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Graph pad 5.0 for windows

Manufactured by GraphPad
Sourced in United States

GraphPad 5.0 for Windows is a software package for scientific data analysis and graphing. It provides tools for curve fitting, statistical analysis, and creating publication-quality graphs and figures. The software is designed to be user-friendly and offers a range of features to assist researchers in data visualization and interpretation.

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8 protocols using graph pad 5.0 for windows

1

Metabolomic Analysis of Dental Caries

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Data handling was done using Microsoft Excel 2016, GraphPad 5.0 for Windows (GraphPad Software, San Diego, CA, USA), and MetaboAnalyst 4.0 (https://www.metaboanalyst.ca/)48 (link)–50 (link). For statistical evaluation, analytes that could be quantified (S/N > 10) in more than 80% of the samples per group were used. The data were log transformed. To evaluate the significant differences among the caries-free, caries-rehabilitated, and caries-active groups, univariate analysis was performed by one-way ANOVA. The FDR was set to default (0.05). Further information is found in the figure descriptions.
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2

Statistical Analysis of Experimental Data

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The data were graphed using Graph Pad 5.0 for Windows (GraphPad Software, La Jolla, CA, USA). The statistical significance was analyzed by one-way analysis of variance (ANOVA) using either Bonferroni’s multiple comparisons test or Dunn′s multiple comparison test. A p-value < 0.05 was considered significant.
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3

Anticancer and Antimicrobial Assays

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The data was collected and graphed using Microsoft Excel and Graph Pad 5.0 for Windows for statistical analysis. The anticancer assay and antimicrobial activities of the plant extracts were analyzed by one-way analysis of variance (ANOVA) using Dunnett’s Multiple Comparison Test. P-value <0.05 was considered as significant.
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4

Statistical Analysis of Experimental Data

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The data were graphed using Graph Pad 5.0 for Windows (GraphPad Software, La Jolla, CA, U.S.A.). The statistical significance was analyzed using one-way analysis of variance (ANOVA) using either Bonferroni’s multiple comparisons test or Dunnett’s multiple comparison test. P-value < 0.05 was considered significant.
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5

Statistical Analysis of Experimental Data

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The data was graphed using Graph Pad5.0 for Windows (GraphPad Software, La Jolla, CA, USA). The statistical significance was analyzed using one-way or two-way analysis of variance (ANOVA) using either Bonferroni’s multiple comparisons test or Dunn’s Multiple Comparison Test. P-value < 0.05 was considered significant.
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6

Comprehensive Statistical Analysis of Experimental Data

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All statistical analyses were performed using Graph Pad® 5.0 for Windows. Data were tested for normality by the selection of parametric and non-parametric tests. Data were analyzed by a Two-way analysis of variance for repeated measures (Two-way RM ANOVA) followed by a Bonferroni’s multiple comparison test or Student’s t-test, as required. Differences were considered significant only when P-values were less than 0.05.
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7

Antifungal Activity of Plant Extracts

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The data was collected and graphed using Microsoft Excel®. Data was then exported to Graph Pad 5.0 for Windows (GraphPad Software, La Jolla, CA, USA) for statistical analysis. The effects of plant extracts on C. albicans inoculated onto solid agar media, liquid broth and during biofilm formation was analyzed using one-way analysis of variance (ANOVA) using Dunnett’s Multiple Comparison Test. P value <0.05 was considered as significant.
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8

Multivariate Analysis of Infertility Factors

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To check the normal distribution of the samples, we used the Kolmogorov-Smirnov and the Shapiro-Wilk test. For variables with normal distribution, we used the unpaired t-test for comparison; in the absence of a normal distribution, we used the Mann-Whitney test. The quantitative variables were represented as mean and standard deviation. For qualitative variables, we used the Fisher and Chi-square tests. The level of significance adopted was 5% with a power of 80%. In addition, we ran a multivariate analysis to assess the prediction of the covariables: age, time and cause of infertility and the number of visits to the clinic on the number of mature oocytes. We ran the statistical analysis with the aid of the SPSS 16.0 for Windows (SPSS Inc., Chicago, Illinois, USA), SAS 9.0 (SAS Institue Inc., North Caroline University, USA) and the GraphPad 5.0 for Windows (GraphPad Software, San Diego, California, USA).
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