A chemist employed by a pharmaceutical firm has developed a muscle relaxant. She

Question

A chemist employed by a pharmaceutical firm has developed a muscle relaxant. She took a
sample of 14 people suffering from extreme muscle constriction. She gave each a vial
containing a dose (X) of the drug and recorded the time to relief (Y) measured in seconds for
each. She fit a curvilinear model to this data and linear model. You are invited to evaluate
advantages and limitations of each model:
I) For Linear Model:
1. Advantages and limitations
2. Specific features.
3. Statistical indicators.
4. Forecasting based on the model.
5. Your example of use

II) For Curvilinear Model:
1. Advantages and limitations
2. Specific features.
3. Statistical indicators.
4. Forecasting based on the model.
5. Your example of use

Explanation / Answer

Linear model

r(x,y) = cov(x,y)/s.d(x)*s.d(y)

We forecast that the variables are correlated or not using the model

Curvilinear model

It is the mathematical measure of the average relationship between two or more variables in terms of the original unites of the data.

If thre variables in the bivariate distribution are related we will find the points in the scatter diagram will cluster round some curve called curve of regression. If the curve is a straight line it is called the line of regression and there is said to be linear regression between the variables .

Regression line gives the best estimate to the value of one variable for any specific value of the other variable thus the line of regression is the best fit and is obtained by using principal of least squares.

It is used to determine the value of the constants a and b in the given line equation

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