The largest database of trusted experimental protocols

577 protocols using sigmastat

1

Evaluating Cognitive Outcomes in Mice

Check if the same lab product or an alternative is used in the 5 most similar protocols
Results are reported as mean ± standard error (SE). Data was analyzed using two-way repeated measure ANOVAs, and Bonferroni corrected t-tests were used for post hoc analyses (SigmaStat, Systat Software, Inc.). Statistical tests were performed using SigmaStat software (Systat Software Inc.), and alpha levels were set at 0.05, with only significant effects reported.
+ Open protocol
+ Expand
2

Transcriptomic and Lipidomic Analysis of Human Meibum

Check if the same lab product or an alternative is used in the 5 most similar protocols
The transcriptomic datasets were processed using Expression and Transcriptome Analysis Consoles (v.4.0.1.36; both from Affymetrix) and SigmaStat (v.3.5, from Systat Software, Inc., San Jose, CA, USA). The default (and currently the industry standard) filter criteria: (1) (+2) < LFC < (−2), and (2) ANOVA p-value (condition pair) ≤0.05, were used to analyze the data. A tighter LFC of >(+1.2) and <(−1.2), as proposed in [34 (link)], was also tested, but deemed impractical because of an unrealistically high number of samples needed to satisfy statistical criteria (see Discussion).
The RP-UPLC/MS data were analyzed using MassLynx (v.4.1), MSe Data Viewer (v.1.4), and Progenesis QI software packages (from Waters). A Supplemental Table S1 lists major lipids of human meibum relevant to this study, and their corresponding m/z values. SigmaStat and SigmaPlot software packages from Systat Software, Inc. were used to conduct statistical evaluation of the data.
The transcriptomic and lipidomic data for two genders were compared gender-wide using Student’s t-test for the two groups. Tests with p-values ≤ 0.05 were considered statistically significant. Principal component analyses were performed using Transcriptome Analysis Console, Progenesis QI, and EZInfo (v.3.0.3.0 from Umetrics AB, Umeå, Sweden).
+ Open protocol
+ Expand
3

Statistical Analysis of Experimental Data

Check if the same lab product or an alternative is used in the 5 most similar protocols
All experimental data are presented in the text and graphs as the mean ± SEM. Statistical analysis were carried out using one way analysis of variance (ANOVA) when comparing multiple treatment groups (SigmaStat, Systat Software Inc., Richmond, VA). A repeated-measures analysis of variance (ANOVA) was performed for the time-course of the changes in Figs. 3, 4, 5 and 6 utilizing SigmaPlot 14 (SigmaStat, Systat Software Inc., Richmond, VA). Where necessary, post-hoc Newman-Keuls tests were performed for planned comparisons. The unpaired Students t-test was used when there were only two groups to be compared such as the experiment to transfact BDNF cDNA for the expression of TH and pERK1/2 (Fig. 6).
+ Open protocol
+ Expand
4

Statistical Analysis of Cell Culture

Check if the same lab product or an alternative is used in the 5 most similar protocols
Culture experiments were tested for normal distribution and equal variance before being compared to controls by ANOVA, followed by Student Newman–Keuls test to determine where any differences lay. p < 0.05 values were considered statistically significant. Analyses were performed using SigmaStat version 3.5 (Systat Software, Inc., San Jose, CA) and data have been expressed as mean ± SD.
+ Open protocol
+ Expand
5

Quantitative Analysis of Protein Levels

Check if the same lab product or an alternative is used in the 5 most similar protocols
All experiments were performed at least three times. All data are expressed as means±standard deviations. Statistical analysis was performed using Sigma Stat (Systat Software, La Jolla, CA, USA). Data in which two conditions were compared were evaluated using one-way analysis of variance followed by Tukey's post-hoc test; p-values <0.05 were considered significant.
+ Open protocol
+ Expand
6

Statistical Analysis of Experimental Data

Check if the same lab product or an alternative is used in the 5 most similar protocols
All data are reported as mean values ± sem. Statistical differences between treatment and control groups were evaluated by Sigma Stat (Systat Software, London, UK). Both parametric and non-parametric analyses were applied, in which the Mann–Whitney rank sum test (Mann–Whitney U-test) was used for samples on a non-normal distribution, whereas a two-tailed t-test was performed for samples with a normal distribution.
+ Open protocol
+ Expand
7

Cardiac and Exercise Hemodynamics Analysis

Check if the same lab product or an alternative is used in the 5 most similar protocols
A 1-way analysis of variance (ANOVA) was used to determine group differences in participant characteristics, LV structure and function and BV variables and for parametric data Bonferroni’s t-test post hoc testing was used when the ANOVA resulted in a p <0.05 result. Non-parametric data were analyzed via Kruskal-Wallis ANOVA on ranks, with Dunn’s post hoc testing. Repeated-measures (RM) ANOVAs were used to determine group differences in exercise metabolic and hemodynamics variables. When the main group effect achieved p < 0.05, Bonferroni post hoc tests were performed to examine group differences at the different experimental conditions. All statistical analyses were performed using SigmaStat (Systat Software) and p <0.05 was considered statistically significant. Data are presented as means ± SD or median (25% - 75%) in Tables 15 and means ± SD in Figs 1-4.
+ Open protocol
+ Expand
8

Statistical Analysis of Experimental Data

Check if the same lab product or an alternative is used in the 5 most similar protocols
Statistical analysis was performed using SigmaStat (Systat Software, San Jose, CA, USA) and data were visualized using GraphPad Prism (La Jolla, CA, USA). Comparisons between groups were performed with Student’s t-tests. If comparisons failed normality tests then Mann–Whitney rank sum tests were performed. Pearson’s correlations were performed to determine linear correlation between two groups. Significance was set at p < 0.05.
+ Open protocol
+ Expand
9

Comprehensive Statistical Analysis Protocol

Check if the same lab product or an alternative is used in the 5 most similar protocols
Results are expressed as the mean ± SEM. Two-group analyses were performed using an unpaired t-test. Three or more groups with one independent variable were analyzed using a one-way ANOVA test. Three or more groups with two independent variables were analyzed using a two-way ANOVA test. Analyses were performed using the Prism (GraphPad Software, San Diego, CA, USA) and SigmaStat (SyStat Software, Inc., San Jose, CA, USA) software packages. All tests were two-tailed and a p-value < 0.05 was considered to indicate statistical significance.
+ Open protocol
+ Expand
10

Statistical Analysis of Biomarker Associations

Check if the same lab product or an alternative is used in the 5 most similar protocols
SigmaStat (Systat Software, Chicago, IL, USA) software was used for statistical analyses. Differences between the three groups were analyzed using Kruskal–Wallis one way analysis of variance on ranks. Spearman rank order correlation analysis was used to find associations between the markers. Criteria for significance were set at p<0.05 for all parameters.
+ Open protocol
+ Expand

About PubCompare

Our mission is to provide scientists with the largest repository of trustworthy protocols and intelligent analytical tools, thereby offering them extensive information to design robust protocols aimed at minimizing the risk of failures.

We believe that the most crucial aspect is to grant scientists access to a wide range of reliable sources and new useful tools that surpass human capabilities.

However, we trust in allowing scientists to determine how to construct their own protocols based on this information, as they are the experts in their field.

Ready to get started?

Sign up for free.
Registration takes 20 seconds.
Available from any computer
No download required

Sign up now

Revolutionizing how scientists
search and build protocols!