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What is MDS in statistics?
Multidimensional Scaling. Leanr more here: http://www.socialresearchmethods.net/tutorial/Flynn/mds.htm
What is the importance of scaling a bar graph?
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.
What is the difference between factor analysis with multidimensional scaling?
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.
Why do you use a broken bar graph?
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.
What are advantages and disadvantages of column chart and line graphs?
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.
