Multidimensional Scaling. Leanr more here: http://www.socialresearchmethods.net/tutorial/Flynn/mds.htm
scaling a bar graph can be used for two reasons, to jump past a large group of numbers unused (say the bar graph goes from 1-1000 but none of the data starts below 500) Scaling can be important to emphasize a difference in numbers too, suppose item a is at 700, item b is at 850, and item c is at 1000. if your bar graph jumps from 1 to 500 and then goes up in increments of 100, it can make 700 look like its far less than 850 or 1000. this is usually a business tactic done to impress board members when presenting lackluster numbers.
Multidimensional scaling (MDS): Is a family of distance and scalar-product (factor) and other conjoint models. It re-scales a set of dis/similarity data into distances and produces the low-dimensional configuration that generated them. Factor Analysis / Principal Components Analysis (FA/PCA), by contrast: PCA is the full reduction of set of scalar-products to a new orthogonal set of spanning dimensions (components); FA is a dimension-reducing model (properly containing communalities and not 1 in diagonal) to orthogonal or oblique dimensions (factors). In general usage, PCA and FA are primarily dimensional and use interval-level data, whereas MDS usually uses an ordinal (non-metric) transformation of the data producing a spatial configuration where dimensions are arbitrary.
A broken bar graph is used when one value, or a few values, goes up very high. Instead of scaling everything down, the abnormally high value is indicated with the broken bar graph. Of course, a number also has to be indicated, so that anybody who reads the bar graph can find out what the number actually is.
Colum charts and line graphs are both very handy but line charts can be made desceptive if scaling along the axis is done wrong, for example to let trendlines appear to show a much faster grow rate than it actually is. Histograms (column charts) are easy to see at once and to understand but they dont allow for performing regression or interpolation.
A scaling tower and scaling ladder are both used to scale walls. A scaling tower is better though
Hyung Ahn has written: 'Effects of missing responses in multiple choice data on dual scaling results' -- subject(s): Multiple-choice examinations, Item response theory, Scaling (Social sciences)
Alan T. Nettles has written: 'Scaling effects in carbon/epoxy laminates under transverse quasi-staic loading' -- subject(s): Scaling, Impact tests, Static loads, Static tests, Epoxy matrix composites
A SCALING LADDER A SCALING TOWER A BATTERING RAM A LONGBOW A CATULPULT ALL OF THESE WERE USED TO ATTACK CASTLES
Scaling- when you multiply or divide equivalent fractions
The scaling factor is 9/3 = 3
a scaling tower with a battering ram attached to it
Cliff scaling can be interpreted two ways. If someone is scaling the fiscal cliff, they are trying to manage cash flow so that cash does not run out. If a person is climbing a rocky overhang or the side of a mountain, they are cliff scaling.
ITS SCALING... and well scaling is a part of treatment for Pyrrohea... its not the whole and sole treatment.... the full treatment consists of scaling and then Flap surgery.....
Taking an existing IC design and scaling the components smaller.
scaling is the resizing of picturs
The difference between multidimensional and dimensional scaling is in terms of relationship between physical characteristic and dimension. In the case of multidimensional scaling, each dimension can be connected to 2 or more physical characteristics, unlike dimensional scaling..