matlab 2019 statistics Search Results


matlab 2019 statistics  (MathWorks Inc)
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matlab version 2019b  (MathWorks Inc)
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origin pro 2019  (OriginLab corp)
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matlab r2018a  (SAS institute)
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origin 2019  (OriginLab corp)
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jmp  (SAS institute)
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statview 5.0  (SAS institute)
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spm toolbox in matlab  (MathWorks Inc)
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MathWorks Inc spm toolbox in matlab
Fig. 1. Upper row shows the results for the three UCM components (UCM‖, UCM and UCMratio) for different shoes (H: 50 mm, M: 35 mm and L: 27 mm) as mean (thicker lines) ± standard deviations (upper and lower thinner lines). The average of two running speed conditions are represented for each shoe condition. Lower row shows the corresponding <t>SPM</t> <t>rmANOVA</t> results for the main factor shoe. F* values indicate the corresponding thresholds for α = 0.05.
Spm Toolbox In Matlab, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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statistics 26  (SPSS Inc)
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SPSS Inc statistics 26
Fig. 1. Upper row shows the results for the three UCM components (UCM‖, UCM and UCMratio) for different shoes (H: 50 mm, M: 35 mm and L: 27 mm) as mean (thicker lines) ± standard deviations (upper and lower thinner lines). The average of two running speed conditions are represented for each shoe condition. Lower row shows the corresponding <t>SPM</t> <t>rmANOVA</t> results for the main factor shoe. F* values indicate the corresponding thresholds for α = 0.05.
Statistics 26, supplied by SPSS Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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rstudio version 1.2.5033  (RStudio)
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RStudio rstudio version 1.2.5033
Fig. 1. Upper row shows the results for the three UCM components (UCM‖, UCM and UCMratio) for different shoes (H: 50 mm, M: 35 mm and L: 27 mm) as mean (thicker lines) ± standard deviations (upper and lower thinner lines). The average of two running speed conditions are represented for each shoe condition. Lower row shows the corresponding <t>SPM</t> <t>rmANOVA</t> results for the main factor shoe. F* values indicate the corresponding thresholds for α = 0.05.
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microsoft excel  (MathWorks Inc)
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MathWorks Inc microsoft excel
Fig. 1. Upper row shows the results for the three UCM components (UCM‖, UCM and UCMratio) for different shoes (H: 50 mm, M: 35 mm and L: 27 mm) as mean (thicker lines) ± standard deviations (upper and lower thinner lines). The average of two running speed conditions are represented for each shoe condition. Lower row shows the corresponding <t>SPM</t> <t>rmANOVA</t> results for the main factor shoe. F* values indicate the corresponding thresholds for α = 0.05.
Microsoft Excel, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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antenna systems  (MathWorks Inc)
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MathWorks Inc antenna systems
Fig. 1. Upper row shows the results for the three UCM components (UCM‖, UCM and UCMratio) for different shoes (H: 50 mm, M: 35 mm and L: 27 mm) as mean (thicker lines) ± standard deviations (upper and lower thinner lines). The average of two running speed conditions are represented for each shoe condition. Lower row shows the corresponding <t>SPM</t> <t>rmANOVA</t> results for the main factor shoe. F* values indicate the corresponding thresholds for α = 0.05.
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Image Search Results


Fig. 1. Upper row shows the results for the three UCM components (UCM‖, UCM and UCMratio) for different shoes (H: 50 mm, M: 35 mm and L: 27 mm) as mean (thicker lines) ± standard deviations (upper and lower thinner lines). The average of two running speed conditions are represented for each shoe condition. Lower row shows the corresponding SPM rmANOVA results for the main factor shoe. F* values indicate the corresponding thresholds for α = 0.05.

Journal: Journal of biomechanics

Article Title: The effects of different shoe stack heights and running speeds on full-body running coordination: An uncontrolled manifold analysis.

doi: 10.1016/j.jbiomech.2025.112615

Figure Lengend Snippet: Fig. 1. Upper row shows the results for the three UCM components (UCM‖, UCM and UCMratio) for different shoes (H: 50 mm, M: 35 mm and L: 27 mm) as mean (thicker lines) ± standard deviations (upper and lower thinner lines). The average of two running speed conditions are represented for each shoe condition. Lower row shows the corresponding SPM rmANOVA results for the main factor shoe. F* values indicate the corresponding thresholds for α = 0.05.

Article Snippet: The time series of the three UCM components (UCM‖, UCM�, UCMratio) were analyzed with statistical parametric mapping (SPM) repeated measures analysis of variance (rmANOVA) by using the SPM toolbox in MATLAB (spm1d toolbox; (Pataky et al., 2019).

Techniques:

Fig. 2. Upper row shows the results for the three UCM components (UCM‖, UCM and UCMratio) for different running speeds (10 km/h and 15 km/h) as mean (thicker lines) ± standard deviations (upper and lower thinner lines). The average of three shoe conditions are represented for each running speed. The significant speed effects in SPM rmANOVA are shown as the gray areas. Lower row shows the corresponding SPM rmANOVA results for the main factor speed with clustered p- values. F* values indicate the corresponding thresholds for α = 0.05.

Journal: Journal of biomechanics

Article Title: The effects of different shoe stack heights and running speeds on full-body running coordination: An uncontrolled manifold analysis.

doi: 10.1016/j.jbiomech.2025.112615

Figure Lengend Snippet: Fig. 2. Upper row shows the results for the three UCM components (UCM‖, UCM and UCMratio) for different running speeds (10 km/h and 15 km/h) as mean (thicker lines) ± standard deviations (upper and lower thinner lines). The average of three shoe conditions are represented for each running speed. The significant speed effects in SPM rmANOVA are shown as the gray areas. Lower row shows the corresponding SPM rmANOVA results for the main factor speed with clustered p- values. F* values indicate the corresponding thresholds for α = 0.05.

Article Snippet: The time series of the three UCM components (UCM‖, UCM�, UCMratio) were analyzed with statistical parametric mapping (SPM) repeated measures analysis of variance (rmANOVA) by using the SPM toolbox in MATLAB (spm1d toolbox; (Pataky et al., 2019).

Techniques:

Fig. 3. SPM rmANOVA results for the interaction effects between shoe and speed conditions. F* values indicate the corresponding thresholds for α = 0.05.

Journal: Journal of biomechanics

Article Title: The effects of different shoe stack heights and running speeds on full-body running coordination: An uncontrolled manifold analysis.

doi: 10.1016/j.jbiomech.2025.112615

Figure Lengend Snippet: Fig. 3. SPM rmANOVA results for the interaction effects between shoe and speed conditions. F* values indicate the corresponding thresholds for α = 0.05.

Article Snippet: The time series of the three UCM components (UCM‖, UCM�, UCMratio) were analyzed with statistical parametric mapping (SPM) repeated measures analysis of variance (rmANOVA) by using the SPM toolbox in MATLAB (spm1d toolbox; (Pataky et al., 2019).

Techniques: