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5.0
forest biometrics exam 2 Questions with Detailed
Verified Answers (100% Correct Answers) /Already
Graded A+
regression analysis
Ans: To study the relationship between X and Y we perform
Regression:
Ans: the statistical or mathematical relationship between the independent
variable (X) and a dependent variable (Y) while considering certain
constants or parameters
dependent varible
Ans: The quantity being estimated through regression is called the
independent variable
Ans: is measured in order to predict the dependent variable
scatter diagrams
Ans: 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.
Ans: pattern
Sunday, 02 March 2025
,The simplest relationship is called a ---- ---- ---- which is also called a
straight line relationship
Ans: 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 --
Ans: X, Y ..... Yi, Xi
linear model equation
Ans: Y^=A + BX
prediction equation
Ans: 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
Ans: least squares
So what do we need for least squares?
Ans: 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
Examstudy - Stuvia US
, 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
Ans: 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
Ans: Y^i
(yi-y^i)
Ans: is the deviation of the observed Y from the predicted Y^
sum(Yi-Y^)2
Ans: 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:
Ans: 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
Examstudy - Stuvia US
In today's fast-paced educational landscape, students need reliable resources to excel in their studies.
5.0
forest biometrics exam 2 Questions with Detailed
Verified Answers (100% Correct Answers) /Already
Graded A+
regression analysis
Ans: To study the relationship between X and Y we perform
Regression:
Ans: the statistical or mathematical relationship between the independent
variable (X) and a dependent variable (Y) while considering certain
constants or parameters
dependent varible
Ans: The quantity being estimated through regression is called the
independent variable
Ans: is measured in order to predict the dependent variable
scatter diagrams
Ans: 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.
Ans: pattern
Sunday, 02 March 2025
,The simplest relationship is called a ---- ---- ---- which is also called a
straight line relationship
Ans: 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 --
Ans: X, Y ..... Yi, Xi
linear model equation
Ans: Y^=A + BX
prediction equation
Ans: 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
Ans: least squares
So what do we need for least squares?
Ans: 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
Examstudy - Stuvia US
, 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
Ans: 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
Ans: Y^i
(yi-y^i)
Ans: is the deviation of the observed Y from the predicted Y^
sum(Yi-Y^)2
Ans: 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:
Ans: 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
Examstudy - Stuvia US
