Answered You can hire a professional tutor to get the answer.
I need some assistance with these assignment. relation between speed and weight of cars Thank you in advance for the help!
I need some assistance with these assignment. relation between speed and weight of cars Thank you in advance for the help! Ideally, the speed of the vehicles will be the dependent variable while the weight of the vehicles will be the independent variable.
The first step in examining the relationship between the two variables is use a scatter plot. The aim of this step is to form a general pattern and establish whether there is any deviation from this general pattern. The next step will be taken if we shall establish the existence of a linear relationship between the two variables.
Figure 1 above shows how the weight of cars correlated with their speeds. A clear inverse linear relationship is evident, though not very strong as evidenced by large variation. This means that, generally, as the weight of the car is increased, the speed is reduced.
Figure 2 above shows how the weight of trucks correlated with their speeds. A clear inverse linear relationship is evident, which is very strong since variation is relatively low (Vining et al. 15). This means that, generally, as the weight of the tricks is increased, the speed is reduced. To supplement the graphs, a numerical measurement will be conducted through correlation. This technique measures the strength and direction of the linear relationship between the two variables. To do this, more columns are added to the raw data in the same manner that is done when calculating Pearson coefficient of correlation, as shown below:
Incidentally, the close r is to 1, the better the model since it is considered to be less subject to sampling errors. Therefore, the two models are relatively fit for performing the predictions because they are not too far from 1, but model one (cars) is stronger because it is nearer to 1 than model two.
Although it has been established that there is an inverse relationship between the variables in the two models, there is no evidence to show that these relationships have not resulted from other variables that have not been factored into the study (Vining et al. 15).
