Spss version 17

Manufactured by IBM

Sourced in United States, Japan, United Kingdom, Germany, Israel, Thailand

SPSS version 17.0 is a statistical software package developed by IBM. It provides a comprehensive set of tools for data analysis, including data manipulation, visualization, and predictive modeling. The software is designed to handle a wide range of data types and offers a user-friendly interface for conducting complex statistical analyses.

Automatically generated - may contain errors

Lab products found in correlation

Prism 5, by GraphPad (43 mentions) Prism 6, by GraphPad (18 mentions) Prism 7, by GraphPad (17 mentions) Sas version 9, by SAS Institute (16 mentions) Prism 8, by GraphPad (9 mentions) Origin 8, by OriginLab (7 mentions) R version 3, by R Project for Statistical Computing (5 mentions) Version 18, by MedCalc (5 mentions) Spss statistics for windows version 17, by IBM (5 mentions) Sas 9, by SAS Institute (5 mentions) Prism software, by GraphPad (4 mentions) Spss v17, by IBM (4 mentions) Stata version 11, by StataCorp (4 mentions) Prism version 5, by GraphPad (4 mentions) Version 15, by MedCalc (3 mentions) Stata version 10, by StataCorp (3 mentions) Originpro 8, by OriginLab (3 mentions) Prism version, by GraphPad (3 mentions) Spss statistics for window, by IBM (3 mentions) Prism 4, by GraphPad (3 mentions)

4 196 protocols using spss version 17

Evaluating Genetic Variants in Glioma

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The statistical tests were regarded as significant when P value was less than 0.05. The genotype frequency deviation from Hardy-Weinberg equilibrium was tested based on Pearson’s Chi-square test through the online program (http://ihg.gsf.de/cgi-bin/hw/hwa1.pl). Pearson’s Chi-square test in the program UNPHASED version 3.1.2 was employed for analyzing overall allele and genotype frequency difference between the case and control cohorts. The same test in SPSS version 17.0 (SPSS Inc., Chicago, IL, USA) was employed for comparison of the frequency difference between the case and control cohorts for each genotype sub-group. Student’s t-test and ANOVA in SPSS version 17.0 were used to test the significance of correlation of the three glioma grades, survival status, or genotypes with ZFPM2 mRNA expression levels in the glioma tissues. Kaplan-Meier non-parametric test [33 (link)] and Cox regression in SPSS version 17.0 was used to generate survival curves to evaluate the importance of rs71305152 genotypes to survival time.

Tsang S.Y., Mei L., Wan W., Li J., Li Y., Zhao C., Ding X., Pun F.W., Hu X., Wang J., Zhang J., Luo R., Cheung S.T., Leung G.K., Poon W.S., Ng H.K., Zhang L, & Xue H. (2015). Glioma Association and Balancing Selection of ZFPM2. PLoS ONE, 10(7), e0133003.

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Correlating miR-148a Expression with Osteosarcoma

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Data are presented as the mean ± standard deviation. Student's t-test was used to analyze statistical comparisons between groups, and two-tailed P<0.05 was considered to indicate a statistically significant difference. Spearman's rank correlation coefficient in SPSS version 17.0 software (SPSS, Inc., Chicago, IL, USA) was used to analyze the correlation between miR-148a expression and clinical osteosarcoma stages, while Kaplan-Meier survival analysis with log-rank test in SPSS version 17.0 software was used to analyze the overall survival in osteosarcoma patients. Pearson's correlation coefficient in SPSS version 17.0 software was used to analyze the correlation between the expression of miR-148a and the protein levels of PTEN.

Zhang H., Wang Y., Xu T., Li C., Wu J., He Q., Wang G., Ding C., Liu K., Tang H, & Ji F. (2016). Increased expression of microRNA-148a in osteosarcoma promotes cancer cell growth by targeting PTEN. Oncology Letters, 12(5), 3208-3214.

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Genetic Associations with Venous Thrombosis

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Power analysis of each study sample was conducted using the Power and Sample Size Calculations program (PS version 3.0.43, by William D. Dupont and Walton D. Plummer, Jr. http://ps-power-and-sample-size-calculation.software.informer.com/). The genotyping results of SNPs were screened for deviations from Hardy‐Weinberg equilibrium using PLINK version 1.07 (http://zzz.bwh.harvard.edu/plink/index.shtml), and no SNPs showed significant deviation (P>0.05). An independent t test was used to analyze the difference of sex and age in case and control groups by SPSS version 17.0 (IBM Corp). Association analysis for 3 SNPs before adjusting for covariates of age and sex were performed by 2×2 contingency tables using PLINK version 1.07. Association analysis for the 3 SNPs after adjusting for covariates of age and sex was performed using logistic regression analysis with SPSS version 17.0. Odds ratios (ORs) and corresponding 95% confidential intervals (CIs) were also calculated. In addition, we performed multiple logistic regression analysis to adjust significant covariates of sex and age for VT.

