Test your knowledge

Before completing the tasks, work through each of the sub-pages for tutorial 1. 

Task 1: Create a dataset from scratch

Select 10 Twitter Accounts of your choice and create a dataset with the following variables:

Note: Some of you may select organisations rather than people, or a combination of the two. If this is the case create one variable that measures whether the twitter account is a person or an organisation and a second variable that collects the sex, if available - if it is an organisation just add in NaN for missing values.

If you haven't already done so, add a description for each variable and add labels to your Gender levels (Male for 0s and Female for 1s)

Task 2: Clean Existing Data and get it ready for Jamovi

Access the sample data from here and open it in Excel

Use the Filter and Replace function in Excel to clean your data

Clean the following variables using the replace function

Open up the saved file in Jamovi and attached Labels and descriptions.

Add the following descriptions to variables: 

Now add the following labels:

Your file is now ready to analyse.  You would use a very similar process to clean a bigger dataset. 

If you have really big datasets, it is worth learning some Python or R to make data cleaning easier. 

Task 3: Create New Variables using Transform

Use the Twitter Dataset you created in Task 1

Using the Twitter dataset you have just created do the following:

Create an ordinal variable using the Followers variable.  Call it Followers_cat. 

Create the following categories:

Change the numbers to suit your dataset (e.g. instead of 1,000 change it to 1 million).

You should now have a new variable that has four ordinal categories.

Use the Dataset you cleaned in Task 2.

For this task use the Dataset you just cleaned in  task 2:

Create a nominal variable using the Age variable. Call it Over_50

Create the following categories:

You should now have a new nominal variable.