Quantitative Analysis

Figure adapted from: Linear coefficient of correlation betwixt beta-cell intensity and form load throughout the lifespan in Lewis bums: utilisation of beta-cell hyperplasia and hypertrophy. E Montanya, V Nacher, M Biarnes and J Soler (Diabetes 49:1341-1346, 2000) development the preceding(prenominal) chart address the questions listed below:(A)For the inset chart: put over AND explain whether the analog linkup depicted is a affirm to familiarity or an indirect/inverse descent. What would be a likely range for a analogue 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 equating represent? d) Using the inset graph and the above linear regression equation, calculate the predicted trunk weight of a blackleg if the Beta Cell Mass is 10.1 mg.. Answer: The linear association depicted in the graph shows a direct domineering relationship between ?-cell sight and personify weight. That is, there lead 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 be 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 expected interchange in ?-cell mass for a one-unit change in body weight. The real sum up 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 spy will be 3.36 g [= (0.016×10.1)... If you want to get a full essay, post it on our website: OrderEssay.net

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