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Sas 9.0 statistical

Manufactured by SAS Institute

SAS 9.0 is a statistical software package developed by SAS Institute. It provides a comprehensive set of tools for data analysis, modeling, and reporting. The core function of SAS 9.0 is to enable users to perform advanced statistical analyses, data management, and business intelligence tasks.

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Lab products found in correlation

4 protocols using sas 9.0 statistical

1

Cumulative Gas Production Kinetics

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In order to estimate the kinetic parameters of Cumulative Gas production (GP), all the results of GP were fitted using the NLIN Procedure of the SAS 9.0 statistical software. The formula used is as follows: a = b × (1 − e−ct), where: a = volume (mL) of gas production per 0.2 g DM substrate at time t; b = asymptotic gas production (mL) of 0.2 g DM substrate; c = rate of gas production per hour. The test data were preliminarily sorted by Excel, and the one-way ANOVA was performed by SAS 9.0 statistical software. Duncan’s multiple comparison test was used to calculate the SEM and p Values. Additionally, the linear and quadratic curve trend analysis (Orthogonal polynomial contrast) was carried out. p < 0.05 (significant) and p < 0.01 (extremely significant) were used as the criteria to judge the significance of differences.
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2

Evaluating IBS-QOL and Abdominal Pain Impact

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SAS9.0 statistical software was used to generate random numbers and analyze the data. The IBS—QOL and VAS measure were taken as the evaluation standard of the influence of QOL and abdominal pain before and after the education program. EpiData 3.1 was used to record the data in the IBS—QOL Scale and abdominal pain scores, which were evaluated by SPSS17.0 statistical analysis. Comparisons between categorical data were conducted using the Chi-square test, and the scoring data were evaluated by the student’s t test between education group and no-education group, and by the factorial design analysis of variance in different years between education group and no-education group, with P = 0.05 as the cutoff.
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3

Statistical Analysis of Experimental Data

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Statistical analysis was conducted
using analysis of variance using SAS 9.0 statistical software. The
results are depicted as the mean ± standard deviation. Duncan’s
multiple range test was applied at a 5% level of significance.
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4

Covariate-Adjusted ANOVA for Fish Study

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Analysis of variance was performed with effects of treatments and blocks as the sources of variation and fish initial weight as the co-variable. The data were analyzed using the GLM procedure of SAS 9.0 statistical software.
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