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Forest Biometrics Exam 2 Questions and
Answers 100% Pass
Regression analysis - Answer✔To study the relationship between X and Y we perform
Regression: - Answer✔the statistical or mathematical relationship between the independent
variable (X) and a dependent variable (Y) while considering certain constants or parameters
dependent varible - Answer✔The quantity being estimated through regression is called the
independent variable - Answer✔is measured in order to predict the dependent variable
scatter diagrams - Answer✔One way to examine the x and y relationship is through
Once the X,Y points are plotted, the diagram can be analyzed to see if a ------ forms. -
Answer✔pattern
The simplest relationship is called a ---- ---- ---- which is also called a straight line relationship -
Answer✔simple linear regression
There is an assumption, for each -- value a distribution for the -- values will occur with each
observation of i, at observation -- there will be an observation at -- - Answer✔X, Y ..... Yi, Xi
1
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linear model equation - Answer✔Y^=A + BX
prediction equation - Answer✔an equation suggested by the points of a scatter plot that is used
to predict other points
is a way for us to get the estimates needed, in other words values for a and b - Answer✔least
squares
So what do we need for least squares? - Answer✔1. Estimates of A and B by using a and b
2. We use the estimates of a and b in the prediction equation Y^= a + bX
3. Get estimates of a and b variances 4. Test hypothesis 5. Set confidence intervals 6. And on
occasion, estimate Y for a given value of X
Least Squares allows us to get the best - Answer✔unbiased estimates
So for every observed Yi there is a predicted value of --, equal to (a + bXi ) which corresponds to
a location on the regression line - Answer✔Y^i
(yi-y^i) - Answer✔is the deviation of the observed Y from the predicted Y^
sum(Yi-Y^)2 - Answer✔The sum of squares of all the deviations form the fitted line :
Since we know Y^ = a + bX, we can substitute for Y^ in the formula to get: - Answer✔sum(Yi - a -
bXi ) 2
When a and b have been found their numerical values (using the previous two formulas and the
data) for the two estimators a and b can be substituted into the - Answer✔prediction equation
Y^ = a + bX
2
Forest Biometrics Exam 2 Questions and
Answers 100% Pass
Regression analysis - Answer✔To study the relationship between X and Y we perform
Regression: - Answer✔the statistical or mathematical relationship between the independent
variable (X) and a dependent variable (Y) while considering certain constants or parameters
dependent varible - Answer✔The quantity being estimated through regression is called the
independent variable - Answer✔is measured in order to predict the dependent variable
scatter diagrams - Answer✔One way to examine the x and y relationship is through
Once the X,Y points are plotted, the diagram can be analyzed to see if a ------ forms. -
Answer✔pattern
The simplest relationship is called a ---- ---- ---- which is also called a straight line relationship -
Answer✔simple linear regression
There is an assumption, for each -- value a distribution for the -- values will occur with each
observation of i, at observation -- there will be an observation at -- - Answer✔X, Y ..... Yi, Xi
1
, ©JASONMcCONNELL 2025 ALL RIGHTS RESERVED
linear model equation - Answer✔Y^=A + BX
prediction equation - Answer✔an equation suggested by the points of a scatter plot that is used
to predict other points
is a way for us to get the estimates needed, in other words values for a and b - Answer✔least
squares
So what do we need for least squares? - Answer✔1. Estimates of A and B by using a and b
2. We use the estimates of a and b in the prediction equation Y^= a + bX
3. Get estimates of a and b variances 4. Test hypothesis 5. Set confidence intervals 6. And on
occasion, estimate Y for a given value of X
Least Squares allows us to get the best - Answer✔unbiased estimates
So for every observed Yi there is a predicted value of --, equal to (a + bXi ) which corresponds to
a location on the regression line - Answer✔Y^i
(yi-y^i) - Answer✔is the deviation of the observed Y from the predicted Y^
sum(Yi-Y^)2 - Answer✔The sum of squares of all the deviations form the fitted line :
Since we know Y^ = a + bX, we can substitute for Y^ in the formula to get: - Answer✔sum(Yi - a -
bXi ) 2
When a and b have been found their numerical values (using the previous two formulas and the
data) for the two estimators a and b can be substituted into the - Answer✔prediction equation
Y^ = a + bX
2
