Thanks to theidioms.com        ## R lm() – lm function in R for Linear Regression # R lm() – lm function in R for Linear Regression  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
In the example above, you can substitute `ageandheight.xls` to be any dataset that you want.  