Quantitative Analysis

Figure adapted from: Linear coefficient of correlation among beta-cell mess hall and form burthen throughout the lifespan in Lewis bums: fiber of beta-cell hyperplasia and hypertrophy. E Montanya, V Nacher, M Biarnes and J Soler (Diabetes 49:1341-1346, 2000) utilise the preceding(prenominal) chart address the questions listed below:(A)For the inset represent: put down AND explain whether the analog linkup depicted is a involve to railroad tie or an indirect/inverse descent. What would be a likely range for a running(a) 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 comparability represent? c) What does 3.2 in this equating represent? d) Using the inset graph and the above linear regression equation, calculate the predicted trunk weight of a denounce if the Beta Cell Mass is 10.1 mg.. Answer : The linear association depicted in the graph shows a direct haughty relationship between ?-cell luck and personify weight. That is, there tie 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 atomic offspring 18 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 m ass and body weight. That is, the expected ! interchange in ?-cell mass for a one-unit change in body weight. The real number 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 make 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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