Jonathan Tian - 1 year ago 77
R Question

# R in counting data

Right now I'm trying to do a bell curve on a file called output9.csv on my.

Here is my code, I want to uses z score to detect outliers, and uses the difference between the va

``````hist(height) #histogram

#POPULATION PARAMETER CALCULATIONS
pop_sd <- sd(height)*sqrt((length(height)-1)/(length(height)))
pop_mean <- mean(height)
``````

But I have this error after I tried the histogram part,

``````hist(height)
``````

Error in hist.default(height) : 'x' must be numeric

how should I fix this?

Answer Source

Since I don't have your data I can only guess. Can you provide it? Or at least a portion of it?

What class is your data? You can use `class(data)` to find out. The most common way is to have table-like data in `data.frames`. To subset one of your columns to use it for the `hist` you can use the `\$` operator. Be sure you subset on a column that actually exists. You can use `names(data)` (if `data` is a `data.frame`) to find out what columns exist in your data. Use `nrow(data)` to find out how many rows there are in your data.

After extracting your `height` you can go further. First check that your `height` object is `numeric` and has something in it. You can use `class(height)` to find out.

Did you try to convert it to numeric? `as.numeric(height)` might do the trick. `as.numeric()` can coerce all things that are stored as characters but might also be numbers automatically. Try `as.numeric("3")` as an example.

Here an example I made up.

``````height <- c(1,1,2,3,1)
class(height)
# [1] "numeric"

hist(height)
``````

This works just fine, because the data is numeric.

In the following the data are numbers but formatted as characters.

``````height_char <- c("1","1","2","3","1")
class(height_char)
# [1] "character"

hist(height_char)
# Error in hist.default(height) : 'x' must be numeric
``````

So you have to coerce it first:

``````hist(as.numeric(height_char))
``````

..and then it works fine.

For future questions: Try to give Minimal, Complete, and Verifiable Examples.

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