Use the following linear regression equation to answer the questions.
x1 = 1.1 + 3.0x2 –
8.4x3 + 2.3x4
(a) Which variable is the response variable?
x3
x1
x2
x4
Which variables are the explanatory variables? (Select all that
apply.)
x1
x2
x3
x4
(b) Which number is the constant term? List the coefficients with
their corresponding explanatory variables.
constant = | |
x2 coefficient= | |
x3 coefficient= | |
x4 coefficient= |
(c) If x2 = 4, x3 = 10, and
x4 = 6, what is the predicted value for
x1? (Use 1 decimal place.)
(d) Explain how each coefficient can be thought of as a "slope"
under certain conditions.
If we hold all other explanatory variables as fixed constants, then we can look at one coefficient as a "slope."
If we look at all coefficients together, each one can be thought of as a "slope."
If we look at all coefficients together, the sum of them can be thought of as the overall "slope" of the regression line.
If we hold all explanatory variables as fixed constants, the intercept can be thought of as a "slope."
Suppose x3 and x4 were held
at fixed but arbitrary values and x2 increased
by 1 unit. What would be the corresponding change in
x1?
Suppose x2 increased by 2 units. What would be
the expected change in x1?
Suppose x2 decreased by 4 units. What would be
the expected change in x1?
(e) Suppose that n = 13 data points were used to construct
the given regression equation and that the standard error for the
coefficient of x2 is 0.391. Construct a 95%
confidence interval for the coefficient of x2.
(Use 2 decimal places.)
lower limit= | |
upper limit = |
(f) Using the information of part (e) and level of significance
10%, test the claim that the coefficient of x2
is different from zero. (Use 2 decimal places.)
t= | |
t critical ± | = |
Conclusion
Reject the null hypothesis, there is sufficient evidence that ?2 differs from 0.
Reject the null hypothesis, there is insufficient evidence that ?2 differs from 0.
Fail to reject the null hypothesis, there is insufficient evidence that ?2 differs from 0.
Fail to reject the null hypothesis, there is sufficient evidence that ?2 differs from 0.
Explain how the conclusion of this test would affect the regression
equation.
If we conclude that ?2 is not different from 0 then we would remove x3 from the model.If we conclude that ?2 is not different from 0 then we would remove x4 from the model.
If we conclude that ?2 is not different from 0 then we would remove x1 from the model.If we conclude that ?2 is not different from 0 then we would remove x2 from the model.
Answer :
A) response variable = x1, it is the variable where the value calculated as a response from input is stored.
Explanatory variable : x2,x3 and x4. These are independent variables system is having.
B) constant term : 1.1
Coefficient of x2 = 3.0
Coefficient of x3 = -8.4
Coefficient of x4= 2.3
C) given x2 = 4, x3 = 10 and x4 = 6: then using given equation
X1 = 1.1 + 3.0*4 - 8.4*10+2.3* 6. = -57.1
D) If we hold all other explanatory variables as fixed constants, then we can look at one coefficient as a "slope."
Example : if x3 and x4 are zero that is de =0 and x4=0 than the coefficient of x2 will be the slope of the line and this is valid in all the other cases also.
If x3 and x4 are constant and de is increase by 1, then the x1 will get increase by the factor equals to coefficient of x2.
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