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Linear regression model with (categorical) predictor variables
The Next CEO of Stack Overflow2019 Community Moderator ElectionNeural Network Timeseries Modeling with Predictor VariablesTime Series Machine Learning Feature Selection ProblemWhy after adding categorical data the Linear Regression fails?Handling categorical variables in linear regression and random forestcustomer segmentation with categorical variablesLinear Model for Linear RegressionRegression model for continuous dependent variable and count independent variablesIntuitive Explanation of R-squaredGet insights from Random forest::Variable Importance analysis
$begingroup$
I used LM model with (categorical) predictor variables on my data in r like this (I have count variable as dependent/target variable):
# Fit linear model to total viewing:
fit <- lm(
total_viewing_minutes ~ panelist + sex + internet + education,
data = cln
)
If I understood correctly in r the first category is always the reference one so has by definition a coefficient of 0.
So by looking at the model result, is 68.3 minutes (intercept) average time viewing of
Panelist0 + sex1 + internet1 + education1
and by taking into account the term Panelist1
the 68.4 + 17.6 is avg time viewing of
Panelist1 + sex1 + internet1 + education1
is that correct interpretation?
machine-learning r linear-regression categorical-data
asked Feb 22 at 18:16
AnnAnn
61
$endgroup$
bumped to the homepage by Community♦ 11 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I used LM model with (categorical) predictor variables on my data in r like this (I have count variable as dependent/target variable):
# Fit linear model to total viewing:
fit <- lm(
total_viewing_minutes ~ panelist + sex + internet + education,
data = cln
)
If I understood correctly in r the first category is always the reference one so has by definition a coefficient of 0.
So by looking at the model result, is 68.3 minutes (intercept) average time viewing of
Panelist0 + sex1 + internet1 + education1
and by taking into account the term Panelist1
the 68.4 + 17.6 is avg time viewing of
Panelist1 + sex1 + internet1 + education1
is that correct interpretation?
machine-learning r linear-regression categorical-data
asked Feb 22 at 18:16
AnnAnn
61
$endgroup$
bumped to the homepage by Community♦ 11 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I used LM model with (categorical) predictor variables on my data in r like this (I have count variable as dependent/target variable):
# Fit linear model to total viewing:
fit <- lm(
total_viewing_minutes ~ panelist + sex + internet + education,
data = cln
)
If I understood correctly in r the first category is always the reference one so has by definition a coefficient of 0.
So by looking at the model result, is 68.3 minutes (intercept) average time viewing of
Panelist0 + sex1 + internet1 + education1
and by taking into account the term Panelist1
the 68.4 + 17.6 is avg time viewing of
Panelist1 + sex1 + internet1 + education1
is that correct interpretation?
machine-learning r linear-regression categorical-data
asked Feb 22 at 18:16
AnnAnn
61
$endgroup$
I used LM model with (categorical) predictor variables on my data in r like this (I have count variable as dependent/target variable):
# Fit linear model to total viewing:
fit <- lm(
total_viewing_minutes ~ panelist + sex + internet + education,
data = cln
)
If I understood correctly in r the first category is always the reference one so has by definition a coefficient of 0.
So by looking at the model result, is 68.3 minutes (intercept) average time viewing of
Panelist0 + sex1 + internet1 + education1
and by taking into account the term Panelist1
the 68.4 + 17.6 is avg time viewing of
Panelist1 + sex1 + internet1 + education1
is that correct interpretation?
machine-learning r linear-regression categorical-data
machine-learning r linear-regression categorical-data
asked Feb 22 at 18:16
AnnAnn
61
asked Feb 22 at 18:16
AnnAnn
61
asked Feb 22 at 18:16
AnnAnn
61
asked Feb 22 at 18:16
AnnAnn
61
asked Feb 22 at 18:16
AnnAnn
61
61
bumped to the homepage by Community♦ 11 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 11 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
add a comment |
1 Answer
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$begingroup$
Your interpretation is correct. I would also add that if Panelist1 increases by 1 unit and the other predictors are held constant, then the average increase in the response variable is 17.557 minutes.
answered Feb 27 at 22:08
N. AgarwalN. Agarwal
11
$endgroup$
add a comment |
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$begingroup$
Your interpretation is correct. I would also add that if Panelist1 increases by 1 unit and the other predictors are held constant, then the average increase in the response variable is 17.557 minutes.
answered Feb 27 at 22:08
N. AgarwalN. Agarwal
11
$endgroup$
add a comment |
$begingroup$
Your interpretation is correct. I would also add that if Panelist1 increases by 1 unit and the other predictors are held constant, then the average increase in the response variable is 17.557 minutes.
answered Feb 27 at 22:08
N. AgarwalN. Agarwal
11
$endgroup$
add a comment |
$begingroup$
Your interpretation is correct. I would also add that if Panelist1 increases by 1 unit and the other predictors are held constant, then the average increase in the response variable is 17.557 minutes.
answered Feb 27 at 22:08
N. AgarwalN. Agarwal
11
$endgroup$
Your interpretation is correct. I would also add that if Panelist1 increases by 1 unit and the other predictors are held constant, then the average increase in the response variable is 17.557 minutes.
answered Feb 27 at 22:08
N. AgarwalN. Agarwal
11
answered Feb 27 at 22:08
N. AgarwalN. Agarwal
11
answered Feb 27 at 22:08
N. AgarwalN. Agarwal
11
answered Feb 27 at 22:08
N. AgarwalN. Agarwal
11
11
add a comment |
add a comment |
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