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PSY4051 > Full_Module_3_Flashcards_Research_Strategies_ANOVA > Flashcards

Full_Module_3_Flashcards_Research_Strategies_ANOVA

1
Q

What is ANOVA?

A

ANOVA (Analysis of Variance) is a statistical test used to compare the means of three or more groups.

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2
Q

Why is ANOVA used instead of multiple t-tests?

A

ANOVA controls for Type I error that increases when performing multiple t-tests.

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3
Q

When is a one-way independent-measures ANOVA used?

A

It is used when comparing the means of three or more independent groups on one factor.

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4
Q

What are the assumptions of ANOVA?

A

ANOVA assumes normality, homogeneity of variances, and independent observations.

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5
Q

What does the F-ratio represent in ANOVA?

A

The F-ratio compares between-group variance to within-group variance. A higher F-ratio suggests significant differences between groups.

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6
Q

What does a significant p-value (<0.05) in ANOVA mean?

A

A significant p-value means there is a statistically significant difference between at least two group means.

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7
Q

What is the effect size in ANOVA and why is it important?

A

Effect size (e.g., η²) shows the magnitude of the difference between groups. It is important to interpret practical significance, not just statistical significance.

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8
Q

How do you handle violations of homogeneity of variance in ANOVA?

A

If the assumption of homogeneity is violated, you can use a Welch ANOVA or transform the data.

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9
Q

What are post-hoc tests?

A

Post-hoc tests are conducted after a significant ANOVA to determine which specific group means are different.

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10
Q

Why are post-hoc tests necessary after ANOVA?

A

Post-hoc tests control for Type I error when making multiple comparisons between group means.

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11
Q

Give an example of a post-hoc test.

A

Examples include Tukey’s HSD, Bonferroni correction, and Scheffé test.

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12
Q

How do you interpret post-hoc test results?

A

Look for pairwise comparisons with p-values less than 0.05 to identify which groups differ significantly.

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13
Q

What are planned comparisons in ANOVA?

A

Planned comparisons test specific hypotheses developed before data collection about group differences.

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14
Q

When would you use planned comparisons?

A

Use them when you have specific predictions about the differences between certain group means.

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15
Q

How are contrast weights used in planned comparisons?

A

Contrast weights assign values to group means based on hypothesized relationships, focusing the comparison on specific groups.

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16
Q

How do you interpret planned comparisons?

A

Interpret planned comparisons by looking at the contrast weights, F-ratio, p-value, and effect size.

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17
Q

What is trend analysis in ANOVA?

A

Trend analysis examines patterns of change (e.g., linear or quadratic trends) across levels of the independent variable.

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18
Q

Why would a researcher perform a trend analysis?

A

Trend analysis helps identify systematic increases or decreases in the dependent variable across different groups.

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19
Q

When is trend analysis appropriate?

A

It is appropriate when you expect a specific pattern or trend across ordered levels of a variable (e.g., time, dosage).

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20
Q

How do you interpret trend analysis results?

A

You interpret significant trends by looking for systematic patterns in the data (e.g., a linear or quadratic trend).

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21
Q

What is the Mann-Whitney U test?

A

The Mann-Whitney U test is a non-parametric test used to compare two independent groups when the data are not normally distributed.

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22
Q

When should the Mann-Whitney U test be used?

A

It should be used when data are ordinal or not normally distributed and the assumptions of the independent t-test are violated.

23
Q

How do you interpret the results of a Mann-Whitney U test?

A

If the p-value is less than 0.05, there is a significant difference in the ranks of the two groups.

24
Q

What is the Wilcoxon Signed-Ranks test?

A

The Wilcoxon Signed-Ranks test is a non-parametric test used to compare two related groups (e.g., pre-test vs post-test) when data are not normally distributed.

25
Q

When should the Wilcoxon Signed-Ranks test be used?

A

It should be used when comparing two related groups and the assumptions of the paired-samples t-test are violated.

26
Q

How do you interpret the results of the Wilcoxon Signed-Ranks test?

A

A significant p-value (<0.05) indicates a significant difference between the two paired samples.

27
Q

What is the Kruskal-Wallis test?

