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Spss statistical package version 12

Manufactured by IBM
Sourced in United States

SPSS Statistics is a software package used for statistical analysis. Version 12 provides a range of statistical techniques for data manipulation, analysis, and presentation. The core function of SPSS Statistics is to assist users in managing and analyzing data effectively.

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Lab products found in correlation

7 protocols using spss statistical package version 12

1

Serum Protein Levels and Inflammation

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In this non-inferiority study, we postulated that serum PAB levels in the egg white protein group would be non-inferior to the casein protein group by a presumptive non-inferior margin of 5 mg%. We calculated that 17 patients per additive protein group would provide a minimum power of 80 % to determine the non-inferior margin of a 5 mg% using a one-sided α of 0.05. Continuous data were expressed as mean and standard error of the mean (SEM). Categorical data were expressed as number and percentage. An independent t test was used to compare continuous demographic variables for each treatment group. Fisher’s exact test was used to compare category demographic variables for each treatment group. Repeated-measures ANOVA was used to determine the group effects displayed by the serum PAB and CRP levels. A post hoc analysis of the linear regression model was performed to determine the changes in PAB reflective of adequate caloric and protein support or changes in inflammatory responses. The results were considered statistically significant when the p value was less than 0.05. Statistical analysis was computed by SPSS® statistical package version 12.
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2

Statistical Analysis of Biological Data

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All quantitative data are presented as the mean ± standard deviation (SD) of at least three independent experiments. A two-group comparison was conducted using the two-sided, two-sample Student’s t-test. Simultaneous comparison of more than two groups was conducted using a one-way analysis of variance (ANOVA) followed by Tukey’s post hoc tests. The SPSS statistical package version 12 (SPSS Inc., Chicago, IL) was used for all statistical analyses. Statistically significant differences were considered when P-values were less than 0.05.
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3

Comprehensive Statistical Analysis of Experimental Data

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All quantitative data are presented as the mean ± SD of at least three independent experiments. The normality of the data was assessed using Shapiro-Wilk test. Means of two groups were compared using Student's t-test. Means of more than two groups were compared using one-way ANOVA, followed by Tukey post-hoc tests. Normality and homogeneity assumptions were met. The SPSS statistical package version 12 (SPSS Inc., Chicago, IL, USA) was used for all statistical analyses. Values of P < 0.05 indicated statistically significant differences.
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4

Comparative Statistical Analysis of Quantitative Data

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Quantitative variables were described using the mean ± standard deviation or median [interquartile range], depending on whether they followed a normal distribution, which we tested with the Kolmogorov-Smirnov method. For between-group comparisons, we used the Student t test for continuous variables and the chi-square test for qualitative variables. Statistical significance was defined as P < .05. Statistical analyses were performed with SPSS statistical package version 12.
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5

Statistical Analysis of Perioperative Outcomes

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All statistical analyses were performed using the SPSS® statistical package,
version 12.0 (SPSS Inc., Chicago, IL, USA) for Windows®. The baseline
characteristics and perioperative data were statistically analysed using
Student’s t-test and are presented as mean ± SD. A two-tailed
test was used to compare the postoperative adverse events. A
P-value < 0.05 was considered statistically significant.
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6

Comparative Statistical Analysis of Unpaired Data

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The results are presented as mean±standard deviation. For comparison of the two groups, the numeric values were analyzed using the independent samples t-test for unpaired values. Categorical data were assessed by the chi-squared test. A p value <0.05 was considered statistically significant. The statistical analyses were conducted using the SPSS statistical package, version 12.0 (SPSS Inc., Chicago, IL, USA).
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7

Statistical Analysis of Tumor Size

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All statistical analyses were performed using the SPSS® statistical package, version 12.0 (SPSS Inc., Chicago, IL, USA) for Windows®. Results are expressed as the mean ± standard error of the mean (SEM). Comparisons between the two groups were made with Student’s t-test. Tumour sizes for the experimental groups were compared with analysis of variance. A P-value <0.05 was considered statistically significant.
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