Lecture 2 - Principles of Experimental Designs I

Question 1

What is causation?

Answer 1

When one factor directly affects aother factor

Question 2

What are two important factors to show causation?

Answer 2

• Changing the first thing produces a change in the second
• There is no other possible cause for the change in the second thing (rule out alternatice explanations or hypotheses)

Question 3

What is a population?

Components of an experiment

Answer 3

Members of a specific group, defined by purpose of the experiment

Question 4

What is a sample?

Components of an experiment

Answer 4

Relatively small subset of a population that is selected to represent the population

Question 5

What is a repreentative sample?

Components of an experiment

Answer 5

Characteristics and behaviour of the sample reflect those of the population (insures generalisability)

Question 6

Representative sampling is achieved by…?

Answer 6

Random sampling

Question 7

What is random sampling?

Answer 7

• Members selected in an unbiased manner
• All members have equal chance of selection

Question 8

What are descriptive statistics?

Answer 8

Summaries of the data collected from the sample e.g. averages

Question 9

What are inferential statistics?

Answer 9

Generalises from the sample to the population. How likely the effect that you have obtained in your sample is to actually occur in the population e.g. t-tests

Question 10

What is the dependant variable (DV)?

AKA measured variable

Answer 10

• The measurement taken
• What you record

Question 11

What does operational definition mean?

Answer 11

Specification of how the property of interest will be measured. In many cases there is no direct way to measure what you want e.g. honesty, happiness, intelligence so you need to think about two things

Question 12

What two things do you need to think about for operational definition?

Answer 12

• The property of interest (what you are trying to measure e.g. intelligence)
• The dependent variable (a measureable value that must indirectly reflece the property of intrest e.g. score on IQ test)
  The indirect measure (DV) is the operational definition of your property of interest

Question 13

What is validity?

Answer 13

• A DV is valid if it measures what it is supposed to
• Threat to validity arises from any unintended component that is reflected in a score

Question 14

What is reliability?

Answer 14

• A DV is reliable if, under the same conditions, it gives the same measure, and contains a minimum of measurement error
• Unreliable data reflect error and provide a biased perspective
• If a measure lacks reliability, it also lacks validity

Question 15

What is bias in terms of the DV?

Answer 15

A biased DV is consistently inaccurate in one direction (i.e. always high or always low)

Question 16

What makes a good DV?

Answer 16

• Validity
• Reliability
• Unbiased

Question 17

What are the floor and ceiling effects?

Answer 17

• Ceiling effect is when a task is so easy that all scores are very high
• Floor effect is when a task is so difficult that all scores are very low

Question 18

What is data type?

Answer 18

• The data type determines what sorts of analyses you can perform on your data and the conclusions you can draw
• Data types are associated with different scales of measurement
• The type of scale of measurement dictates the type of conclusion that you can draw

Question 19

What is the ordinal scale?

Answer 19

• Categorises and orders the categories
• Bigger means more
• Distance between points on the scale not considered equal e.g. rugby team standings

Question 20

What is the nominal scale?

Answer 20

• Categorises without ordering
• # s that substitute for names e.g. gender 1 = female, 2 = male

Question 21

What is the interval scale?

Answer 21

• Categorises, orders, and establishes an equal unit of measurement in the scale
• Knowing hoe much more
• Distance between points on the scale considered equal e.g. celsius temperature

Question 22

What is the ratio scale?

Answer 22

• Categorises, orders, establishes an equal unit in the scale, and contains a true zero point
• Allows ratio statements e.g. “twice as big”
• e.g. # of items recalled in a memory task (could be zero recalled)