SPSS DESDE CERO | CÓMO INGRESAR DATOS Y ORGANIZACIÓN DE VARIABLES. FÁCIL

Introduction to SPSS Course

Overview of the Course

• The course offers personalized consulting for research and statistics, with a link provided for scheduling appointments via WhatsApp.

• It aims to teach statistical analyses using SPSS software, covering step-by-step instructions from the basics to advanced analyses.

• The instructor assumes no prior knowledge of SPSS, promising that participants will gain confidence in using the program by the end of this section.

Getting Started with SPSS

• Upon opening SPSS, users are presented with options to create a new database or access recent files; sample databases are available for practice.

• Users can opt not to show the welcome dialog in future sessions for quicker access to their work.

Understanding Data Views in SPSS

Data and Variable Views

• In SPSS, there are two essential windows: Data View (showing data entries) and Variable View (showing variable characteristics).

• Each column in Data View represents a variable; icons indicate variable types such as categorical ordinal (e.g., age), nominal (e.g., gender), or numerical variables.

Types of Variables

• Statistical variables fall into two main categories: quantitative (interval and ratio scales) and qualitative (nominal and ordinal scales).

• Examples include nominal variables like gender without hierarchy, while ordinal variables like education level have an inherent order.

Working with Variables

Participant Representation

• Each row in Data View corresponds to a participant or observation; each cell contains values assigned to those participants across various variables.

Characteristics of Variables

• In Variable View, each variable is listed in rows with attributes such as name, type, width, decimals, labels, etc.

Creating a New Database

Starting from Scratch

• To create a new database in SPSS, navigate through File > New > Data; this opens an empty Variable View window.

Editing Variables

• Users can enter random numbers initially labeled as "Variable 001" and edit them by double-clicking on the name to rename according to their needs.

Data Structuring in SPSS

Importance of Data Organization

• The organization of databases is crucial; typically, sociodemographic data is assigned first, followed by other variables.

• Restructuring the database begins with participant IDs, gender, age, and weight. Missing values are noted when information is incomplete.

Variable Labeling and Editing

• Each variable must have a label for clarity during analysis; spaces and special characters can be used in labels.

• SPSS allows editing of variable types; most entered variables are numeric but can also include dates or strings.

Handling Different Variable Types

• String variables are created automatically when letters are inputted into a new column. Numeric entries align to the left indicating they are treated as text.

• It’s recommended to use numeric codes for categorical variables (e.g., 1 for male, 2 for female), facilitating easier analysis later on.

Assigning Values and Measures

• In the 'Values' column, assign numerical values to categorical variables like gender. This helps in maintaining consistency across analyses.

• The 'Measure' column categorizes each variable as nominal, ordinal, or scale based on its nature; this classification aids in proper statistical treatment.

Managing Missing Data

• For missing data management, it’s advisable to assign a high number (e.g., 999) that participants will not reach as a placeholder for missing values.

• Indicating missing values ensures that these do not skew analysis results.

Finalizing the Database Structure

• After assigning hypothetical values and ensuring all categories are correctly labeled, review the dataset structure before saving it.

• The final view in SPSS allows checking category names and value labels before concluding the setup process.

How to Save and Manage Data in SPSS

Basic Functions of SPSS

• To save a database in SPSS, click the "Save" button, then add a preferred name and location before clicking "Save."

• The tutorial covers the basic functionality and interface of SPSS, including how to enter numerical and categorical data.

• Users learn to add characteristics to variables, change their format, and manage missing data effectively.

• The discussion raises a question about handling pre-existing databases created in other software.