geom_smooth() Not Plotting Best Fit LIne

[R3d]

I know I'm probably missing something related to syntax or that someone else might have already asked a similar question (I'm very novice) but I can't get geom_smooth() to plot a best fit line for this chart. What can I do in order to get geom_smooth() in ggplot to work? Should I use ggplot2 to get a best fit line instead?

# install tidyverse package
install.packages("tidyverse")

# install readr library
library(readr)

library(readxl)

responses <- read_excel("Abreviated Responses.xlsx")


# Don't forget to Capitalize V
View(responses)

# Import data from excel sheet in from the range AB1 through AB7
rating_info <- read_excel('Abreviated Responses.xlsx', sheet = 1, range = 'AB1:AB71')

# Import data from excel sheet in from the range AQ1 through AQ7A
current_understanding <- read_excel("Abreviated Responses.xlsx", sheet = 1, range = 'AQ1:AQ71')

# Create a Data frame from both imported data vectors
rating_vs_understaing<-data.frame(rating_info, current_understanding)

# Plot the Data frame (this is where the question about geom_smooth is not working)
ggplot(data = rating_vs_understaing, aes(x= X4B_Rate_Information, y = X7B_Currently_Understand)) + geom_point() + geom_smooth(method = lm, se = FALSE)

# Plot the Data frame, jitter() will slightly randomize the results since the data set is too small and similar
ggplot(data = rating_vs_understaing, aes(x= X4B_Rate_Information, y = X7B_Currently_Understand)) + geom_point() + geom_jitter()

[williaml]

Are you after the regression line? See this:

Insert regression model into ggplot2

For this kind of questions, a quick search on stackoverflow is usually a great source of solutions. For example:

Also, your code isn't reproducible as we don't have your dataset. See:

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.…

[R3d]

Thank you! This is part of one of my first projects in RStudio. I do not have permission to publish the data (as it is a part of a capstone) however, I'm guessing that it might be possible that my dataset might not be large enough to produce a best fit line.

[nirgrahamuk]

@R3d

I do not have permission to publish the data

You don't have to literally publish the data, you could rather provide example data that has similar enough properties to approximate your data.
for example

# example data
set.seed(42)
(rating_info <- data.frame(X4B_Rate_Information = 1:25))
(current_understanding <- data.frame(X7B_Currently_Understand = 1:25 + sample(-5:5,size = 25,replace=TRUE)))


# Create a Data frame from both imported data vectors
rating_vs_understaing<-data.frame(rating_info, current_understanding)

# Plot the Data frame (this is where the question about geom_smooth is not working)
ggplot(data = rating_vs_understaing, aes(x= X4B_Rate_Information, y = X7B_Currently_Understand)) + geom_point() + geom_smooth(method = lm, se = FALSE)