H
happycow
When doing a multiple regression in excel, what are the meaning of thes
out puts (that's are all in the same table)
the fist column has my dependent variable which is labeled her
"Intercept" and the independent variables, X2, X3, X4, X5
the second columns labeled "Coefficients" i think this column has th
slope values of each independent variable; X2, X3, X4, and X5. Thes
slope variables are in relation to all the other variables, so th
slope of X2 is effected by by X3, X4 and X5. These slope values are th
measure of how each independent variable effects the dependent variable
I'm guessing this allows me to predict where added data will go in th
correlation. So for example if I want to predict how a film will do (m
regression has to do with film gross) according to this data, i woul
multiple my variables from that movie (budget (X2), first weekend gros
(X3), users ratings(X4) and MPPA rating (X5)) to the correspondin
Coefficients values in this column. If what i am saying is right (or a
least partially right), i don't know what the value of Intercept is for
since is from the dependent variable, it shouldn't have a slope value.
The second column which is labeled "Standard Error" I'm guessing (i
what I am saying above the coefficients values are right) is th
accuracy of the predications that can be made. I'm guessing the large
the number the bigger the error.
The fourth column which is labeled "t Stat" i have no clue what i
means and how it contributes to my regression. I'm thinking it's som
type of testing but i don't understand what it's testing and why.
The fifth column which is labeled "P-value" is again something I don'
understand. I think it has to do something with "t-Stat". My othe
theory is that it has to do something with probability. I really don'
know though.
The next two columns labeled "Lower 95%" and "Upper 95%", i believ
this is the limits of my correlations. I think that this allows one t
say that "i am 95% sure that the predicted data that lies between thes
lowers and uppers can be predicted by the accuracy of my the values i
my "coefficients" column.
I also am wondering about the graph outputs, the first graph "Line Fi
Plot" outputs 4 scatter diagrams for each of my 4 independen
variables. the graphs looks like their comparing my dependent variabl
(on the y axis) to a independent variable on the x axis. Is this jus
showing the correlation and relationship of each independent variabl
to the dependent variable. For each individual diagram, Is th
comparison being made and liner relationship (the direction the line
seem to be going; positive, negative or none) based on just th
independents variable and the dependent variable, or is the independen
variable's slope taking into account the other 3 independent variables?
The second graph; the "Residual Plot Graph", does this show the measur
of stand error for each point? and the closer to 0 a point gets th
lesser the error
out puts (that's are all in the same table)
the fist column has my dependent variable which is labeled her
"Intercept" and the independent variables, X2, X3, X4, X5
the second columns labeled "Coefficients" i think this column has th
slope values of each independent variable; X2, X3, X4, and X5. Thes
slope variables are in relation to all the other variables, so th
slope of X2 is effected by by X3, X4 and X5. These slope values are th
measure of how each independent variable effects the dependent variable
I'm guessing this allows me to predict where added data will go in th
correlation. So for example if I want to predict how a film will do (m
regression has to do with film gross) according to this data, i woul
multiple my variables from that movie (budget (X2), first weekend gros
(X3), users ratings(X4) and MPPA rating (X5)) to the correspondin
Coefficients values in this column. If what i am saying is right (or a
least partially right), i don't know what the value of Intercept is for
since is from the dependent variable, it shouldn't have a slope value.
The second column which is labeled "Standard Error" I'm guessing (i
what I am saying above the coefficients values are right) is th
accuracy of the predications that can be made. I'm guessing the large
the number the bigger the error.
The fourth column which is labeled "t Stat" i have no clue what i
means and how it contributes to my regression. I'm thinking it's som
type of testing but i don't understand what it's testing and why.
The fifth column which is labeled "P-value" is again something I don'
understand. I think it has to do something with "t-Stat". My othe
theory is that it has to do something with probability. I really don'
know though.
The next two columns labeled "Lower 95%" and "Upper 95%", i believ
this is the limits of my correlations. I think that this allows one t
say that "i am 95% sure that the predicted data that lies between thes
lowers and uppers can be predicted by the accuracy of my the values i
my "coefficients" column.
I also am wondering about the graph outputs, the first graph "Line Fi
Plot" outputs 4 scatter diagrams for each of my 4 independen
variables. the graphs looks like their comparing my dependent variabl
(on the y axis) to a independent variable on the x axis. Is this jus
showing the correlation and relationship of each independent variabl
to the dependent variable. For each individual diagram, Is th
comparison being made and liner relationship (the direction the line
seem to be going; positive, negative or none) based on just th
independents variable and the dependent variable, or is the independen
variable's slope taking into account the other 3 independent variables?
The second graph; the "Residual Plot Graph", does this show the measur
of stand error for each point? and the closer to 0 a point gets th
lesser the error