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Spss statistics for windows 24

Manufactured by IBM
Sourced in United States

SPSS Statistics for Windows 24.0 is a comprehensive software package designed for advanced statistical analysis. It offers a wide range of analytical tools and techniques to help users efficiently manage, analyze, and interpret complex data. The software provides a user-friendly interface and powerful statistical capabilities.

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Lab products found in correlation

33 protocols using spss statistics for windows 24

1

Statistical Analysis of Research Data

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Descriptive statistical analysis (including means or medians with ranges and percentages to characterize data) was performed using Microsoft Excel 2013 (Redmond, WA, USA, Microsoft Corp.). Statistical analyses were performed with SPSS software version 24 (IBM SPSS Statistics for Windows 24.0, Armonk, NY, USA, IBM Corp.), using the χ2-test, Student’s t-test and Mann–Whitney U test. The normality of variables was tested using Shapiro–Wilk tests. p values < 0.05 were considered statistically significant.
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2

Statistical Analysis of MedBakter Data

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Data for analysis were collected from the MedBakter laboratory information system, while
the management of data and the preparation of data for statistical analyses were performed
using Microsoft Excel 2013 (Microsoft Corp, Redmond, Washington). Statistical analyses
were performed with SPSS software version 24 (IBM SPSS Statistics for Windows 24.0; IBM
Corp Armonk, New York). The normality of variables was tested using Shapiro-Wilk tests.
P values <.05 were considered statistically significant.
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3

Statistical Analysis of Eye Measurements

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To perform the statistical analyses, IBM SPSS Statistics for Windows 24.0 (IBM Corp., Armonk, NY, USA) were used. The right eye of each subject was considered when conducting the statistical analyses. Descriptive statistics were presented in the form of the mean ± standard deviation (minimum-maximum). The Pearson chi-square test was used in the evaluation of the categorical variables. Student’s t-test was used for normally distributed variables in pairwise comparisons of study groups. Statistical significance was set as p<0.05.
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4

Descriptive Statistical Analysis of Isolates

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Due to the low number of relevant isolates, only descriptive statistical analyses were performed. Categorical variables were summarized by frequencies and percentages, while continuous data were presented as mean ± standard deviation (SD) and counts or percentages (%). All statistical analyses were performed using Statistical Package for Social Science (SPSS) software (IBM SPSS Statistics for Windows 24.0, IBM Corp., Armonk, NY, USA).
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5

Cell Experiment Statistical Analysis

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Variables were reported as mean ± SD. Each cell experiment was performed at least three times. Data were compared using 2-tailed Student's t-test for two independent samples or one-way ANOVA followed by Kruskal-Wallis H test for more than two groups. p < 0.05 was considered statistically significant. All statistical analyses were performed with IBM SPSS Statistics for Windows 24.0 (SPSS Inc., Chicago, IL, USA).
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6

Statistical Analysis of Microbiological Data

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Descriptive statistical analysis was performed using Microsoft Excel 2013 (Redmond, WA, Microsoft Corp.). Additional statistical analyses were performed with SPSS software version 24 (IBM SPSS Statistics for Windows 24.0, IBM Corp. Armonk, NY, USA), using the χ2-test and two-sample-test (isolation frequency and resistance trends). P values <0.05 were considered statistically significant.
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7

Comparing Biomarkers of Cardiometabolic Risk

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Continuous variables were reported as mean ± SD, and dichotomous variables were reported as percentage. Baseline demographics of patients between two groups were compared with the χ2 test (two‐sided) or Fisher's exact test for dichotomous variables and Wilcoxon signed‐rank test for continuous variables. Differences in galectin‐3, hsCRP, lipid profiles, and liver and renal function in the two groups were compared using the Wilcoxon matched‐pairs signed‐rank test (two‐tailed). Each cell experiment was performed at least three times. Data were compared using 2‐tailed Student's t test for two independent samples or one‐way analysis of variance followed by Kruskal–Wallis H test for more than two groups. p < 0.05 was considered statistically significant. All statistical analyses were performed with IBM SPSS statistics for Windows 24.0 (SPSS, Inc., Chicago, IL, USA).
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8

Statistical Analysis of Research Data

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Descriptive statistical analysis (including means or medians with ranges and percentages to characterize data) was performed using Microsoft Excel 2013 (Redmond, WA, Microsoft Corp.). Statistical analyses were performed with SPSS software version 24 (IBM SPSS Statistics for Windows 24.0, Armonk, NY, IBM Corp.), using the χ2-test, Student’s t-test and Mann–Whitney U test. The normality of variables was tested using Shapiro–Wilk tests. P values < 0.05 were considered statistically significant.
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9

Marital Dissolution and Work Hours

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All statistical analyses were performed after sex stratification. The χ2 test was conducted to determine statistical associations among weekly workhours, marital status change (2014–2015), and possible confounding variables. In this study, dependent variable set as the marital status in 2015 was divorce or separation. Univariate and multivariate logistic regression analyses were performed to understand the statistical association between weekly workhour and the dissolution of marital relationship. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated in 2 models: i) Model 1, adjusted by age, total monthly household income, and working type; and ii) Model 2, adjusted by age, total monthly household income, working type, and depression. IBM SPSS statistics for Windows 24.0 (IBM Corp., Armonk, NY, USA, released 2016) was used for all statistical analyses with significance level set at p < 0.05.
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10

Temporal Analysis of UDR Isolates

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Statistical analyses, including the descriptive analysis and statistical tests (Student’s t-test and Mann–Whitney U test) were performed with the SPSS software version 24 (IBM SPSS Statistics for Windows 24.0, IBM Corp., Armonk, NY, USA). The normality of variables was tested using Shapiro–Wilk tests. A correlation analysis was also performed with the aim of assessing the temporal nature of changes in the ratio of UDR isolates during the study period; the coefficient of determination (R2) was also calculated. These analyses were performed using the Past 3.16 statistical software (Paleontological Museum, University of Oslo; Oslo, Norway). p values <0.05 were considered statistically significant.
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