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Sigmaplot software 11

Manufactured by IBM
Sourced in United States

SigmaPlot software 11.0 is a data analysis and graphing tool developed by Systat Software Inc. It provides functionality for creating and customizing a variety of scientific and technical graphs and charts from data. The software supports a range of data file formats and offers features for data manipulation, statistical analysis, and report generation.

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Lab products found in correlation

6 protocols using sigmaplot software 11

1

Survivin Protein Analysis in Tumor Growth

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Means and standard errors were calculated for all data points from at least three independent experiments. Pairwise comparisons of survivin protein concentrations and cell survival between each of the experimental conditions were performed using a Student’s two-tailed t-test (SigmaPlot software 11.0, SPSS, Chicago, IL). Mean tumor volumes over time were compared among groups using repeated measures analysis of covariance (ANOVA) assuming a quadratic model and accounting for separate variances in each group. Post-hoc pairwise comparisons among groups were done using the Tukey-Kramer method [32 ]. Absolute tumor growth delay values, defined as the time in days for the tumors in the treated groups to grow from 250 mm3 to 1000 mm3 minus the time in days for untreated control tumors to grow across this same size range, were also determined [29 ].
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2

Survivin Protein Concentration Analysis

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Means and standard errors were calculated for all data points from at least three independent experiments. Pairwise comparisons of survivin protein concentrations and cell survival between each of the experimental conditions were performed using a Student’s two-tailed t test (SigmaPlot software 11.0, SPSS, Chicago, IL).
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3

Statistical Analysis of Experimental Data

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Data are presented as the mean ± SD. Comparison between more than two groups was performed by two-way ANOVA. If a significant main effect or association was identified, the means of the respective groups were compared using the Bonferroni t-test. Correlations between variables were established with the Pearson Product Moment Correlation. In all cases, a p value < 0.05 was considered significant. All analyses and graphics were performed with SigmaPlot software 11.0 (SPSS Inc.).
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4

Neurological Outcome with Early/Late Surgery

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Data analysis was supported by the Institute for Medical Biometrics and IT at the University of Heidelberg, Germany. Statistical analysis for consecutive variables was done with the Student’s t-test. The odds ratio of early and late surgery, age, and sex with AIS improvement were calculated (Table 1). Categorical data between groups were compared with the chi-squared test. Binary logistic regression was applied to analyze the dependence between neurological outcome and early or late surgery (Table 1). The presence or absence of AIS improvement from the initial to final follow-up was set as the outcome variable. The timing of surgery (early or late) was set as the predictor variable. Additionally, sex and age were tested as covariates. Statistical analyses were done with SPSS Software 22.0 (IBM Corporation, Armonk, NY, USA). Figures were created with Sigmaplot Software 11.0 (SPSS Inc., Chicago, Illinois, USA).
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5

Tumor Growth Delay Analysis

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Means and standard errors were calculated for all data points from at least three independent experiments. Pairwise comparisons of cell survival between each of the experimental conditions were performed using a Student’s two-tailed t-test (SigmaPlot software11.0, SPSS, Chicago, IL). Mean tumor volumes over time from 7 days on were compared among groups using repeated measures analysis of covariance (ANCOVA) assuming a quadratic model and accounting for separate variances in each group. Post-hoc pairwise comparisons among groups were also done using the Tukey-Kramer method (Kramer 1956 ). Absolute tumor growth delay values in the metformin treated groups was defined as the median time in days for the tumors to grow to greater than 1000 mm3 minus the median time in days for 10 Gy only tumors to grow to this size (Schimming et al. 1999 ). Since some tumors did not reach 1000 mm3, time to reach 1000 mm3 was compared between groups using a Kaplan-Meier curve and the log rank test.
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6

Cell Survival and Apoptosis Analysis

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Means and standard errors were calculated for all data points from at least three independent experiments. Pairwise comparisons of cell survival and apoptosis frequencies between each of the experimental conditions were performed using a Student's two-tailed t test (SigmaPlot software 11.0, SPSS, Chicago, IL).
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