Predicting maximum yield using R linear regression output
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I have a question in a paper that involves calculating the maximum yield based on a linear model in which yield is explained by the amount of something being transported plus the number of days it is being transported for (plus an intercept). The thing is being transported for at least 3 days and not more than 10, and the amount is a fixed value.
There is a negative coefficient for days and a positive one for amount. Both are significant in the presence of each other (as well as the intercept).
The R output is provided, so it includes the estimate of coefficient, the standard error, the T value and the Pr(>|t|) value.
How do you approach this? My initial thought was that, given that there is a negative coefficient for days, that it would be the maximum at 3 days - as each day passes the yield would decrease. But then I had second thoughts about this. Should I be taking the standard error into account? If so, how? Would prediction/confidence intervals be possible? I don't think so because I don't know the value of $n$, but someone else might know better!
statistics regression confidence-interval
asked Jan 19 at 18:32
Maths BarryMaths Barry
438
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add a comment |
$begingroup$
I have a question in a paper that involves calculating the maximum yield based on a linear model in which yield is explained by the amount of something being transported plus the number of days it is being transported for (plus an intercept). The thing is being transported for at least 3 days and not more than 10, and the amount is a fixed value.
There is a negative coefficient for days and a positive one for amount. Both are significant in the presence of each other (as well as the intercept).
The R output is provided, so it includes the estimate of coefficient, the standard error, the T value and the Pr(>|t|) value.
How do you approach this? My initial thought was that, given that there is a negative coefficient for days, that it would be the maximum at 3 days - as each day passes the yield would decrease. But then I had second thoughts about this. Should I be taking the standard error into account? If so, how? Would prediction/confidence intervals be possible? I don't think so because I don't know the value of $n$, but someone else might know better!
statistics regression confidence-interval
asked Jan 19 at 18:32
Maths BarryMaths Barry
438
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$begingroup$
You want to use the output to decide if the coefficients are significant. Although the coefficient is negative it could be that it is not significantly different from zero. (Look at the t-value).
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– user121049
Jan 19 at 19:30
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Can you copy-paste the output?
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– V. Vancak
Jan 20 at 5:54
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The T values all say that the coefficients and the intercept are highly significant (99.9%).
$endgroup$
– Maths Barry
Jan 20 at 8:31
add a comment |
$begingroup$
I have a question in a paper that involves calculating the maximum yield based on a linear model in which yield is explained by the amount of something being transported plus the number of days it is being transported for (plus an intercept). The thing is being transported for at least 3 days and not more than 10, and the amount is a fixed value.
There is a negative coefficient for days and a positive one for amount. Both are significant in the presence of each other (as well as the intercept).
The R output is provided, so it includes the estimate of coefficient, the standard error, the T value and the Pr(>|t|) value.
How do you approach this? My initial thought was that, given that there is a negative coefficient for days, that it would be the maximum at 3 days - as each day passes the yield would decrease. But then I had second thoughts about this. Should I be taking the standard error into account? If so, how? Would prediction/confidence intervals be possible? I don't think so because I don't know the value of $n$, but someone else might know better!
statistics regression confidence-interval
asked Jan 19 at 18:32
Maths BarryMaths Barry
438
$endgroup$
I have a question in a paper that involves calculating the maximum yield based on a linear model in which yield is explained by the amount of something being transported plus the number of days it is being transported for (plus an intercept). The thing is being transported for at least 3 days and not more than 10, and the amount is a fixed value.
There is a negative coefficient for days and a positive one for amount. Both are significant in the presence of each other (as well as the intercept).
The R output is provided, so it includes the estimate of coefficient, the standard error, the T value and the Pr(>|t|) value.
How do you approach this? My initial thought was that, given that there is a negative coefficient for days, that it would be the maximum at 3 days - as each day passes the yield would decrease. But then I had second thoughts about this. Should I be taking the standard error into account? If so, how? Would prediction/confidence intervals be possible? I don't think so because I don't know the value of $n$, but someone else might know better!
statistics regression confidence-interval
statistics regression confidence-interval
asked Jan 19 at 18:32
Maths BarryMaths Barry
438
asked Jan 19 at 18:32
Maths BarryMaths Barry
438
edited Jan 20 at 22:16
Maths Barry
asked Jan 19 at 18:32
Maths BarryMaths Barry
438
asked Jan 19 at 18:32
Maths BarryMaths Barry
438
asked Jan 19 at 18:32
Maths BarryMaths Barry
438
438
$begingroup$
You want to use the output to decide if the coefficients are significant. Although the coefficient is negative it could be that it is not significantly different from zero. (Look at the t-value).
$endgroup$
– user121049
Jan 19 at 19:30
$begingroup$
Can you copy-paste the output?
$endgroup$
– V. Vancak
Jan 20 at 5:54
$begingroup$
The T values all say that the coefficients and the intercept are highly significant (99.9%).
$endgroup$
– Maths Barry
Jan 20 at 8:31
add a comment |
$begingroup$
You want to use the output to decide if the coefficients are significant. Although the coefficient is negative it could be that it is not significantly different from zero. (Look at the t-value).
$endgroup$
– user121049
Jan 19 at 19:30
$begingroup$
Can you copy-paste the output?
$endgroup$
– V. Vancak
Jan 20 at 5:54
$begingroup$
The T values all say that the coefficients and the intercept are highly significant (99.9%).
$endgroup$
– Maths Barry
Jan 20 at 8:31
$begingroup$
You want to use the output to decide if the coefficients are significant. Although the coefficient is negative it could be that it is not significantly different from zero. (Look at the t-value).
$endgroup$
– user121049
Jan 19 at 19:30
$begingroup$
You want to use the output to decide if the coefficients are significant. Although the coefficient is negative it could be that it is not significantly different from zero. (Look at the t-value).
$endgroup$
– user121049
Jan 19 at 19:30
$begingroup$
Can you copy-paste the output?
$endgroup$
– V. Vancak
Jan 20 at 5:54
$begingroup$
Can you copy-paste the output?
$endgroup$
– V. Vancak
Jan 20 at 5:54
$begingroup$
The T values all say that the coefficients and the intercept are highly significant (99.9%).
$endgroup$
– Maths Barry
Jan 20 at 8:31
$begingroup$
The T values all say that the coefficients and the intercept are highly significant (99.9%).
$endgroup$
– Maths Barry
Jan 20 at 8:31
add a comment |
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$begingroup$
You want to use the output to decide if the coefficients are significant. Although the coefficient is negative it could be that it is not significantly different from zero. (Look at the t-value).
$endgroup$
– user121049
Jan 19 at 19:30
$begingroup$
Can you copy-paste the output?
$endgroup$
– V. Vancak
Jan 20 at 5:54
$begingroup$
The T values all say that the coefficients and the intercept are highly significant (99.9%).
$endgroup$
– Maths Barry
Jan 20 at 8:31