17 Questions
What does a correlation coefficient (r) of 1 indicate?
Perfect positive association
When is the assumption of normal bivariate distribution rarely met?
When the sample size is small
What does the Spearman Rank Correlation measure?
Strength of association considering the order
In correlation analysis, which factor can influence the correlation coefficient?
Presence of outliers
What does a correlation coefficient (r) of 0 indicate?
No association
What does the absolute value of the correlation coefficient (|r|) represent?
The strength of linear association
What is the formula for the Spearman rank correlation coefficient?
ρ = 1 - (6Σd²)/(n(n²-1))
What does the Spearman rank correlation coefficient measure?
Monotonic relationship
What is the purpose of the partial correlation coefficient?
To measure the unique variance between two variables without the influence of a third variable’s variance
Which hypothesis is tested in the significance test for correlation coefficient?
Ho: ρ=0 vs Ha: ρ≠ 0 (two-tailed)
How is the rejection of the null hypothesis determined using a t-test for correlation coefficient?
|t| > tα/2, n-2
What does the p-value signify in statistical significance testing?
The probability of observing a sample statistic as extreme as the test statistic, assuming that the null hypothesis is true
What does a p-value of 0.03 indicate in statistical significance testing?
The result is statistically significant at α = 0.05 level
What is the purpose of a nonparametric Monte Carlo Randomization test?
To test for relationships between variables without making distributional assumptions
What do degrees of freedom represent in statistical testing?
The number of restrictions on variability within a sample
How are critical values used in statistical testing?
To determine whether to reject or fail to reject the null hypothesis
What do you use a t table for in statistical testing?
To find critical values for hypothesis testing using t-distribution
This quiz introduces the concept of correlation analysis and simple linear regression, exploring the strength of relationship between two variables with examples like rainfall and wind speed. It covers the calculation of Pearson correlation coefficient and understanding the strength of association.
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