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Stats revision

Caitlin Leahy Englisch 55 Karten

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  1. 1Univariate ANOVAsUsed to reduce error rates and avoid false positives (type 1s); we can see if there is an overall difference
  2. 2How do we avoid a type 1 error?Correct the P value (normally through Bonferroni), but could increase the possibility of false negatives
  3. 3Between-Subjects ANOVAUsed when need to explore 3+ independent conditions on a single variable; tells us overall condition, not what conditions differ from each other
  4. 4What do you need to run a Between-Subjects ANOVA?Normally distributed data (interval/ratio data) and homogeneity of Variance
  5. 5Do we want Levene's to be sig or non-sig?Non-significant, it means we have H of V
  6. 6What effect does a small sample have on the effect size?Effect size will be bigger
  7. 7How do we correct this?Run a Bonferroni
  8. 8What graphs would you use to represent unrelated groups and which for mixed designs?Simple bar chart for unrelated, clustered for mixed
  9. 9What does it mean if the error bars are tight?Low variance
  10. 10What is standard error?Measure of spread
  11. 11What does it mean if 2 separate bars don't don't overlap?There is a significant difference
  12. 12What is Cohen's D used for?Used to compare the magnitude of differences between 2 means
  13. 13If you have a Cohen's D of 0.2+ but less than 0.5 what effect size do we have?Small Effect
  14. 14If you have a Cohen's D of 0.5+ but less than 0.8 what effect size do we have?Medium Effect
  15. 15If you have a Cohen's D of 0.8+ what effect size do we have?Large Effect (can be as much as 1)
  16. 16What are Pearson's Correlation Coeffients?0.1 - 0.3 = small
    0.3 - 0.5 = medium
    0.5 + = large
  17. 17When is a One Way Within Subjects ANOVA used?When there is a single within subjects variable with 3+ levels
  18. 18What does a One Way Within test?Whether differences in scores between the within subjects conditions are higher than differences between scores due to chance factors and controlling for ind diffs
  19. 19What would you do instead if you only had 2 levels?Paired Samples t-test
  20. 20What would you do instead if the data was non-parametric?Friedman test
  21. 21What assumptions do you need to meet before you run the ANOVA?Normally distributed data (ratio or interval data) and sphericity
  22. 22What is sphericity?Equality in differences of variances between IV levels
  23. 23Would we have sphericity if you only had 2 levels?Yes, sphericity is automatically assumed
  24. 24Do we want Mauchley's test to be significant or non-significant?Non-significant
  25. 25What is a MANOVA?Multivariate Analysis Of VAriance
  26. 26When would we use a MANOVA?When you have 1 IV and many DVs
  27. 27What's the problem with having many DVs?You increase the probability of having a type 1 error
  28. 28How do you reduce the possibility of having a type 1 error?Only use 1 test
  29. 29What does a MANOVA assessIf an IV has an overall effect on variables
  30. 30How does a MANOVA assess this?Using a single P value to see which specific aspects affect the result
  31. 31What assumptions does a MANOVA have?The usual ANOVA assumptions (normally distributed data, interval or ratio, H of V)
  32. 32Can a MANOVA be within subjects?No, its always between
  33. 33What is Box's test?Equality in covariance matrices- only presents a problem when it is <.001
  34. 34If we have 2 levels of an IV do we need to do post-hocs?No
  35. 35What do we use if 1 variable does not show equality of variance?Use Tanhane's T2
  36. 36What is an ANCOVA?ANalysis of CO-VAriance
  37. 37What are covariates?Variables that associate with the DV but are not part of the experimental manipulation
  38. 38Why could they be an issue?We don't want them to interact with the IV
  39. 39Why are co-variates used?To reduce within group error variance (more likely to find a significant effect of manipulation and eliminate confounds)
  40. 40What assumptions do we have?Usual ANOVA assumptions (Normally distributed data, interval or ratio data, H of V); independence of covariate and IV effect; independence of covariate and homogeneity of regression slopes
  41. 41How do we get make sure we have homogeneity of regression slopes?We run an ANOVA on the covariate and want there to be a non-significant result
  42. 42What is homogeneity of regression slopes?The relationship between the covariate and DV is constant across all groups
  43. 43What happens with a Complex Between subjects design?If there is more than 1 IV, then we can expect there to be an interaction
  44. 44How can you see if there is an interaction when the data is presented graphically?Lines converge, diverge or cross
  45. 45If you have a large sample, would you have greater or smaller power?Greater
  46. 46What assumptions need to be met?Normally distributed data; interval/ratio data; H of V
  47. 47What will happen in SPSS if you get a significant interaction?It won't compute post hoc tests for pairwise comparisons within the interaction
  48. 48When do we use a Complex Within Subjects ANOVA?When we have more than 1 IV
  49. 49Do all participants have to contribute a score in every condition?Yeah
  50. 50What assumptions need to be met?Normally distributed data; ratio/interval data; sphericity (which is checked for main effects and interactions)
  51. 51When do we need sphericity?When we have 3+ levels
  52. 52How do we conduct post hocs?Use the syntax method within SPSS or use a series of T-Tests
  53. 53When do we use mixed ANOVAs?When we have within and between subjects IVs
  54. 54What assumptions need to be met?Usual ANOVA assumptions (normally distributed data; interval or ratio data; H of V; sphericity; equality of covariance matrices)
  55. 55How would you conduct post-hocs?Paired samples T-tests, conducting them separately for each condition

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Beschreibung
Semester 1 Stats revision Y2 UOL
Erstellt von
Caitlin Leahy
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