Li Q., Zhao Y., Wu G., Chen S., Zhou Y., Li S., Zhou M., Fan Q., Pu J., Hong K., Cheng X., Kenneth Wang Q, & Tu X. (2017). De Novo FGF12 (Fibroblast Growth Factor 12) Functional Variation Is Potentially Associated With Idiopathic Ventricular Tachycardia. Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, 6(8), e006130.

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Fatty Acid Profiling of Baobab Seed Oil

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Descriptive statistics were performed to quantify the amount of fatty acids (saturated and unsaturated fatty acids) and cyclic fatty acids (CPFAs) in baobab seed crude oil using the MS Excel spreadsheet. The samples were analysed in triplicate, and the data were presented as mean ± standard deviation (SD). One-way analysis of variance (ANOVA) was performed to test for significant differences between the composition of fatty acids and CPFAs in three different regions and treatments. ANOVA with Tukey's least significant difference (LSD) test was used in SPSS version 17.0 (SPSS, Chicago, IL, USA) to evaluate the differences between and within fatty acids and CPFAs. The differences were considered statistically significant at p < 0.05. A general linear model (GLM) ANCOVA in SPSS version 17.0 (IBM Corp., Chicago IL) was run using time as a fixed/random factor and temperature as a covariate to determine the effects of heat and boiling duration on the concentrations of fatty acids and CPFA composition.

Msalilwa U.L., Makule E.E., Munishi L.K, & Ndakidemi P.A. (2020). Physicochemical Properties, Fatty Acid Composition, and the Effect of Heating on the Reduction of Cyclopropenoid Fatty Acids on Baobab (Adansonia digitata L.) Crude Seed Oil. Journal of Lipids, 2020, 6691298.

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Multimodal Neuroimaging Analysis of MDD

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Clinical data were analyzed using SPSS Version 17 (SPSS Inc., Chicago, IL, USA), using an independent two-sample t-test between the MDD and HC groups. sMRI data were analyzed using SPM8, and the comparison of rs-fMRI data were analyzed using REST 1.8. Gaussian random field correction was used in this study, and the P-value was set as <0.05, using two-tailed tests. PickAtlas was utilized to make mask and REST 1.8 to extract the ALFF/fALFF/ReHo values.17 (link),18 (link) The correlation between the HAM-D-17 and resting-state indexes was analyzed using SPSS Version 17.0. Partial correlation was used when the number of years of education was used as a covariate.

Li G., Rossbach K., Zhang A., Liu P, & Zhang K. (2018). Resting-state functional changes in the precuneus within first-episode drug-naive patients with MDD. Neuropsychiatric Disease and Treatment, 14, 1991-1998.

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Body Weight and Food Intake Analysis

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Data are expressed as mean ± standard error of mean (SEM). One-way analysis of variance (ANOVA) tests were used to analyze the data with statistical package for the social sciences (SPSS) version 17.0 software. In addition, the least significant difference (LSD) method was adopted for comparisons between groups. The repeated measures procedure of the general linear model (GLM) in SPSS version 17.0 was used to conduct one-way ANOVA analysis for repeated measures data (body-weight and food intake), and multivariate analysis process of variance was used to make comparisons between groups on each time point (the LSD method). P values <0.05 were considered statistically significant.

Wu F., Song Y., Li F., He X., Ma J., Feng T., Guan B., Wang L., Li S., Liu X., Liu Y., Mao M., Liu J., Bai S, & Song C. (2014). Wen-Dan Decoction Improves Negative Emotions in Sleep-Deprived Rats by Regulating Orexin-A and Leptin Expression. Evidence-based Complementary and Alternative Medicine : eCAM, 2014, 872547.

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Age Distribution of Pine Regeneration

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Three repetitions in each gap size class were first combined into one experimental unit (total units, n = 5). To detect the significance, the age distributions in different gap size classes were compared two by two using the Kolmogorov-Smirnov test in SPSS version 17.0. A Monte Carlo simulation with a significance level of 99% was used for precision detection. The coefficient of skewness (g), which can correctly predict the direction of population change^{48 (link)}, was calculated for each age histogram:

g = \frac{\frac{n \sum {(x - \bar{x})}^{3}}{(n - 1) (n - 2)}}{{(\frac{\sum {(x - \bar{x})}^{2}}{n - 1})}^{3 / 2}}

where n is the number of regenerated pines,

x

is the age, and

\bar{x}

is the average age.
g > 0 indicates a distribution with few younger regenerat ion and many older regeneration, whereas g < 0 indicates a distribution with few older regeneration and many younger ones^{17 (link)}. A logarithmic transformation was performed for age before calculating g. In addition, to understand the changes between these two age groups of regeneration, the percentages of REAG and REBG were compared in the same gap size class and in different gap size classes. Analysis of variance (ANOVA) and multiple comparisons (Duncan’s test) were implemented using SPSS version 17.0. Significant differences were detected at p < 0.05.

