Quantitative Analysis

Figure adapted from: Linear coefficient of correlation surrounded by beta-cell plenteousness and form burden throughout the lifespan in Lewis bums: use of goods and services of beta-cell hyperplasia and hypertrophy. E Montanya, V Nacher, M Biarnes and J Soler (Diabetes 49:1341-1346, 2000) victimisation the preceding(prenominal) chart address the questions listed below:(A)For the inset graphical record: enter AND explain whether the analog linkup depicted is a assume to link or an indirect/inverse descent. What would be a likely range for a additive correlation coefficient for this graph? Explain your reasoning. If given the linear regression equality [ lt;em>y = 0.016x + 3.2] which is in the form of y=mx+b: a) What does ?y represent? b) What does 0.016 in this equality represent? c) What does 3.2 in this compare represent? d) Using the inset graph and the above linear regression equation, calculate the predicted trunk weight of a grunter if the Beta Cell M ass is 10.1 mg.. Answer: The linear association depicted in the graph shows a direct dominate relationship between ?-cell bargain and body weight. That is, there bend up stakes greater ?-cell mass for excessive body weight. This strong relationship suggests a likely range for a linear correlation coefficient to be 0.9 ? 1.0 because the more closely the variables argon associated the higher the r value. Further, for the given linear regression equation y = 0.016x + 3.

2, the restricted variable ?y? represents the ?-cell mass in mg. The real sum 0.016 represents the magnitude of the linear relationship between ? -cell mass and body weight. That is, the ex! pected interchange in ?-cell mass for a one-unit change in body weight. The real itemise 3.2 in the equation is the value of ?-cell mass when body weight equals zero. Finally, if the ?-cell mass is 10.1 mg the predicted body weight of a shop will be 3.36 g [= (0.016×10.1)... If you want to get a full essay, post it on our website: OrderCustomPaper.com

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