Statistics for Business MTH212 Reflection



In this lab, we’ll get a short introduction to doing some basic data visualization and exploration using the Jamovi software. For this assignment, you’ll need access to the software and the data set we’ll be working with.

Software: You can download jamovi onto a Mac or PC by following the link here:\Links to an external site.. You can also access a web-browser version with no installation needed here:\\Links to an external site..NOTE: the web-browser version is still new and always changing a bit, and so it can sometimes be unstable. The main issue is that it will “time-out” after not being used for a while, and so saving often is encouraged.Data Set: Download the WineRatingsSampled.csvEdit\Download WineRatingsSampled.csv data set. For now, just save this somewhere on your computer where you can find it easily. You will open this in Jamovi directly, and you shouldn’t need to do anything to the data set to get it ready.

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One last thing that will likely be helpful is taking some screenshots of the graphs and tables we produce. Visit\Links to an external site.

to learn how to take a screenshot using the device you’re on.

You should go through the tasks below and write up a short report. This should read like and essay, and you can use any editor you’d like (Google Docs, Word, Pages, etc). You’ll eventually submit your submission as either a Word doc file or a pdf. Feel free to use the titles for the tasks to organize your report.


Data Exploration

First, just take a couple of minutes to explore the data. If you click on the Variables tab on the top, you will see a list of all of the variables in this data set. We’ll only be interested in a couple of them. You can see a spreadsheet of the data in the Data tab. This is sometimes helpful to just see what kinds of variables we have: which ones are numbers and which ones are categories or other text descriptions. For a description of the different variables in this data set, scroll to the bottom of this assignment to view the Data Documentation.

Once you’ve got a handle on what this kind of looks like, click on the Analyses tab. This will be the main place that we do work in Jamovi. We are going to get some basic data visualizations to interpret and explain in this lab. Everything that we will need is in the Exploration menu, under Descriptives. So go there, and we’ll begin the lab!

Include In Your Report

You should include a short introduction to this data set: explain what it is, and what we are exploring.


We’re first going to explore the different categories of wine in this data set.

Add the “category” variable to the Variableswindow. You can do this by clicking and dragging it, or selecting it and then clicking the arrow button to add to the Variables window. There will be a little checkbox underneath that says “Frequency tables.” Click that to get Jamovi to display the frequency distribution of the categories of wine. It will display on the right, in the Results window.

Now, under “Plots” below, select a bar plot.

Include In Your Report

Include a screenshot of the frequency table and the bar plot. Explain what these tell us about the distribution of wine categories. Compare the two, explaining which one you think does a better job of showing the distribution of categories. Include your reasons.

Alcohol, Price, and Rating

Now, we’re going to look at the alcohol content, price, and rating of each wine in this data set. You can either start a new “Descriptives” section in your Results window by clicking Descriptives from the Exploration menu again, or you can remove the “category” variable and start over.

Add the variables “alcohol,” “price,” and “rating” to the Variables window. You can do this by clicking and dragging each one over, or selecting each one and then clicking the arrow button to add to the Variables window.

This will immediately display a table in the Results window on the right. We’re going to customize that table a bit. You should see a drop-down menu labeled “Descriptives.” You can change the option between “Variables across rows” and Variables across columns. This will change how the table is laid out. Choose whichever you like best.

Under the “Statistics” menu, you can select which descriptive statistics you would like to include in the table. There are a lot of options! Let’s just include the mean, median, and standard deviation.

Under the “Plots” menu, we have more options of which kind of plots to include. For now, select histogram and box plot. You should have the six graphs (three histograms and three boxplots) now in the Results window on the right.

Include In Your Report

Include the table you created, and explain what it is reporting. You should give a brief interpretation of each value, and what it says about the data.

Next, you should summarize the histograms. Include the pictures in your report, and describe them in terms of their shape, their center, and their spread. You should compare them to each other, but note that they are on different scales.

Then, add the boxplots. Again, interpret each one and describe what information they tell us about the variables, and compare them to each other.

Finally for this section, compare the boxplots and histograms overall. Which one do you think more effectively summarizes the data? Which one gives a better comparison of the two variables? Explain your answers.

Grouping by Category

For this next task, you’ll choose either “alcohol,” “price” or “rating” variable to work with. Put your choice in the “Variables” window, and then add the “category” variable to the “Split by” window. This will add a second variable, the type or category of wine, to the analysis.

Again, include a table with the mean, median, and standard deviation, but add IQR as well. I normally like to orient the table by choosing “Variables across rows.”

Again, choose to display histograms and boxplots.

Include In Your Report

Include the table you created, and describe the differences in these values across the different categories. What are the things to notice, and what do they mean about the variable you selected across different categories?

Now include the histograms and boxplots. For each, interpret. Describe what these visuals tells you about the differences between categories for your variable.

Between the histograms and the boxplots, which ones do you think do a better job of illustrating these differences? Why? Explain your reasoning.

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