If you're satisfied that all the assumptions for OLS is satisfied, and there are no unusual observations, you can proceed with your interpretation.
However, I'm very surprised that you're able to distinguish a value as small as 0.000049
from 0
, and from the value of the test-statistic, p-value will be extremely small, almost 0
.
Can you please provide a REPRoducible EXample of your problem?
In case you don't know how to make a reprex, here's a great link:
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.…
PS
Please familiarise yourself with the following post:
What is @name mentioning?
@name mentioning is when you type someone's username with an @ preceding it. Doing this sends a notification to the user. Depending on their settings, it may also send them an email message.
For example, with @JacqueHousteauGram in my text, Jacque here will be dynamically notified in community (and via email if he's configured for it).
Please don't use this feature excessively
In general, it is considered bad form to @name mention someone not otherwise engaged in the conversation.
Why should I limit how much I @name mention others?
It can be annoying
Active people who were being frequently mentioned in topics were first to request that this practice be minimized…
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