1. Experiments

2. Types of experiments ‘so far’ Paired comparison Happy experiment watching Goon video Two independent groups Different treatments for each group: Historical experiment ‘Scurvy’; Balance: eyes open, eyes closed; pencil in teeth or lips. Control – Treatment: Red Hammer experiment

3. This is not inference We are not making an inference about a population from a sample we have taken. The main objective is causal i.e. We wish to find evidence that any effect observed between treatment groups can be linked to the treatment effect and is not a characteristic of the individuals in the group i.e. not due to chance acting alone.

4. Ideas discussed Random allocation to groups. Random assignment does not guarantee that the groups are "matched" or equivalent, only that any significant differences are due to chance. Controlling variables; keeping all other factors the same as far as is possible Problem has a context Extensions to the experiment Implications or usefulness of the result

5. Hiding the true intent of the experiment; pencil experiment, red hammer Not knowing what group you are in: Blind experiment Researcher and groups not knowing what group people are in: Double blind Not knowing what the experiment is about

6. Notes from the Achievement Standard Carry out investigations of phenomena, using the statistical enquiry cycle: conducting experiments using experimental design principles seeking explanations using informed contextual knowledge, exploratory data analysis, and statistical inference communicating findings and evaluating all stages of the cycle Make inferences from surveys and experiments: using methods such as randomisation to assess the strength of the evidence

7. Achieved Conduct an experiment to investigate a situation using experimental design principles involves showing evidence of using each component of the investigation process. It doesn’t say with research but “using informed contextual knowledge” means no research = no grade

8. Merit Conduct an experiment to investigate a situation using experimental design principles, with justification involves linking components of the process of investigating a situation by experiment to the context, explaining relevant considerations in the investigation process, and supporting findings with statements which refer to evidence gained from the experiment.

9. Excellence Conduct an experiment to investigate a situation using experimental design principles, with statistical insight involves integrating statistical and contextual knowledge throughout the investigation process, and may include reflecting about the process; discussing how possible sources of variation were dealt with during the design phase; considering other relevant variables.

10. The process of investigating a situation by experiment using experimental design principles involves: posing an investigative question about a given experimental situation

11. The process of investigating a situation by experiment using experimental design principles involves: planning the experiment using experimental design principles selecting experimental units determining treatment and response variables determining allocation of treatments to experimental units determining data collection and recording methods considering other sources of variation

12. The process of investigating a situation by experiment using experimental design principles involves: conducting the experiment collecting data recording any issues that arise

13. The process of investigating a situation by experiment using experimental design principles involves: selecting and using appropriate displays and summary statistics

14. The process of investigating a situation by experiment using experimental design principles involves: making an appropriate formal statistical inference (it isn’t an inference)

15. The process of investigating a situation by experiment using experimental design principles involves: communicating findings in a conclusion.

16. It isn’t inference even though the standard says it is – this will probably be upgraded Carry out investigations of phenomena, using the statistical enquiry cycle: conducting experiments using experimental design principles seeking explanations using informed contextual knowledge, exploratory data analysis, and statistical inference communicating findings and evaluating all stages of the cycle Make inferences from surveys and experiments: using methods such as randomisation to assess the strength of the evidence

17. Experimental Design

18. Comparison and control Most experiments are carried out to see whether a treatment causes an effect on a phenomenon (response). In order to see the effect of a treatment, the treatment group needs to be compared fairly to a group that receives no treatment (control group). If an experiment is designed to test a new treatment then a control group can be a group that receives an existing or established treatment.

19. Randomisation A randomising method should be used to allocate individuals to groups to try to ensure that all groups are similar in all characteristics apart from the treatment received. The larger the group sizes, the better the balancing of the characteristics, through randomisation, is likely to be.

20. Randomisation This is not the same as random sampling. When we take a random sample from a population, we are only selecting some of the population. When we randomly allocate to groups, we are using all of our participants or objects, and they end up in one group or the other.

21. Variability A well-designed experiment attempts to minimise unnecessary variability. The use of random allocation of individuals to groups reduces variability among the groups, as does larger group sizes. Keeping experimental conditions as constant as possible also restricts variability.

22. Replication For some experiments it may be appropriate to carry out repeated measurements. Taking repeated measurements of the response variable for each selected value of the explanatory variable is good experimental practice because it provides insight into the variability of the response variable.

23. Experiment What can you do to make yourself look older?

24. Experiment What can you do to make yourself look older? Why is it important to be able to estimate a person’s age? What jobs require a good ability to estimate age?

25. What can you do to make yourself look older? Clothes. Wear a suit. Style of hair Length of hair Makeup Colour of lipstick

26. Why is it important to be able to estimate a person’s age? Language of conversation. Work- related i.e. are they underage?

27. What jobs require a good ability to estimate age? Supermarket Tellers Human resources Police Bouncers Customs Retailing Tourism

28. Stroop test

29. What has to be constant?