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Spss statistic program

Manufactured by IBM
Sourced in United States, Germany

SPSS is a statistical software package used for data analysis and management. It provides a comprehensive set of tools for data manipulation, statistical modeling, and visualization. SPSS is designed to handle a wide range of data types and can be used for a variety of analytical tasks, including regression analysis, hypothesis testing, and multivariate statistics.

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23 protocols using spss statistic program

1

ELBW Children's Neurodevelopmental Outcomes

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Statistical analyses were made by IBM SPSS Statistic program (version 22 and 25). Pearson chi‐square test/Fisher's exact test (for comparison of background information between participating and nonparticipating children and between the subpopulation and other ELBW children in the study group, proportions of normal WIPPSI‐scores, school and neuromotor outcome between the study and the control group), Mann Whitney U test (for ADHD rating scale and comparison of WIPPS‐R‐scores at the age of 5 years between participating and nonparticipating children and between the subpopulation and other ELBW children in the study group), and Student's t‐test (for comparison of WISC‐III scores between study group and the controls) were used in analyses. P‐values of less than .05 were considered statistically significant. Effect sizes (Cohen's d and r) were interpreted as small (d < 0.50, r < .10), medium (d < 0.80, r < .30), or large (d ≥ 0.80, r ≥ .50).
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2

Analyzing Bacterial Counts on Skin

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Mesophilic aerobic bacteria, E. coli and total coliforms counts per gram of skin from triplicate experiments were converted to log units for statistical analysis. Bacterial counts were compared to evaluate significant differences among treatments, using one way ANOVA and post hoc analysis via Tukey test at P < 0.05 (IBM SPSS Statistic program, 2020 ). Prevalence differences for Salmonella were determined using the chi-squared test (FREQ procedure). A P-value < 0.05 was considered significant (SPSS, 2021 ).
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3

Statistical Analysis of Experimental Data

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All data were expressed as mean ± standard deviation (SD). To compare the difference between four groups, all parameters were analysed by using one-way ANOVA (post hoc, LSD and descriptive) test from the IBM SPSS statistic program (version 22, Armonk, NY), downloaded from KKU software center, Khon Kaen University, Thailand (November 2019). If the p value was less than 0.05, the difference was considered as statistical significance.
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4

Statistical Analysis Methods Utilized

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Statistical analyses were performed with the IBM SPSS Statistic program (IBM, Ehningen, Germany) or GraphPad Prism Version 6 (GraphPad Software Inc., San Diego, CA, USA). All data sets were tested for normal distribution, and appropriate parametric or non-parametric tests were chosen. Two datasets were tested by two-tailed Student’s t test or Mann–Whitney U test, respectively, if not stated otherwise. Correlations were analyzed by Spearman’s ranked test. For association between categorical variables, chi-square analyses were performed.
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5

Analyzing Non-Parametric Data Differences

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The normality and homogeneity of the data were tested using the Shapiro-Wilk normality and Levene’s homogeneity test, respectively. Since the data did not distribute normally, Mann-Whitney test was used to determine the different between two groups. Statistical tests were conducted using SPSS Statistic program, version 26 (IBM, New York, USA).
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6

Epidemiological Trends in Chronic Illness

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Quantitative variables were expressed as median and range. Qualitative variables were expressed as frequency and percentage. Analysis of normality was performed with the Kolmogorov–Smirnov test. Categorical data and proportions were analysed using chi-squared test or Fisher’s exact test as required. Statistical analysis was performed using the IBM SPSS Statistic program version 25. Follow-up of patients was updated on December 2020.
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7

Statistical Evaluation of Apomorphine Behavioral Test

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Statistical evaluation for animal apomorphine behavioral test (after 6-OHDA) injection was performed by Student’s t-test. For the staircase test, upon 6-OHDA and even hBM-MSCs secretome, levodopa or Neurobasal®-A medium injections, ANOVA repeated measures followed by post-hoc Bonferroni for multiple comparisons was performed using SPSS statistic program (version 25; IBM Co., Armonk, NY, USA). Graphical representation by using GraphPad Prism ver.8 (GraphPad Software, La Jolla, CA, USA). Equality of variances and sphericity were measured using the Levene’s and Mauchly’s tests, respectively, and was assumed when p > 0.05. Data are presented as mean ± SEM. The significance value was set at p < 0.05. Effect size was calculated using η2 partial.
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8

Statistical Analysis Techniques in Research

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Statistical analysis was carried out using the SPSS Statistic Program (version 26; IBM Co., Armonk, NY, USA) and GraphPad Prism 8 software, specifically for graphics design (La Jolla, USA). Normality assumption was evaluated for all continuous variables using the Shapiro-Wilks statistical test, considering the respective measures of skewness and kurtosis and visualizing normal histogram distributions. Levene’s and Mauchly’s tests appraised the homogeneity of variances and sphericity, respectively, and assumed when the p-value ≥ 0.05. Student’s t-tests for independent samples or Mann-Whitney U tests (data presented as mean + IQR) were carried out to compare means between two groups. For lengthwise comparisons of mean differences, both two-way ANOVA analysis and mixed-design factorial ANOVA were applied. To further evaluate the nature of the differences between groups, multiple comparison post hoc tests were performed, employing either Tukey’s HSD post hoc test or Bonferroni’s. All tests were performed with a 95% confidence interval. Data were acknowledged as statistically significant if the p-value ≤ 0.05. Suitable effect sizes for each test were calculated (ANOVA: eta-square partial (η2partial); t-test: Cohen’s d (d); Mann Whitney U-test: rank-biserial correlation(r)). All graphs are represented with mean values ± SEM (standard error of the mean).
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9

Statistical Analysis of Experimental Data

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All statistical analyses were performed as indicated using the IBM SPSS Statistic program (Versions 20–22; IBM, Ehningen, Germany) or GraphPad Prism (Versions 4 and 5; GraphPad Software Inc., San Diego, CA, USA).
All data sets were tested for normal distribution based on the expected experimental results and appropriate parametric or non-parametric tests were chosen. An estimate of variation was made for selected analyses. Comparison of two groups with similar variances was done by Student's t-test or Wilcoxon non-parametric test. Analyses were two-sided, if not stated otherwise.
Sample size was chosen according to Fisher's exact test and the expected difference between experimental conditions. Animal behavior was analyzed by two-way repeated measures analysis of variances (ANOVAs) with the variables genotype and treatment, object, or trial, thus considering correcting for multiple testing. Significant effects of the independent variables were explored further by splitting the data appropriately and conduction of lower level ANOVAs and post hoc comparisons including respective corrections for multiple testing. Paired sample t-tests were applied when appropriate.
Appropriate statistical tests and P-values are stated in the respective figure legends and/or results section. P-values of *P⩽0.05, **P⩽0.01, ***P⩽0.001 were used as significance levels.
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10

Statistical Analysis Protocols for Insect Studies

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ANOVA was performed to compare the mean group values with a significance level of 0.05 by the IBM SPSS statistic program (IBM Schweiz AG, Zurich, Switzerland). Tukey HSD was used if the data had a homogenous variance and same number of replicates for all groups. Hochberg's G2T was used when sample sizes of groups were unequal and Games Howell was performed when homogeneity of variance was not given. Standard deviations of averages calculated from other averages that already have a standard deviation (e.g., averaged AA composition of the three insect species) were calculated taking the quadrature of the internal (SDint) and external standard deviation (SDext) [see equations (S1–S5) in the Supplementary Material; (24 (link))].
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