Help with linear model

[TrevR]

So I'm trying to create a linear model between aDOT (average depth of target) and YAC/rec (yards after the catch per reception). Neither of the variables aDOT or YAC/rec are in my data frame so I was wondering how I could create a model between the two?
I tried:

airyards %>%
  summarise(aDOT = airyards$air_yards / airyards$tar) %>% 
  summarise(yac_per_rec = airyards$yac / airyards$rec) %>%
  summary(lm(aDOT ~ yac_per_rec))

Then I'll get the error

> airyards %>%
+   summarise(aDOT = airyards$air_yards / airyards$tar) %>% 
+   summarise(yac_per_rec = airyards$yac / airyards$rec) %>%
+   summary(lm(aDOT ~ yac_per_rec))
Error: Column `aDOT` must be length 1 (a summary value), not 16757

So then I wasn't sure what to do so I did the sum of the variables

airyards %>%
  summarise(aDOT = sum(airyards$air_yards) / sum(airyards$tar) %>% 
  summarise(yac_per_rec = sum(airyards$yac) / sum(airyards$rec)) %>%
  summary(lm(aDOT ~ yac_per_rec))

And literally nothing happened. This is all I got in the console

> airyards %>%
+   summarise(aDOT = sum(airyards$air_yards) / sum(airyards$tar) %>% 
+   summarise(yac_per_rec = sum(airyards$yac) / sum(airyards$rec)) %>%
+   summary(lm(aDOT ~ yac_per_rec))
+ 

I'm very new to this and I'd really appreciate any help

[andresrcs]

I think you are confusing summarise() with mutate() function, to help us help you, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

EDIT: I think this example with built-in data is very close to what you are trying to do

library(dplyr)
library(magrittr)

iris %>%
  mutate(aDOT = Sepal.Length / Sepal.Width,
         yac_per_rec = Petal.Length / Petal.Width) %$%
  lm(aDOT ~ yac_per_rec) %>% 
  summary()
#> 
#> Call:
#> lm(formula = aDOT ~ yac_per_rec)
#> 
#> Residuals:
#>      Min       1Q   Median       3Q      Max 
#> -0.71340 -0.17850 -0.00652  0.15870  0.87885 
#> 
#> Coefficients:
#>             Estimate Std. Error t value Pr(>|t|)    
#> (Intercept)  2.37802    0.05201  45.722   <2e-16 ***
#> yac_per_rec -0.09844    0.01046  -9.414   <2e-16 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#> 
#> Residual standard error: 0.3178 on 148 degrees of freedom
#> Multiple R-squared:  0.3745, Adjusted R-squared:  0.3703 
#> F-statistic: 88.62 on 1 and 148 DF,  p-value: < 2.2e-16