Wang Z., Zhao K., Yang H., Ma L, & Jia Z. (2017). Various response of Pinus tabulaeformis Carr. regeneration in artifical gaps. Scientific Reports, 7, 14568.

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Comprehensive Statistical Analysis of Crop Traits

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Analysis of variance (ANOVA) was performed for conventional descriptors, digital parameters, and biochemical compounds. Means, standard deviations, and coefficient of variation (expressed in percentage as the ratio between standard deviation and mean) were used for descriptive analysis of traits. Significant differences among means were detected using Tukey HSD test (p < 0.05). Statistical analyses were performed with SPSS version 17.0 software [73 ]. The correlations among all evaluated parameters were estimated by using the Pearson’s test at p < 0.05 after Bonferroni’s adjustment for multiple comparisons [74 ]. The calculation of coefficients and visualization of correlograms was performed with Rcmdr and Corrplot packages implemented in R 3.6.0 software [75 ]. Conventional (quantitative), TA, and biochemical attributes were comprehensively examined through principal component analysis (PCA). In addition, the similarity across accessions was estimated by agglomerative hierarchical cluster analysis (HCA) using Ward’s coefficient. Multivariate analyses were conducted with the computer software SPSS version 17.0 [73 ] and R 3.6.0. [75 ]. Graphical representation of the tree was performed with MEGA X software [76 (link)].

García-González C.A, & Silvar C. (2020). Phytochemical Assessment of Native Ecuadorian Peppers (Capsicum spp.) and Correlation Analysis to Fruit Phenomics. Plants, 9(8), 986.

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Magnetic Resonance Imaging of Resorption in Platelet-Rich Plasma-Enhanced Microfat Grafts

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The magnetic resonance imaging volumes of resorption are expressed as median [interquartile range (first quartile to third quartile)]. The semiquantitative histologic data are expressed as mean ± standard error. The Nonparametric Analysis of Longitudinal Data in Factorial Experiments (nparLD package) from R Version 3.5.2 software (R Foundation for Statistical Computing, Vienna, Austria) was performed for magnetic resonance imaging volume analysis. The Wald-type test statistic was used to compare magnetic resonance imaging-derived graft volumes over time compared to those 1 day after injection (baseline volumes). The interaction term between sites and time was tested in this statistical model. We completed this global analysis by comparing the graft survival of the three platelet-rich plasma-enriched microfat mixes versus graft survival of the microfat alone at each time of magnetic resonance imaging evaluation with a Kruskal-Wallis nonparametric test (SPSS Version 17.0; SPSS, Inc., Chicago, Ill.). We performed the Bonferroni test and we presented the Bonferroni adjusted p values for the pairwise comparisons. Semiquantitative histologic data were analyzed by means of analysis of variance and the Tukey post hoc test (SPSS Version 17.0). Values of p < 0.05 were considered to be significantly different.

Abellan Lopez M., Bertrand B., Kober F., Boucekine M., De Fromont De Bouailles M., Vogtensperger M., Bernard M., Casanova D., Magalon J, & Sabatier F. (2020). The Use of Higher Proportions of Platelet-Rich Plasma to Enrich Microfat Has Negative Effects: A Preclinical Study. Plastic and reconstructive surgery, 145(1).

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Antioxidant Activity and Phenolic Content Analysis

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All experiments were independently conducted in triplicate, and experimental results were expressed as means ± standard deviations or average. One-way analysis of variance (ANOVA) and Duncan’s multiple range tests were performed using SPSS version 17.0 (SPSS Inc., Chicago, IL, USA) software. Statistical significance was determined at p < 0.05. Interpolation from linear regression analysis was used to obtain the EC₅₀. In order to interpret the relationships between antioxidant activity and total phenolic contents, two-tailed Pearson’s correlation coefficient analysis and principal component analysis (PCA) were conducted using SPSS version 17.0 (SPSS Inc., Chicago, IL, USA) software.

Yang R., Guan Y., Wang W., Chen H., He Z, & Jia A.Q. (2018). Antioxidant capacity of phenolics in Camellia nitidissima Chi flowers and their identification by HPLC Triple TOF MS/MS. PLoS ONE, 13(4), e0195508.

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