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The R lm() function is used to fit linear models for performing linear regression, single stratum analysis of variance, and analysis of covariance.

The usage of the lm() function in R is as follows:

lm(formula, data, subset, weights, na.action, method = "qr", model = TRUE, x = FALSE, y = FALSE, qr = TRUE, singular.ok = TRUE, contrasts = NULL, offset, …)

Here, the parameters/arguments are defined as:

- formula: an object of class
`"formula"`

(or one that can be coerced into that class): a symbolic description of the model to be fitted. - data: an optional data frame, list or environment (or object coercible by
`as.data.frame`

to a data frame) containing the variables in the model. If not found in`data`

, the variables are taken from`environment(formula)`

, typically the environment from which`lm`

is called. - subset: an optional vector specifying a subset of observations to be used in the fitting process.
- weights: an optional vector of weights to be used in the fitting process. Should be
`NULL`

or a numeric vector. If non-NULL, weighted least squares is used with weights`weights`

(that is, minimizing`sum(w*e^2)`

); otherwise ordinary least squares is used. - na.action: a function which indicates what should happen when the data contain
`NA`

s. The default is set by the`na.action`

setting of`options`

, and is`na.fail`

if that is unset. The ‘factory-fresh’ default is`na.omit`

. Another possible value is`NULL`

, no action. Value`na.exclude`

can be useful. - method: the method to be used; for fitting, currently only
`method = "qr"`

is supported;`method = "model.frame"`

returns the model frame (the same as with`model = TRUE`

). - model, x, y, q: If
`TRUE`

the corresponding components of the fit (the model frame, the model matrix, the response, the QR decomposition) are returned. - singular.ok: If
`FALSE`

(the default in S but not in R) a singular fit is an error. - contrasts: an optional list.
- offset: this can be used to specify an
*a priori*known component to be included in the linear predictor during fitting. This should be`NULL`

or a numeric vector or matrix of extents matching those of the response. One or more`offset`

terms can be included in the formula instead or as well, and if more than one are specified their sum is used. - …: additional arguments to be passed to the low level regression fitting functions.

## Example Implementation of R lm() function:

The lm() function can be implemented in R according to the following example:

library(readxl) # Library for reading excel files ageandheight <- read_excel("ageandheight.xls", sheet = "Untitled1") # Upload the data lmHeight = lm(height~age, data = ageandheight) # Create linear regression model using lm summary(lmHeight) # Review the results

In the example above, you can substitute `ageandheight.xls`

to be any dataset that you want.

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