked to see if it was significant and if the hypothesis was confirmed 9.Conclusions were made 10.Generalisations were made.

38. Empirical Research Report/Activity ERA Once you have conducted your experiment you are to write it up in an ERA format

39. Homework 14.2 all 14.4 all 14.7 questions 1,2,3,4 14.8 alll