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19.0 spss software

Manufactured by IBM
Sourced in United States

The 19.0 SPSS software is a statistical analysis software package developed by IBM. It is designed to assist users in analyzing and visualizing data. The software provides a wide range of statistical and analytical tools, enabling users to perform various types of data analysis, including regression analysis, hypothesis testing, and data modeling.

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Lab products found in correlation

7 protocols using 19.0 spss software

1

Cost-Effectiveness of Pulsed Electromagnetic Fields

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To determine whether the PEMFs are cost-effective to pay for additional health gain, we will compute mean (and SD) per patient costs and incremental cost-utility ratios using quality-adjusted life-years (QALYs) derived from SF-36 scores with appropriate preference weightings [35 (link), 36 (link)].
For all the analyses mentioned above, a two-sided value of P <0.05 will be considered statistically significant. All statistical analyses will be carried out using 19.0 SPSS software (SPSS, Chicago, IL).
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2

SPSS-based Statistical Analysis of Experimental Data

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The data and statistical analyses comply with the recommendations on experimental design and analysis. Data analysis was performed using 19.0 SPSS software (SPSS Inc., Chicago, IL, USA). One-way analysis of variance (ANOVA) was used to compare the mean differences among the groups. The results are shown as the mean ± SEM and a level of p ≤ 0.05 or p ≤ 0.01 was considered to be statistically significant.
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3

Antibody Expression Levels Analysis

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All statistical analyses were performed using the 19.0 SPSS software. Results were expressed as medians, means, SDs and confidence intervals (CI). We used a linear regression model to correlate different levels of antibody expression. (p < 0.05).
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4

Statistical Analysis of Experimental Data

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The data were presented as the mean ± standard deviation (SD). All the statistical analysis were performed using 19.0 SPSS software (SPSS, USA). The qualitative variables were compared by chi-square test or Fisher's exact test, while the quantitative variables were compared by Student's t-test. A p value <0.05 (two-sided) indicated statistically significant.
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5

Statistical Analysis of Experimental Data

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All data were expressed as the mean ± standard deviation and statistical analyses were performed with 19.0 SPSS software (IBM, Corp., Armonk, NY, USA); three independent experiments were performed. Statistical analyses of pairs of samples were performed using the Student’s t-test. Multiple group comparisons were carried out by one-way analysis of variance with Bonferroni’s post-hoc test. P<0.01 was considered to indicate a statistically significant difference.
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6

Triplicate Experiment Statistical Analysis

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All experiments were performed in triplicate and the data were reported as mean value ± standard deviation (SD). Statistical analysis (ANOVA) of the result were conducted using the student t-test (p < 0.05) using 19.0 SPSS software (IBM, Armonk, NY, USA).
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7

Comparative Drug Efficacy Analysis

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All experiments were performed independently three times. Data are presented as the mean ± standard deviation (SD) of three independent experiments. The difference between the drug-treated group and the control group was analyzed using unpaired Student’s t-test with 19.0 SPSS software (IBM Corp.). P < 0.05 was considered to indicate a statistically significant difference.
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