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The correlation coefficient ranges from 0 to ±1. The sign of the correlation coefficient shows the correlation as positive (as one increases so does the other) or negative (as one increases the other decreases). 0 represent no correlation and ±1 represents perfect correlation. The further from 0 towards ±1, the stronger the correlation, ie the greater the absolute value* of the correlation coefficient the stronger the correlation. To have a stronger correlation than -0.54 the absolute value must be greater than 0.54; ie all correlation coefficients that are less than -0.54 (eg -0.6, -0.9) and all those greater than +0.54 (eg 0.7, 0.95) are stronger correlations. Mathematically speaking, all those with a correlation coefficient r such that |r| > 0.54 *The absolute value of a number is the number ignoring its sign (ie how far it is away from 0 ignoring the direction along the number line), eg |56| = 56 |-45| = 45 |-56| = 56 Thus |-56| = |56| = 56.
From Laerd Statistics:The Pearson product-moment correlation coefficient (or Pearson correlation coefficient for short) is a measure of the strength of a linear association between two variables and is denoted by r. Basically, a Pearson product-moment correlation attempts to draw a line of best fit through the data of two variables, and the Pearson correlation coefficient, r, indicates how far away all these data points are to this line of best fit (how well the data points fit this new model/line of best fit).
Whenever you are given a series of data points, you make a linear regression by estimating a line that comes as close to running through the points as possible. To maximize the accuracy of this line, it is constructed as a Least Square Regression Line (LSRL for short). The regression is the difference between the actual y value of a data point and the y value predicted by your line, and the LSRL minimizes the sum of all the squares of your regression on the line. A Correlation is a number between -1 and 1 that indicates how well a straight line represents a series of points. A value greater than one means it shows a positive slope; a value less than one, a negative slope. The farther away the correlation is from 0, the less accurately a straight line describes the data.
Yes, if the incline angle becomes great enough. > As the angle increases, the force on the object down the incline increases but the effective weight on the slope surface decreases. > When the object breaks away the angle of incline can be used to calculate the coefficient of friction between the two surfaces. > coefficient of friction = sine ( incline angle ) / cosine ( incline angle )
The term regression means to take back. To regress you take away something not in a physical form. For example in old age pensioners can often suffer from memory regression where they are mentally taken back to times past.
Relationship between Lorenz curve and Gini coefficient is the more the Lorenz line curves away from the line of equality, the greater the degree of inequality represented.
It masses increases and the weight increases
When rainfall increases erosion increases, wearing away the mountains and cliffs and filling in the canyons with the products of erosion.
"Explain why operating leverage decreases as a company increases sales and shifts away from the break-even point."
Intensity
It increases.
-- Its speed increases. -- Its wavelength increases. -- It refracts away from the normal to the interface at the point of incidence.