How to Enter Data in SPSS Or Excel

In the preceding session, the Smart PLS4 series was introduced, and now the focus is on working with a specific model. Assuming that data has been successfully collected, the next step involves entering this data into either SPSS or Excel. For instance, let’s consider a questionnaire with constructs representing organizational learning and items measuring these constructs.

Coding Items in SPSS:

The initial step is to code the items systematically. For example, items measuring organizational learning could be coded as “ol1,” “ol2,” and so on. In SPSS, navigate to the Variable View, where you can name and define all variables. Additionally, it is advisable, given SPSS’s statistical nature, to represent variables in numeric terms. Assign numeric values to the scale options, such as 1 for strongly disagree, 2 for disagree, and so forth.

Defining Variables in SPSS:

In SPSS, define each variable by specifying its type (nominal, ordinal, or scale). It’s recommended to combine interval and ratio variables into the “scale” category. Also, consider demographic variables like gender and age, assigning numeric values for representation.

Entering Data:

Once variables are defined, enter the data systematically, referring to numbered questionnaires. 

Error Checking:

After entering data, perform a thorough check for errors. While specific error-checking procedures are not outlined in this tutorial, errors checking includes assessing missing values, respondents bias/misconduct. It is essential to validate data for accuracy. Checking for minimum and maximum values can be achieved using relevant formulas in Excel.

Importing Data into Smart PLS4:

Smart PLS4 conveniently accepts data files from SPSS, Excel, and CSV formats. After entering and checking data in SPSS or Excel, save the file in the desired format (e.g., CSV) and import it into Smart PLS4 for further analysis.

This tutorial provides a foundational understanding of how to enter data into SPSS and Excel, emphasizing systematic coding, variable definition, and error checking. Subsequent tutorials will delve into defining projects and importing data into Smart PLS4 for comprehensive analysis.