statistical tests

Question 1

what is nominal data?

Answer 1

represented in categorical forms - categorical data
e.g. male and female
discrete data = item can only appear in one category

Question 2

what is ordinal data

Answer 2

• ordered in some way e.g. rating scale - unit not at equal intervals
  e. g. 1st, 2nd, 3rd
• lacks precision as ordering is subjective
• unsafe data - raw scores need converting into ranks to use in the test

Question 3

what is interval data?

Answer 3

• based on numerical scales with equal units (precisely defined)
• uses public scales of measurement e.g. stopwatch, thermometer, weighing scales - producing data based on accepted units of measurement
• most precise and sophisticated level of data

Question 4

what are inferential tests and how can we use them

Answer 4

• try to infer from the sample data what the population might think
• allow psychologists to draw conclusions from their findings
• these conclusions are based on probability that a particular pattern of results could have arisen by chance or not
• findings not due to chance = significant

Question 5

what probability do psychologists use and why?

Answer 5

• 95% means there is a 5% chance of results occurring if null hypothesis is true
• probability of 5% recorded as p

Question 6

equal to or less than

Answer 6

• probability should be equal to or less than 5%

- meaning there is a 5% chance that is it not significant

Question 7

if results are significant which hypothesis do you accept/reject

Answer 7

reject null

accept alternative

Question 8

what are critical values

Answer 8

numerical boundary between acceptance and rejection of null hypothesis

Question 9

what is the degree of freedom

Answer 9

n-1

Question 10

what is a type 1 error

Answer 10

false positive
incorrect rejection of null hypothesis - need to accept instead
optimistic error - claiming to have found significant results when they are not
most likely if significance level is too lenient e.g. 0.05

Question 11

what is a type 2 error

Answer 11

false negative
incorrectly accepted null
pessimistic error - claiming to have found insignificant results
most likely if significance level too stringent e.g. 0.01 which is why 0.05 is accepted in most cases

Question 12

what do we need to know about our data in order to tell whether we have significance

Answer 12

level of measurement
type of hypothesis
experimental design