GROUP 7_HYPOTHESIS TEST FOR CORRELATION

In a hypothesis test for correlation, what is the null hypothesis (H0) typically stating?

• There is a significant correlation between the variables.

• There is no correlation between the variables.

•  The sample correlation coefficient is equal to 1.

• The sample correlation coefficient is equal to -1.

What does a Pearson correlation coefficient (r) of -1 indicate regarding the relationship between two variables?

•  A strong positive linear relationship. 

• A strong negative linear relationship.

•  No linear relationship.

•  A proportional relationship.

f the critical region is t greater than or equal to

3.3554 or t is less than or equal to -3.3554 and the computed value of t is 7.79, the null hypothesis is ____________.

• Accepted since the computed value lies in the critical region.

• Rejected since the computed value of t is greater than the 3.3354.

• It is neither accepted nor rejected.

• None of these are correct.

In a correlation hypothesis test, if the p-value is less than the chosen significance level (alpha), what is the appropriate action?

• Fail to reject the null hypothesis.

• Reject the null hypothesis in favor of the alternative.

•  Increase the sample size.

• Perform a two-sample t-test

In a correlation hypothesis test, if the calculated correlation coefficient (r) is close to -1, what does it indicate about the relationship between the variables?

• A strong positive correlation.

• A strong negative correlation.

• No correlation.

•  A weak positive correlation.

When determining whether the population correlation (ρ) is "close to zero" or significantly different from zero, which statistics are commonly used in correlation analysis?

•  Mean and standard deviation.

• Mode and range.

•  Sample correlation coefficient (r) and sample size (n).

• Median and interquartile range.

The association between the two variables has been observed and may be generalized to the target population.

• Level of significance

• Correlation coefficient, n

• Null Hypothesis

• Correlation coefficient, r

What is the main objective in correlation analysis? 

• To establish a cause-effect relationship between two variables.

• To determine and quantify the extent of variation between two quantitative variables.

• To identify high and low correlation values.

• To prove that all relationships between variables are linear.

Which statement is true regarding high correlation coefficient (r) values?

• High r values always indicate a cause-effect relationship.

• The interpretation of high or low r values is entirely objective. 

  
  

•  High r values imply a strong linear relationship between variables.

• High r values are only relevant for qualitative variables.

What is a common misconception about the correlation coefficient (r)?

• High r values always indicate a cause-effect relationship.

• Low r values suggest a strong linear relationship.

• The interpretation of high or low r values is purely objective.

•  The primary objective of correlation analysis is to establish causation.