PUB561 Module 4 UPDATED ACTUAL Questions and
CORRECT Answers
What is needed to be able to use correlation or - you need the data for both variables to be continuous
regression? What is a hint that tells you that correlation
can be used? - if the data can be meaningfully portrayed on a scatter plot then you can use
correlation
What does correlation measure? - correlation measures the magnitude of the association between 2 variables
What does Pearson's correlation coefficient detect? - can detect a linear association between two variables
What is the symbol for Pearson's correlation - denoted by r if estimated from a sample
coefficient?
- true population parameter is p
What values does Pearson's correlation coefficient - takes values between -1 and +1 inclusive
take? What do these values indicate?
- values of r close to -1 or +1 indicate a strong linear association (-1 = negative
relationship so as one variable increases the other decreases) (+1 = positive
relations so as one variable increases so does the other)
- values of r close to zero indicate little linear association between variables
How would you set up hypotheses for Pearson's - conclusion: there is a significant linear correlation if p-value <0.05
correlation?
What correlation coefficient can be used if the - Spearman's correlation coefficient
relationship between two variables is not linear? - must be a monotonic relationship
, What does a monotonic relationship between two - always increasing OR always decreasing but doesn't need to be by the same
variables look like? rate
What does a non-monotonic relationship between two - relationship both increases and decreases
variables look like?
Does evidence of correlation always mean that a cause - no
and effect relationship exists? Why or why not?
- there may be an unobserved variable that can be the hidden cause of the
observed effect
What does regression measure? - regression measures the magnitude of dependence of one variable upon
another
What are the requirements for the variables if using - want to find the relationship between the independent (X) and dependent
linear regression? variable (Y)
- both variables are continuous so you can plot as a scatter plot
- want to determine the straight line that best "fits" the data
Linear regression models express Y as a _____ of X Linear regression models express Y as a linear function of X
What is the formula for the simple linear regression
model?
What are the main steps in linear regression analysis? 1) estimate the regression equation (the 'model')
2) assess the model and test hypothesis regarding whether X explains Y
- model significance
- explanatory power (R2)
- mode validity (assumptions)
3) if the model is good, predict dependent variable from values of the
independent variable (optional)
Linear regression equation: - the y-intercept
What is b0? - the value of Y when X = 0
Linear regression equation: - the regression coefficient (slope of the line)
What is b1? - how much Y changes for a one unit change in X
CORRECT Answers
What is needed to be able to use correlation or - you need the data for both variables to be continuous
regression? What is a hint that tells you that correlation
can be used? - if the data can be meaningfully portrayed on a scatter plot then you can use
correlation
What does correlation measure? - correlation measures the magnitude of the association between 2 variables
What does Pearson's correlation coefficient detect? - can detect a linear association between two variables
What is the symbol for Pearson's correlation - denoted by r if estimated from a sample
coefficient?
- true population parameter is p
What values does Pearson's correlation coefficient - takes values between -1 and +1 inclusive
take? What do these values indicate?
- values of r close to -1 or +1 indicate a strong linear association (-1 = negative
relationship so as one variable increases the other decreases) (+1 = positive
relations so as one variable increases so does the other)
- values of r close to zero indicate little linear association between variables
How would you set up hypotheses for Pearson's - conclusion: there is a significant linear correlation if p-value <0.05
correlation?
What correlation coefficient can be used if the - Spearman's correlation coefficient
relationship between two variables is not linear? - must be a monotonic relationship
, What does a monotonic relationship between two - always increasing OR always decreasing but doesn't need to be by the same
variables look like? rate
What does a non-monotonic relationship between two - relationship both increases and decreases
variables look like?
Does evidence of correlation always mean that a cause - no
and effect relationship exists? Why or why not?
- there may be an unobserved variable that can be the hidden cause of the
observed effect
What does regression measure? - regression measures the magnitude of dependence of one variable upon
another
What are the requirements for the variables if using - want to find the relationship between the independent (X) and dependent
linear regression? variable (Y)
- both variables are continuous so you can plot as a scatter plot
- want to determine the straight line that best "fits" the data
Linear regression models express Y as a _____ of X Linear regression models express Y as a linear function of X
What is the formula for the simple linear regression
model?
What are the main steps in linear regression analysis? 1) estimate the regression equation (the 'model')
2) assess the model and test hypothesis regarding whether X explains Y
- model significance
- explanatory power (R2)
- mode validity (assumptions)
3) if the model is good, predict dependent variable from values of the
independent variable (optional)
Linear regression equation: - the y-intercept
What is b0? - the value of Y when X = 0
Linear regression equation: - the regression coefficient (slope of the line)
What is b1? - how much Y changes for a one unit change in X
