Knowing the variability in our data set is critical to making sense of our data.
Let's learn how to calculate standard deviation in JASP!
We will begin this example here in Excel. We have the same data as we used previously when we did
this example by hand, in class. Groups of teens and adults were asked to describe
the plot of a movie and the linguist researcher counted the number of times
each one used the word "like" in their description. Remember that we entered
these data on Sheet 1 of the workbook, and then copied them on to Sheet 2. That
way, the original data will still be on Sheet 1 without additional calculations.
Our plan is to import this data into JASP and then find the means and
standard deviations for both adults and teens. When you plan to import data from
Excel into JASP, do three things: first, put simple variable names on row 1.
Second, put your cleaned data on Sheet 1. However, there is a third thing that we
MUST do before importing data. JASP will not read a native Wxcel file. If the
file has the suffix .xlsx, then we must save this data into the comma
delimited file called a .CSV. In Excel, go to File -> Save. Save the file as "LikeLike"
to the Desktop in the format "Comma Separated Values (.csv)". You may get a
warning about losing information. This is because the transformation of our
workbook into a .CSV will only save the data on the first sheet. Of course, we
still have the original file, so no worries. Click Continue. Now we have our
data saved to the Desktop in a format that
JASP can read. We open our data set in JASP by clicking on the upper left
corner Main Menu icon and then selecting Open -> Computer -> Desktop -> LikeLike.csv
and then clicking Open. Let's take a look at our data. The variables have imported,
but we need to make some changes. Both of these variables are Scale level, so make
sure that JASP imported them as continuous data. If it did not, we would
change that by clicking on the icon and resetting the level of the data. That is
all that we need to do for these simple data, so we are now ready to analyze.
Go to Descriptives -> Descriptive Statistics. In the Results pane, we see the table
where the descriptive statistics are going to appear. Move the variables "Adult"
and "Teens" into the variables box. Here we see the JASP progressive disclosure.
The results appear as soon as we enter the variables. Now click on the disclosure
triangle next to Statistics. Here we find a list of available statistics for our
variables. We want mean and standard deviation - both of which are selected by
default. We can turn off Minimum and Maximum, but let's get variance, range, and
interquartile range. With each click, new results are added to our table. We can
see that teens use the word "like" approximately twice as often as the
adults did, but that their standard deviations were similar: 2.1 versus 2.97.
Remember that standard deviation is the square root of the variance.
Also remember that values calculated by hand, such as we did in class, may vary
due to rounding. If you're off by a hundredth of a point, it's probably just
a rounding error. Just as with the central tendency example, JASP will give
us more information about our variables. For example, we can see a histogram of
both of these distributions. Click the disclosure triangle next to Plots.
We would like to see the distribution plots, this will show us some histograms.
By adding the density of the distribution, we can see how closely each distribution
matches a normal curve. Both of these are small data sets, so the normal curve is
pretty ragged. Correlation plots do not make much sense here. There is no point
in looking for a relationship like: "Is an increase in teens saying "like", positively
related to adults saying "like." It just, like, doesn't make, like, sense, like, y'know...like.
What does make sense here are box plots. We can see that the adult
median is centered on 10, while the teen median is centered on 18. Teens use the
word "like" nearly twice as often when describing. Add the Violin element and we
can see that the distributions are shaped rather similarly. The ranges are
similar, the boxes of the box plots are similarly sized, except one box plot
median is higher than the other. This suggests that teens and adults have
similar distributions of speaking ability (or perhaps conscientiousness)
and that teens will likely refine their speaking ability with age. No need to
despair about the lingual abilities of the future
"The Kids are Alright"
And, of course, we rarely compute variability without central tendency.
We could get all of the other measures of central tendency, dispersion, and measures
for skewness, or kurtosis. Finally, you can save this file as a JASP dataset by
going to Main Menu -> Save as -> Computer -> Desktop and then saving it as "LikeLike".
The new file will appear on your desktop as LikeLike.jasp. Not only will this
file contain all of your numeric data, it will also contain all of the analyses
and plotting that you have done so far.
So this is how you calculate variability in JASP.