within subject design

Question 1

T-Tests

Answer 1

• Is variance between conditions larger than variance within
  -How likely are we to obtain the difference between conditions if the null hypothesis is true/due to chance?

Question 2

within- subject design

Answer 2

• ppts take part in all conditions
• Your score in RM VS SPID

Question 3

within Subject Design -pos

Answer 3

• more powerful : each ppt is there own control (no indiv differences)
• can test fewer ppts : time + cost effective
• preferred when looking at effects over time

Question 4

within- subject design negative

Answer 4

• order effects
• may suffer drop-out

Question 5

matched pairs design

Answer 5

• ppts matched on important characteristics
• each pair matched + scores compared (within)
• one person per condition (between)
• Benefits of within + between subject designs
• No order effects + indiv differences accounted for
• Difficult + time consuming to match

Question 6

Paired samples T - Tests

Answer 6

• used to compare means of 2 conditions
• within subject matched pairs design

Question 7

Paired T- Test Assumptions

Answer 7

• Data are interval/ ratio (continuous)
• N at least 12
• Differences normally distributed

Question 8

Testing normality

Answer 8

• calculate differences between the 2 conditions
• Test normality using Shapiro- Wilk Test
• should be non- significant ( p > 0.05)

Question 9

Reporting results of paired T-Test

Answer 9

• On average _ as shown in Figure belon. The data met the assumptions for paired samples t-test which revealed _ ( t ( df) = _ , p < )

Question 10

Assumptions not met for paired sample T-test

Answer 10

Wilcoxon signed Ranks test for related samples