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Statistics package for the social sciences spss version 23

Manufactured by IBM
Sourced in United States

SPSS version 23 is a software package designed for statistical analysis. It provides a comprehensive set of tools for data management, analysis, and visualization, catering to the needs of social science researchers and professionals.

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Lab products found in correlation

2 protocols using statistics package for the social sciences spss version 23

1

Chronotype, Diet, and Sexuality Associations

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Data analysis was performed using the statistical program International Business Machines (IBM) Statistics Package for the Social Sciences (SPSS) version 23 (IBM Corp, Armonk, NY, USA). Descriptive characteristics for continuous variables (age, BMI, KIDMED score, chronotype score, sexual opinion score, and physical activity) as well as the mean and standard deviation (SD) were calculated. Percentages (%) were used for categorical variables (sex, chronotype, BMI, KIDMED index). A comparison of proportions of the categorical variables was also performed using chi-square or Fisher’s tests for the contingency tables. To compare means of chronotypes and KIDMED test items, a student’s t-test was used. Analysis of variance (ANOVA) was also performed to analyse the differences between two or more means. Pearson correlations were used to establish associations between chronotype and sexual opinion with adherence to the Mediterranean diet and BMI. Adjusted linear regression analyses were carried out when any significant association existed. In all statistical tests, testing was significant when p < 0.05.
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2

Statistical Analysis of Research Data

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Data analysis was performed using the statistical program International Business Machines (IBM) Statistics Package for the Social Sciences (SPSS) version 23 (IBM Corp, Armonk, NY, USA). Continuous variables were stablished through mean and standard deviation (SD). Percentages (%) were used for categorical variables. A comparison of the proportions of the categorical variables was also performed using the chi-square or Fisher’s tests for the contingency tables. Analysis of variance (ANOVA) was also performed to analyse the differences between two or more means. Pearson’s correlation analysis was conducted to evaluate a possible linear correlation. Adjusted linear regression analyses were conducted when any significant association existed. In all statistical tests, testing was significant when p < 0.05.
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