CODEWITHSUNDEEP
rscatter-plot
SJJ
SJJ

Reputation: 53

How to make two lines of best fit R

I have a plot with two sets of data. I was wondering if someone could help me print lines of best fit? Here is my current code. I am trying to use data I created that I'm calling gender_data:

#Insert Data
library(readxl)
gender_data <- read_excel("Desktop/gender_data.xlsx")
View(gender_data)

#Matrix 
times_df <- data.frame(gender_data)
print(gender_data)

#Data Set
plot(x = gender_data$ "Olympic year", 
    y = gender_data$ "Men's winning time (s)", 
    xlab = "year", 
    ylab = "winning times", 
    ylim = c(7,13), 
    col = "green", 
    pch = "*")
points(x = gender_data$ "Olympic year", 
    y = gender_data$ "Women's winning time (s)", 
    col = "blue", pch = "`")
dput(head(gender_data))

My console is spitting out:

#dput(head(gender_data))
structure(list(`Olympic year` = c(1900, 1904, 1908, 1912, 1916, 
    1920), `Men's winning time (s)` = c(11, 11, 10.8, 10.8, NA, 10.8
    ), `Women's winning time (s)` = c(NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_)), row.names = c(NA, -6L), class = c("tbl_df", 
    "tbl", "data.frame"))

Upvotes: 0

Views: 870

Answers (1)

PLY
PLY

Reputation: 571

As you have not provided the data you used and did not include what kind of model you would like to fit, here is example code using the mtcars data. The fit is done using a linear model lm().

model_mpg_disp <- lm(mpg ~ disp, data = mtcars)
model_mpg_disp_predictions <- predict(model_mpg_disp)  
plot(mtcars$disp, mtcars$mpg)
lines(mtcars$disp , model_mpg_disp_predictions)

enter image description here

EDIT

For an ggplot() way as asked by @hachiko, we can use geom_smooth():

library(tidyverse)
ggplot(data = mtcars,
       aes(x = disp, y = mpg)) +
  geom_point() +
  geom_smooth(method = "lm")

enter image description here

Upvotes: 1

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