How to perform Data Analysis with SPSS

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Summary: NVivo Workflow for Data Analysis

✅ Import Data → ✅ Organize & Code Data → ✅ Run Queries & Text Analysis → ✅ Visualize Results → ✅ Export & Report Findings

SPSS (Statistical Package for the Social Sciences) is a powerful statistical software used for data management, statistical analysis, and visualization. It is widely used in research, business, healthcare, and social sciences for both qualitative and quantitative data analysis.

Below is a step-by-step guide on how to analyze data using SPSS.

📌 Step 1: Open SPSS & Load Data

1. Open SPSS

  • Launch SPSS and choose “Open an existing data source” or “Type in data”.

2. Load an Existing Dataset

  • Click File > Open > Data, then select a .sav, .csv, or Excel file.

3. Enter Data Manually

  • In the Data View, enter values in the spreadsheet.
  • In the Variable View, define variables (name, type, label, values, etc.).

✅ Tip: Always check variable types to ensure they are correctly formatted (e.g., Numeric, String, Date).

📌 Step 2: Explore & Clean Data

1. View Dataset Structure

  • Click “Variable View” to check variable types and properties.
  • Click “Data View” to inspect raw data.

2. Check for Missing Values

  • Click Analyze > Descriptive Statistics > Frequencies
  • Select variables and check missing values in the output.

To remove missing values:

mathematica
- Click "Transform" > "Replace Missing Values"
- Choose a method (e.g., Mean, Median, Regression)

3. Identify & Remove Outliers

  • Click Analyze > Descriptive Statistics > Explore
  • Choose variables and check for outliers in boxplots.

✅ Tip: If necessary, transform variables using log, square root, or standardization.

📌 Step 3: Perform Descriptive Statistics

1. Summary Statistics

  • Click Analyze > Descriptive Statistics > Descriptives
  • Select variables and check options for Mean, Standard Deviation, Minimum, Maximum

2. Frequency Tables (For Categorical Data)

  • Click Analyze > Descriptive Statistics > Frequencies
  • Select variables (e.g., Gender, Education) and check percentages & mode.

3. Crosstab Analysis (Comparing Two Categorical Variables)

  • Click Analyze > Descriptive Statistics > Crosstabs
  • Select Row and Column variables (e.g., Gender vs. Satisfaction Level).

✅ Tip: Use Chi-Square Test to check for statistical significance.

Published by Henry