A

The Kruskal-Wallis test is a non-parametric test used to compare three or more independent groups when the assumptions of ANOVA are violated.

28
Q

When should the Kruskal-Wallis test be used?

A

It should be used when comparing three or more independent groups with ordinal or non-normally distributed data.

29
Q

How do you interpret the Kruskal-Wallis test results?

A

A significant p-value (<0.05) means that at least one group differs from the others. Post-hoc tests can then be performed.

30
Q

What are confidence intervals, and why are they important?

A

Confidence intervals provide a range of values within which the true population parameter is likely to fall. They show the precision of an estimate.

31
Q

How do sample size and confidence intervals relate?

A

Larger sample sizes lead to narrower confidence intervals, indicating more precise estimates of the population parameter.

32
Q

What is statistical power, and why is it important?

A

Statistical power is the probability of detecting a true effect. High power reduces the likelihood of a Type II error.

33
Q

How can researchers increase statistical power?

A

Researchers can increase power by increasing sample size, using stronger manipulations, or setting a higher alpha level.

34
Q

What is the relationship between sample size and statistical power?

A

Larger sample sizes increase statistical power, making it more likely to detect a significant effect if it exists.

35
Q

What is the goal of experimental research?

A

The goal of experimental research is to establish cause-and-effect relationships through manipulation of variables.

36
Q

What are the key elements of experimental research?

A

Key elements include manipulation of an independent variable, control of extraneous variables, and random assignment to conditions.

37
Q

What is a quasi-experimental design?

A

A quasi-experimental design involves manipulation of an independent variable but lacks random assignment, leading to potential confounding variables.

38
Q

What are single-case research designs?

A

Single-case research designs focus on the intensive study of a single individual or small group over time.

39
Q

What is a developmental research design?

A

Developmental research designs study how people change over time, typically using longitudinal or cross-sectional methods.

40
Q

What is a one-way independent-measures ANOVA?

A

A one-way independent-measures ANOVA compares the means of three or more independent groups on one factor.

41
Q

What are post hoc tests?

A

Post hoc tests are conducted after a significant ANOVA to determine which specific group means differ.

42
Q

What is a trend analysis?

A

A trend analysis checks for systematic increases or decreases in the dependent variable across ordered levels of the independent variable.

43
Q

What are contrast weights in planned comparisons?

A

Contrast weights are assigned values that represent specific hypotheses about group differences in a planned comparison.

44
Q

How do you interpret a significant planned comparison result?

A

If the p-value is less than 0.05, it means that the specific group differences being tested are statistically significant.

45
Q

What are the different types of sampling techniques?

A

Types of sampling include random, stratified, cluster, and convenience sampling.

46
Q

What is statistical power?

A

Statistical power is the probability of correctly rejecting a false null hypothesis. High power reduces the likelihood of a Type II error.

47
Q

What factors increase statistical power?

A

Increasing sample size, improving measurement precision, and increasing the effect size can all boost statistical power.

48
Q

What is the difference between Type I and Type II errors?

A

A Type I error is rejecting a true null hypothesis, while a Type II error is failing to reject a false null hypothesis.

49
Q

How do you interpret confidence intervals?

A

A 95% confidence interval means that there is a 95% chance the interval contains the true population parameter. Narrower intervals indicate more precise estimates.

50
Q

What is the Mann-Whitney U test?

A

The Mann-Whitney U test is a non-parametric test used to compare two independent groups when the data are not normally distributed.

51
Q

What are the conditions for using the Mann-Whitney U test?

A

Use this test when the assumptions of an independent t-test (normality, interval data) are violated.

52
Q

What is the Wilcoxon Signed-Ranks test?

A

The Wilcoxon Signed-Ranks test is used to compare two related samples when the assumptions of the paired t-test are violated.

53
Q

How do you interpret the results of the Wilcoxon Signed-Ranks test?

A

A significant p-value (<0.05) indicates a significant difference between the two related samples.

54
Q

How do you interpret the results of non-parametric tests?

A

Look for a p-value less than 0.05 to determine if the difference between groups or samples is significant.

PSY4051 (6 decks)

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