Variables,Designs and Hypothesis

Question 1

What are levels/factors of a variable

Answer 1

different measures e.g. test after 1 hour, test after 4 hours. or how many cups of coffee had before a memory test etc

Question 2

what is nominal (categorial) data

Answer 2

mutually exclusive
not necessarily any order
categories
cannot do any meaningful calculations

Question 3

what is ordinal (ranking data

Answer 3

numbers indicate a position/rank in a list
rank is meaningful
dont have to be equally spaced

Question 4

what is interval data

Answer 4

difference between 2 values is meaningful

no meaningful zero

Question 5

what is ratio data

Answer 5

same as interval but has a meaningful zero point

can say ‘twice as big’

Question 6

what makes a nuiscance variable different from a confounding variable

Answer 6

introduces noise but doesnt systematically bias the data in any way - confounding variables make systematic biases

Question 7

whats an experimental hypothesis

Answer 7

question/theory we wish to address in experiments

Question 8

whats a statistical hypothesis

Answer 8

precise statement about the data to be collected - null and alternate

Question 9

talk about the null hypothesis H0

Answer 9

says basically there is no relationship. is our default unless we can accept the alternate hypothesis

Question 10

what might a alternative hypothesis be called

Answer 10

H1 or HA

Question 11

describe the relationship between the null and alternate hypothesis

Answer 11

mutually exclusive - only one can be true

exhaustive - cover all outcomes in the experiment

Question 12

when do we reject the null hypothesis

Answer 12

when the probability of null hypothesis being true (p) is less than some criterion (a)

Question 13

how do we calculate p

Answer 13

we calculate p using a test statistic

p is the probability of collecting this data if the null hypothesis is true (basically the probability that the effect we measured is down to chance)