# Linear regression with data from excel

Could you ask this with a minimal REPRoducible EXample (reprex)? A reprex makes it much easier for others to understand your issue and figure out how to help.

You should look at the documentation about `lm` to see how the formula interface works. It would better to put your two variables in a data.frame and use something like this

``````ModelBelgium <- lm(ShareBelgium ~ MVBelgium, data = my_data)
``````

invalid type (list) for variable 'ShareBelgium'

Otherwise, be sure that `ShareBelgium ` and `MVBelgium` are vectors.

From the help page example:

``````ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2, 10, 20, labels = c("Ctl","Trt"))
group
#>  [1] Ctl Ctl Ctl Ctl Ctl Ctl Ctl Ctl Ctl Ctl Trt Trt Trt Trt Trt Trt Trt
#> [18] Trt Trt Trt
#> Levels: Ctl Trt
weight <- c(ctl, trt)
weight
#>  [1] 4.17 5.58 5.18 6.11 4.50 4.61 5.17 4.53 5.33 5.14 4.81 4.17 4.41 3.59
#> [15] 5.87 3.83 6.03 4.89 4.32 4.69
lm.D9 <- lm(weight ~ group)
lm.D9
#>
#> Call:
#> lm(formula = weight ~ group)
#>
#> Coefficients:
#> (Intercept)     groupTrt
#>       5.032       -0.371
``````

Created on 2018-11-11 by the reprex package (v0.2.1)

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