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Spss statistic base

Manufactured by IBM
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Sourced in United States

SPSS Statistics Base is an analytical software tool that provides advanced statistical analysis capabilities. It offers a comprehensive set of features for data management, analysis, and reporting. SPSS Statistics Base is designed to help users efficiently explore, analyze, and interpret data.

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Lab products found in correlation

Spss 20, by IBM (5 mentions)

Close spelling variants of this product

SPSS Statistics Base SPSS Statistics base software SPSS Statistics Base 19.0 SPSS Statistics Base V 23 SPSS (Statistics Base ver. 23.0; SPSS Statistics Base Integrated Edition 23 SPSS Statistics Base 20 SPSS Statistics Base v22.0 SPSS Statistics Base program, version 22 SPSS Statistics Base 22.0 for Windows

6 protocols using spss statistic base

1

Statistical Analysis of Experimental Data

Check if the same lab product or an alternative is used in the 5 most similar protocols
Analysis of variance (ANOVA) and t-tests calculations were used to test (α = 0.05) for significant differences between factors and levels, where appropriate, using IBM SPSS statistic base (IBM, SPSS 20, Armonk, NY, USA). A comparison of the means was performed when the ANOVA indicated a significant difference by employing the Duncan test. The statistically significant differences in achieved results are given in the Results and Discussion paragraph whenever the data were evaluated.
Wronka A., Beer P, & Kowaluk G. (2022). Selected Properties of Single and Multi-Layered Particleboards with the Structure Modified by Fibers Implication. Materials, 15(23), 8530.
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2

Statistical Analysis of Experimental Data

Check if the same lab product or an alternative is used in the 5 most similar protocols
Analysis of variance (ANOVA) and t-tests calculations were used to test (α = 0.05) for significant differences between factors and levels, where appropriate, using IBM SPSS statistic base (IBM, SPSS 20, Armonk, NY, USA). A comparison of the means was performed when the ANOVA indicated a significant difference by employing the Duncan test.
Sala C.M., Robles E, & Kowaluk G. (2020). Influence of Adding Offcuts and Trims with a Recycling Approach on the Properties of High-Density Fibrous Composites. Polymers, 12(6), 1327.
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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
Analysis of variance (ANOVA) and t-tests calculations were used to test (α = 0.05) for significant differences between factors and levels, and where appropriate, using IBM SPSS statistic base (IBM, SPSS 20, Armonk, NY, USA). A comparison of the means was performed when the ANOVA indicated a significant difference by employing the Duncan test. The statistically significant differences in achieved results are given in the Results and Discussion paragraph whenever the data were evaluated.
Wronka A, & Kowaluk G. (2022). Upcycling Different Particle Sizes and Contents of Pine Branches into Particleboard. Polymers, 14(21), 4559.
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4

Statistical Analysis of Experimental Factors

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Analysis of variance (ANOVA) and t-test calculations were used to test (α = 0.05) for significant differences between factors and levels, using IBM SPSS statistic base (IBM, SPSS 20, Armonk, NY, USA) where appropriate. A comparison of the means was performed when the ANOVA indicated a significant difference by employing the Duncan test. The statistically significant differences in achieved results whenever the data were evaluated are given in the Results and Discussion section.
Wronka A, & Kowaluk G. (2022). The Influence of Multiple Mechanical Recycling of Particleboards on Their Selected Mechanical and Physical Properties. Materials, 15(23), 8487.
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5

Statistical Analysis of Experimental Data

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Analysis of variance (ANOVA) and t-tests calculations were used to test (α = 0.05) for significant differences between factors and levels, where appropriate, using IBM SPSS statistic base (IBM, SPSS 20, Armonk, NY, USA). A comparison of the means was performed when the ANOVA indicated a significant difference by employing the Duncan test.
Gumowska A., Robles E, & Kowaluk G. (2021). Evaluation of Functional Features of Lignocellulosic Particle Composites Containing Biopolymer Binders. Materials, 14(24), 7718.
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6

Statistical Analysis of Experimental Data

Check if the same lab product or an alternative is used in the 5 most similar protocols
Analysis of variance (ANOVA) and t-tests calculations were used to test (α = 0.05) for significant differences between factors and levels, where appropriate, using IBM SPSS statistic base (IBM, SPSS 20, Armonk, NY, USA). A comparison of the means was performed when the ANOVA indicated a significant difference by employing the Duncan test. The statistically significant differences for the achieved results are given in the Results and Discussion paragraph whenever the data were evaluated.
Wronka A., Robles E, & Kowaluk G. (2021). Upcycling and Recycling Potential of Selected Lignocellulosic Waste Biomass. Materials, 14(24), 7772.
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