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Roof pitch is the steepness of a roof expressed as a ratio of inch(es) rise per horizontal foot (or their metric equivalent), or as the angle in degrees its surface deviates from the horizontal. A flat roof has a pitch of zero in either instance; all other roofs are pitched .
These variables include, building material of the envelope, thicknesses of the building materials, day of the year, time of day, orientation of the surface (e.g. wall or roof, 90 degrees or 180), and wall face orientation (cardinal directions, i.e. N, NW, S, SE, etc.), to name a few.
Ordinary least squares regression of Okun's law.Since the regression line does not miss any of the points by very much, the R 2 of the regression is relatively high.. In statistics, the coefficient of determination, denoted R 2 or r 2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the independent variable(s).
The square is an Imperial unit of area that is used in the construction industry in the United States and Canada, [1] and was historically used in Australia. One square is equal to 100 square feet. Examples where the unit is used are roofing shingles, metal roofing, vinyl siding, and fibercement siding products.
Framing square, or steel square, or carpenter's square, or roofing square Originally designed for timber framing, a framing square is made from a single flat piece of metal or polymer to a standardised design with a long, wide blade and at 90° to that a shorter, narrower tongue. It can also be used for measuring lengths and for calculating angles.
A sphere of radius r has surface area 4πr 2.. The surface area (symbol A) of a solid object is a measure of the total area that the surface of the object occupies. [1] The mathematical definition of surface area in the presence of curved surfaces is considerably more involved than the definition of arc length of one-dimensional curves, or of the surface area for polyhedra (i.e., objects with ...
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Linear least squares (LLS) is the least squares approximation of linear functions to data. It is a set of formulations for solving statistical problems involved in linear regression , including variants for ordinary (unweighted), weighted , and generalized (correlated) residuals .
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