Spss Version 25.0 Upd May 2026

| Variable | N | Mean | SD | Skewness | Kurtosis | |----------|---|------|----|----------|----------| | Age (years) | 120 | 34.5 | 11.2 | 0.45 | -0.23 | | Test_Score | 118* | 78.3 | 8.9 | -0.67 | 0.89 | *Note: Listwise deletion due to missing values (handled via SPSS v25.0 multiple imputation). If you are writing a methodology paper , include a screenshot of the SPSS v25.0 output (e.g., the "Viewer" window with a specific table) as a figure – this adds authenticity. If you are writing a review or comparison paper , explicitly compare v25.0 with v26 or v27 in terms of ROC analysis or Bayesian features.

IBM Corp. (2017). IBM SPSS Statistics for Windows (Version 25.0) [Computer software]. IBM Corp. Note: If you used a specific module (e.g., AMOS), include that. For a paper, also note the operating system if relevant (e.g., Windows 10, 64-bit). 5. Strengths & Limitations Section (For a critical paper) | Aspect | Description for Version 25.0 | |--------|-------------------------------| | Strength | Stable build with fewer bugs compared to v24; excellent backward compatibility with .sav files. | | Strength | Output viewer allows seamless export to Word/Excel – superior to earlier versions. | | Limitation | No longer supported by IBM (end of life); no new updates or security patches. | | Limitation | Lacks more advanced machine learning procedures found in v27+ or SPSS Modeler. | | Limitation | Graphics quality is inferior to R or Python (Matplotlib/Seaborn). | 6. Sample Table (as you would present in the paper) Table 1: Descriptive Statistics Generated via SPSS v25.0 spss version 25.0

All data cleaning, transformation, and statistical analyses were performed using IBM SPSS Statistics for Windows, Version 25.0 (IBM Corp., 2017). Descriptive statistics (means, standard deviations, frequencies) were computed for demographic and primary outcome variables. Prior to inferential testing, assumptions of normality (Shapiro-Wilk test, ( p > .05 )) and homogeneity of variance (Levene’s test) were assessed. A paired-samples t-test was conducted to compare pre- and post-intervention scores, utilizing SPSS v25.0’s Bayesian option to provide evidence for the null hypothesis where appropriate. For all frequentist tests, the alpha level was set at ( \alpha = .05 ). Missing data were handled using the multiple imputation procedure (fully conditional specification) available in SPSS v25.0, generating 20 imputed datasets for analysis. In-text citation: (IBM Corp., 2017) | Variable | N | Mean | SD