Access over 250 short video tutorials demonstrating how to use Stata and solve specific problems are available. The videos for simple linear regression, time series, descriptive statistics, importing Excel data, Bayesian analysis, t-tests, instrumental variables, and tables are always popular.
Stata is a robust statistical software that enables users to analyse, manage, and produce graphical visualisations of data. It is primarily used to study data trends by researchers in economics, health, and political science. The software is easier to use because it offers a command line and a graphical user interface.
JGU Global Library has license to STATA 18 for both Windows and Mac OS.
System Requirement for Installation
Windows versions supported by Stata 18 :
- Windows 11 *
- Windows 10 *
- Windows 8.1 *
- Windows Server 2016, 2012R2 *, 2019 *, 2022 *
Mac versions supported by Stata 18 :
- Mac with Apple Silicon or Intel processor (Core i3 or better)
- macOS 11.0 (Big Sur) or newer for Macs with Apple Silicon and macOS 10.12 (Sierra) or newer for Macs with 64-bit Intel processors
It is best that the collected data should be in an excel sheet. This makes it easier to copy and edit. An already existing dataset will be used as an example.

Please see that the observations of variables 'Sex' and 'did you eat cake in the past 7 days' are denoted as 1 &2 and 0 &1 respectively. For the variable 'sex', we will be considering 1 as male and 2 as female. Whereas, for the variable did you eat cake in the past 7 days', we will be considering 0 as 'no' and 1 as 'yes'.
Please see that the observations of variables 'Sex' and 'did you eat cake in the past 7 days' are denoted as 1 &2 and 0 &1 respectively. For the variable 'sex', we will be considering 1 as male and 2 as female. Whereas, for the variable did you eat cake in the past 7 days', we will be considering 0 as 'no' and 1 as 'yes'.
Step 3: A data editor window will appear, where you can copy the data from the excel sheet. Make sure that you copy the data into the first cell in the data editor. You will find a pop-up message asking 'Do you want to treat the first row as variable names or data'. Click 'variable names' and the dataset will be created.
Step 2: You can see the properties displayed on the right side for the selected variable (in this case 'interviewid'). If you want to edit any properties of the variables, you can choose any variable from the left side table and change the properties from the right-hand side table.
Variable properties:
1. Name: Should not contain any numbers or special characters
2. Label: It is basically how the variable name appears in an output. This can be changed as per your requirement.
3: Type: How the data is being stored.
4. Format: It is auto-generated.
5. Value label: set of responses that are valid for a question(multiple choice).
6. Notes: for reference purpose
Variable properties:
1. Name: Should not contain any numbers or special characters
2. Label: It is basically how the variable name appears in an output. This can be changed as per your requirement.
3: Type: How the data is being stored.
4. Format: It is auto-generated.
5. Value label: set of responses that are valid for a question(multiple choice).
6. Notes: for reference purpose
Step 3: For example, earlier we saw that for the variable 'sex', the observations were denoted as 1 and 2, where 1 is male and 2 is female. Now we need to specify it in the variable properties by creating values in the value label.
Select the variable 'sex' from the left-hand side table and click the 'manage' option of the Value label. Then select 'create label'.
Select the variable 'sex' from the left-hand side table and click the 'manage' option of the Value label. Then select 'create label'.
Step 4: A 'create label' window will pop-up, where you need to add the label name, i.e., variable name (in this case 'sex'). In the value section type '1' and in the label section type 'Male'. Then click 'add'.

Same way, In the value section type '2' and in the label section type 'Female'. Then click 'add'. Then 'OK'. The set of values for variable 'sex' is added.
Same way, In the value section type '2' and in the label section type 'Female'. Then click 'add'. Then 'OK'. The set of values for variable 'sex' is added.
Now let's see how to create a graph with the available data. We will be taking the variables 'sex' and 'rice' as examples.
Step 1: Let's create a pie chart for the variable 'sex'. Go to the command pane and type 'graph pie, over(sex)'. (note: in order to produce a pie chart. variable names are added inside the bracket). The command is the same for creating a bar and dot chart. You can replace the word 'pie' with either bar or dot and the same will be produced accordingly.

Step 1: Let's create a pie chart for the variable 'sex'. Go to the command pane and type 'graph pie, over(sex)'. (note: in order to produce a pie chart. variable names are added inside the bracket). The command is the same for creating a bar and dot chart. You can replace the word 'pie' with either bar or dot and the same will be produced accordingly.