Learning Goal: I'm working on a r exercise and need an explanation and answer to help me learn.Suppose I have a large dataset, comprising data over 10,000 patients with height values ranging from 55 to 75 inches, adn weight values ranging from 80 to 250 pounds. Consider a subset of data corresponding to the 2,500 patients with height between 60 and 65 inches. Suppose the variance of the full data set is σ^2/f, and the variance of the subset is σ^2/s. What do we know about σ^2/f in relation to σ^2/sσ^2/s ≤ σ^2/f
σ^2/s = σ^2/f
σ^2/s ≥ σ^2/f
None of the above are necessarily true
Consider the regression of Weight (dependent variable) as a function of Height (Independent variable). How do we interpret the intercept?This always indicates the Weight for a zero-Height individual
This always indicates the Height for a zero-Weight individual
Both explanation are true (i.e. always a zero-Height, zero-Weight individual)
Neither explanation is true (i.e. never a zero Weight, nor a zero-Height individual)
The LM function itself will not yield, in its output display, the P=values for the various aspects of linear regression. If you want to see the P-values, what R function will you need? AIC
BOX-COX
Breusch-Pagan Plot
Circle of Powers
Greedy
Linear Transformation
Log-Linear Plot
Log-Transform
Logistic Regression
Poisson Regression
Other________
A Scatter not of raw data, but of the raw data de-trended from it’s regression (Review Again)AIC
BOX-COX
Breusch-Pagan Plot
Circle of Powers
Greedy
Linear Transformation
Log-Linear Plot
Log-Transform
Logistic Regression
Poisson Regression
Other________
The R Function we would use to superimpose a regression line on top of an existing scatter plot. AIC
BOX-COX
Breusch-Pagan Plot
Circle of Powers
Greedy
Linear Transformation
Log-Linear Plot
Log-Transform
Logistic Regression
Poisson Regression
Other________
Requirements: 1-2