Week 8 - Sources of error in experimental research

Question 1

What is an unsystematic error?

Answer 1

Random error (also called unsystematic error, system noise or random variation) has no pattern. One minute your readings might be too small. The next they might be too large. You can’t predict random error and these errors are usually unavoidable.

Question 2

What is a systematic error?

Answer 2

Systematic error occurs when an observed or calculated value deviates from the true value in a consistent way.

Question 3

What are the two main sources of bias we need to control for?

Answer 3

1) Extraneous variables
2) Confounding variables

Question 4

What is an extraneous variable?

Answer 4

These are extra variables that also could influence the dependent variable that you do not want to influence the dependent variable

Question 5

What is a confounding variable?

Answer 5

A confounding variable is a third variable that influences both the independent and dependent variables.

Question 6

What is the difference between extraneous variables and confounding variables?

Answer 6

An extraneous variable is any variable that you’re not investigating that can potentially affect the dependent variable of your research study. A confounding variable is a type of extraneous variable that not only affects the dependent variable, but is also related to the independent variable.

Question 7

Are extraneous variables a systematic error or unsystematic error?

Answer 7

Unsystematic error

Question 8

How is random error important in significance testing?

Answer 8

Probability tells us if it is significant or not. Controlling for extraneous variables gives you a higher signal to noise ratio and helps you see the effect you are interested in

Question 9

How can you combat unsystematic errors?

Answer 9

1) Create a more powerful manipulation (e.g., increase the dosage of nicotine administered)

2) Test a larger number of people

3) Using a matched pairs design

4) Situational variables - to control for possible participant variables that could add noise to the data. You can specify inclusion and exclusion criteria

5) Power - Random error is always there; however, you can try to overcome it by making sure that your experiment has enough power to find differences between the conditions. Power is the probability of not making a type 2 error

Question 10

What is Power?

Answer 10

The probability of correctly rejecting the null hypothesis

Question 11

What does it mean if a study has high power?

Answer 11

The higher the power the less likely it is that we will miss a false negative

Question 12

What are the ways of increasing the power of your experiment?

Answer 12

1) More participants - Testing more participants will increase the power of the experiment. The random error will also ‘even out’ with more participants. Ensuring you have the appropriate number of participants will mean you are less likely to make a type 2 error.

2) Sensitive measurement - Try to choose a measurement that accurately represents the whole range of possible scores. If task too easy then there will be no difference between the groups. If task too hard than there will be no difference between groups

3) Experimental design - Some designs have more power than others. This is mainly because they control for extraneous and confounding variables differently. In independent measures designs individual differences can have a large impact on the data because they vary between our experimental conditions. In repeated measures the participants essentially control for this because they do both conditions. In matched pairs these differences are partially controlled but not completely

4) Statistical test - Parametric statistics have more power than non-parametric statistics.

Question 13

If a memory task is too easy that most participants get nearly all of the correct answers correct than we won’t find any differences. What is this called?

Answer 13

Ceiling effect

Question 14

If a test is too difficult that nearly everyone gets no correct answers or only a few answers correct. What is this called?

Answer 14

Floor effect

Question 15

Are extraneous variables a systematic error or unsystematic error?

Answer 15

Systematic

Question 16

What is a systematic error?

Answer 16

This is where we have a systematic bias between our two conditions which might affect our results (Make it appear that there is a difference when there isn’t one)

Question 17

How do you control for a systematic error?

Answer 17

1) Standardisation - To ensure environmental conditions do not systematically vary between groups

2) Randomisation - To ensure participants are split between groups without bias

3) Counterbalancing - To avoid order (practice or fatigue) effects

4) Blind design - To prevent the participants and researchers from confounding your results

Question 18

What is a quasi experiment?

Answer 18

• Not a true experiment, meaning the researcher is not able to directly manipulate the independent variable. In a quasi experiment, this is because the researchers select an IV that is based on a pre-existing difference between participants (e.g., age or gender). Consequently, the researchers are unable to randomly allocate participants to either condition.
• Conditions are irrelevant. Don’t mention controlled or naturalistic.

Question 19

What is a natural experiment?

Answer 19

Not a true experiment, meaning the researcher is not able to directly manipulate the independent variable. In a natural experiment, participants are allocated to a particular condition by a naturally occurring event. This means an event that would have happened without the researcher’s influence (e.g., before and after a GCSE exam could be 2 conditions in a natural experiment, with the exam being a naturally occuring event as the researcher didn’t organise the exam). Consequently, the researchers are unable to randomly allocate participants to either condition.

Conditions are irrelevant. Don’t mention controlled or naturalistic.

Question 20

What is an advantage of using a Quasi or Natural experiment?

Answer 20

• These are more naturalistic experiments allowing us to compare conditions that would be unethical to manipulate

Question 21

What is a disadvantage of using Quasi and Natural experiments?

Answer 21

It is difficult to control for extraneous or confounding variables because they may have been naturally occurring as a product of belonging to that group