Need help creating a Regression Chart

[AlexAbbott]

Hello, I'm new to R and statistics in general. I am trying to create a Regression Chart between two variables those being Reliten (Religious Affiliation) and Cappun ( Favoring or Opposing Capital Punishment on Murders) both of which are found in the GSS dataset.

I have my lm and my summarylm
summary(lm(reliten_numeric ~ cappun_numeric, data=gss))
lm(gss$reliten_numeric ~ gss$cappun_numeric)

but my scatterplot
scatterplot(reliten_numeric ~ cappun_numeric, data=gss)
comes up with this error:
pseudoinverse used at 0.995
neighborhood radius 1.005
reciprocal condition number 1.4841e-15
There are other near singularities as well. 1.01
pseudoinverse used at 0.995
neighborhood radius 1.005
reciprocal condition number 0
There are other near singularities as well. 1.01
pseudoinverse used at 0.995
neighborhood radius 1.005
reciprocal condition number 0
There are other near singularities as well. 1.01
pseudoinverse used at 0.995
neighborhood radius 1.005
reciprocal condition number 6.2844e-16
There are other near singularities as well. 1.01
pseudoinverse used at 0.995
neighborhood radius 1.005
reciprocal condition number 1.4841e-15
There are other near singularities as well. 1.01

How do I fix this or create a usable chart?

[andresrcs]

Hi Alexander, welcome!

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.…

Since we don't know from where are you getting the gss dataset, I have made this example with the iris built-in dataset.

library(ggplot2)
ggplot(data = iris, aes(x = Sepal.Length, y = Sepal.Width)) +
    geom_smooth(method = "lm") +
    geom_point()

^{Created on 2019-04-08 by the reprex package (v0.2.1.9000)}

[AlexAbbott]

The GSS dataset comes from the library poliscidata

[andresrcs]

There are no reliten_numeric or cappun_numeric variables in gss dataset, how have you generated this variables? Again, if you want more specific help, please post a reproducible example for your question; otherwise try to adapt the above generic answer to your own data.

library(poliscidata)
library(dplyr)

gss %>% 
    select(starts_with("reliten"), starts_with("cappun")) %>% 
    names()
#> [1] "reliten"  "reliten2" "cappun"