cor( x = parenthood$dan.sleep, y = parenthood$dan.grump )
I couldn't believe that it could do something so complex with such a short command. Its starting to look like the opportunities in R really are as limitless as the book makes it seem!
16 Matching Annotations
- May 2021
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learningstatisticswithr.com learningstatisticswithr.com
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> describeBy( x=clin.trial, group=clin.trial$therapy )
I struggled a bit here. I'm wondering if I did the homework right or not because I got it to show the descriptive statistics for average annual wages by industry title but I still got all of the other categories in the middle. It looks like thats how it works here too though.
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Unlike thesummary()function, it calculates the samedescriptive statistics for any type of variable you give it.
This is so nice!!! I love the way the book is set up it made jumping around and practicing these much easier.
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> kurtosi( x = afl.margins )
I got stuck here for a while in the homework because of there not being an s at the end of kurtosis. Is there a reason for that being that way in R?
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positively skewed data set (skewness“.93)
Looks like the skew from the homework data set is positively skewed
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Mode
Mode = Most Often ...always confuse this with other things but when I asked someone how they remember they said 'mode = most often' and that helped it click
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my.formula <- blah ~ blah.blah # create a variable of class "formula"> print( my.formula )
The formula stuff and combined with the print function is still a bit confusing even after reading this a few times. I'll have to practice it more. I think it would be more helpful if I had an I/O psych example for a reason to use it. Scenarios always help me figure things like this out better.
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$nerd[1] TRUE$parents[1] "Joe" "Liz"As you might have guessed from those$symbols everywhere, the variables are stored in exactly the sameway that they are for a data frame (again, this is not surprising: data framesarea type of list). So youwill (I hope) be entirely unsurprised and probably quite bored when I tell you that you can extract thevariables from the list using the$operator, like so:> Dan$nerd
It's a relief to see that even though there is a lot to learn, many things seem to work in the same way, like extracting different data/answers with different methods but using the same symbol $
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The simplest way is to use the$operator to extract the variable you’reinterested in, like this
Using the $ symbol makes a lot of sense for me because I used to create quests for players in a game and the $ key was what you had to use to move objects around and trigger events to happen. This will be easy to remember!
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expt
Update, I read over this again, compared it to the homework and realized I just misunderstood the directions. I understand how to name things now
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in a data frame calledexpt
This part was confusing because I felt like I needed to rename mine in the homework but I can't find in here where it told us how to rename it. How can we rename a data frame like that?
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s you can see,rm()can be very handy for keeping theworkspace tidy
I'm a little confused by this. Didn't it say earlier that when we open it, nothing is left over? Do we have to clear everything before leaving to avoid future issues?
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Rpackages are out there on the internet, waiting foryou to download, install and use them
Do these work like the toolkits you can download for excel? Do we have a list of safe websites to download from?
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Extracting multiple elements
This section was a bit confusing so I got help from my dad who does a lot of programming work.
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> 10 - 20[1] -10
I can easily see myself getting tripped up by putting things in the wrong order. If I make mistakes like this on assignments, how many points would be deducted? I'll definitely try to avoid this issue.
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nstalling R on a Mac
I have R installed from about two years ago when I was going to try and learn it for fun. Will I need to look for an updated version? Will that make a big difference?
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