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The slope deflection method is a structural analysis method for beams and frames introduced in 1914 by George A. Maney. [1] The slope deflection method was widely used for more than a decade until the moment distribution method was developed. In the book, "The Theory and Practice of Modern Framed Structures", written by J.B Johnson, C.W. Bryan ...
3.33% (1 in 30) – Umgeni Steam Railway, South Africa [24] 3.0% (1 in 33) – several sections of the Main Western line between Valley Heights and Katoomba in the Blue Mountains Australia. [25] 3.0% (1 in 33) – The entire Newmarket Line in central Auckland, New Zealand; 3.0% (1 in 33) – Otira Tunnel, New Zealand, which is equipped with ...
Physical constraints may limit the number of degrees of freedom of a single rigid body. For example, a block sliding around on a flat table has 3 DOF 2T1R consisting of two translations 2T and 1 rotation 1R. An XYZ positioning robot like SCARA has 3 DOF 3T lower mobility.
When only the equality of the two groups means is in question (i.e. whether μ 1 = μ 2), the studentized range distribution is similar to the Student's t distribution, differing only in that the first takes into account the number of means under consideration, and the critical value is adjusted accordingly. The more means under consideration ...
The following table lists values for t distributions with ν degrees of freedom for a range of one-sided or two-sided critical regions. The first column is ν , the percentages along the top are confidence levels α , {\displaystyle \ \alpha \ ,} and the numbers in the body of the table are the t α , n − 1 {\displaystyle t_{\alpha ,n-1 ...
Once the t value and degrees of freedom are determined, a p-value can be found using a table of values from Student's t-distribution. If the calculated p -value is below the threshold chosen for statistical significance (usually the 0.10, the 0.05, or 0.01 level), then the null hypothesis is rejected in favor of the alternative hypothesis.
When computing a t-test, it is important to keep in mind the degrees of freedom, which will depend on the level of the predictor (e.g., level 1 predictor or level 2 predictor). [5] For a level 1 predictor, the degrees of freedom are based on the number of level 1 predictors, the number of groups and the number of individual observations.
However, these must sum to 0 and so are constrained; the vector therefore must lie in a 2-dimensional subspace, and has 2 degrees of freedom. The remaining 3n − 3 degrees of freedom are in the residual vector (made up of n − 1 degrees of freedom within each of the populations).