Bivariate analysis

Which statistical approach is suitable for analyzing the relationship between continuous outcome and binary predictor?

• Pearson's correlation coefficient

• Independent sample t-test

• Chi-square test

• Spearman's rank correlation

What is the primary purpose of performing a one-way ANOVA?

• To compare means of multiple independent groups

  
  

• To determine the correlation coefficient

  
  

• To analyze the distribution of a categorical variable

  
  

• To examine the association between two continuous variables

  
  

When should non-parametric tests be used instead of parametric tests?

• When the data are normally distributed

  
  

• When the sample size is small

  
  

• When outliers are present in the data

  
  

• When the data have a symmetric distribution

  
  

Based on this output, what can we conclude about the data?

• There is a statistically significant difference btw pre-/post-scores.

  
  

• There is no statistically significant difference btw pre-/post-scores.

  
  

• The mean difference between the pre- and post-scores is exactly 0.809.

  
  

• The sample size for this analysis is 29.

  
  

Based on the output provided, which pairwise comparison(s) show a statistically significant difference?

• Group B and Group C

  
  

• Group B and Group D

  
  

• Group C and Group D

  
  

• All of the above

Which statistical test is appropriate for comparing means of two related samples?

• Independent sample t-test

  
  

• Chi-square test

  
  

• Paired sample t-test

  
  

• Two-way ANOVA

  
  

What is the purpose of using post hoc tests after conducting a one-way ANOVA?

• To determine the sample size required for the study

  
  

• To identify the specific groups that differ significantly from each other

  
  

• To estimate the effect size of the relationship

  
  

• To check the assumptions of normality and homogeneity of variance

  
  

In a correlation analysis, if the correlation coefficient is -0.92, what can we conclude?

• There is a strong positive relationship between the variables.

  
  

• There is no relationship between the variables.

  
  

• The correlation coefficient cannot be negative.

  
  

• There is a strong negative relationship between the variables.

  
  

Which of the following statements accurately describes the Bonferroni correction in statistical analysis?

• The Bonferroni correction is a method used to estimate the effect size in a study.

• The Bonferroni correction is a technique used to determine if the sample size is adequate for statistical analysis.

• The Bonferroni correction is a procedure that adjusts the p-values to account for multiple comparisons.

• The Bonferroni correction is a strategy employed to identify outliers in a dataset.