The IBM SPSS version 22.0 statistics program (IBM Corp., Armonk, NY, USA) was used for statistical analyses. The data are summarized as the mean ± standard deviation. Normal distribution was assessed using the one-way analysis of variance test. For non-normally distributed data, the Mann-Whitney U test with Bonferroni correction was used to compare between two groups. P<0.05 was considered to indicate a statistically significant difference.
Spss version 22.0 statistics
Manufactured by IBM
Sourced in United States
SPSS version 22.0 is a statistical software package developed by IBM. It provides a comprehensive set of tools for data analysis, including descriptive statistics, regression analysis, and hypothesis testing. The software is designed for use by researchers, analysts, and data scientists in a variety of fields.
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Lab products found in correlation
6 protocols using spss version 22.0 statistics
1
Statistical Analysis of Experimental Data
2
Exploring the Interplay of Internet Addiction, Self-Esteem, and Sociodemographics
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The research was designed using a quantitative method. The survey was conducted on the internet via Google Forms. After collecting the data, it was cleaned and arranged in the MS Excel program, and then the IBM SPSS version 22.0 statistics (IBM, Armonk, NY, USA) [108 ] package was used to analyze the research data. Demographic information of the participants was shown by percentage and frequency analysis. Correlation analysis was performed using the Pearson coefficient to determine the relationship between internet addiction, self-esteem, daily internet usage, and sociodemographic variables. Multiple regression analysis was conducted to determine the direct effects of age and other sociodemographic variables on self-esteem (Step 1), daily internet usage (Step 2), and internet addiction (Step 3). Indirect and moderation analyzes were performed to test the hypotheses. We tested the mediation and moderation hypotheses using the PROCESS macro plugin [109 ] and conducted simple slope tests for two-way interactions [110 (link)]. Model 14 in PROCESS macro was used for moderated mediation analyzes [109 ]. The significance level was set at 0.05.
3
Statistical Analysis of Behavioral Data
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We used the SPSS version 22.0 statistics software (IBM, Armonk, NY) for the behavioral and demographic data analysis. The Shapiro-Wilk test was performed to test the normality of the continuous variable distribution. For the demographic data analysis, a two-independent samples t-test was used to compare normally distributed data of both groups. For the non-normally distributed data, a nonparametric test was used to compare the group differences. For the non-continuous variables, the Chi-square test was applied to explore the group differences.
4
Multivariate Data Analysis Protocol
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The descriptive statistics and the general linear model's full factorial model of multivariant components employing IBM SPSS Statistics (22.0 version) were used for data analysis. The post hoc multiple comparisons and Duncan's multiplication test (p < .05) were used for observed means and equal variance.
5
Cytokine and Chemokine Profiling in Children
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The average values and 95% CI of the cytokines and chemokines in duplicate samples for each child were calculated by SPSS. The values below the detection limit were assigned a 0 pg/mL concentration. The chi-square (χ2) test and rank sum test were used for statistical analyses by SPSS Statistics 22.0 version (IBM, Armonk, NY, USA). For specimens with small sample sizes, “unpaired” in “Experimental design”, “Use nonparametric test in “Assume Gaussian distribution”, then “Mann Whitney test” in “Choose test” was chosen. P-values under 0.05 were considered statistically significant. Spearman’s rank correlation coefficient in SPSS was used to analyze the relationship between two related variables. GraphPad Prism 8.0.1 was used for data visualization.
6
Evaluating Significance of Differences
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Results are presented as mean ± SEM. Prior to each analysis, test variables were checked for normality; all data were evaluated by the Kolmogorov-Smirnov test in order to follow a posterior parametric or nonparametric statistical analysis. The analysis of the results was performed using unpaired Student t-test or ANOVA and post hoc Tukey in order to analyze the significance of differences between groups. IBM SPSS Statistics (22.0 version) software was used and a difference was considered to be statistically significant when p < 0.05.
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