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19.0 for windows

Manufactured by IBM
Sourced in United States

19.0 for Windows is a software product developed by IBM for laboratory equipment. It provides essential functionalities for managing and analyzing data from various laboratory instruments and experiments. The core function of this product is to enable data acquisition, processing, and visualization capabilities for users in a Windows-based computing environment.

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Lab products found in correlation

3 protocols using 19.0 for windows

1

Statistical Analysis of Experimental Data

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Statistical package 19.0 for Windows (SPSS, Chicago, IL, USA) was used for statistical analyses. The values were expressed as the mean ± standard deviation (mean ±SD). The data were analyzed by the paired-sample t-test or one-way analysis of variance, and p<0.05 was considered statistically significant. All experiments were performed in triplicate.
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2

Statistical Analysis of Experimental Data

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Statistical analysis was performed using the average results of three experiments under identical conditions. Numerical data are presented as the mean ± standard deviation. Differences between two means were compared by Student's t-test. A one-way analysis of variance was performed for multiple comparisons of groups, which was followed by the Fisher's least signi cant difference post hoc test, and associated parameters were further analysed using the Spearman's correlation test. Data were analysed using 19.0 for Windows (SPSS Inc., Chicago, IL, USA). P < 0.05 was considered to indicate a statistically signi cant difference.
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3

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 the average results of three experiments under identical conditions. Numerical data are presented as the mean ± standard deviation. Differences between two means were compared by Student's t-test. A one-way analysis of variance was performed for multiple comparisons of groups, which was followed by the Fisher's least signi cant difference post hoc test, and associated parameters were further analysed using the Spearman's correlation test. Data were analysed using 19.0 for Windows (SPSS Inc., Chicago, IL, USA). P < 0.05 was considered to indicate a statistically signi cant difference.
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