Multivariate Statistics the Research Question Term Paper

Excerpt from Term Paper :

I might believe that other variables (such as gender and low income) have a more significant impact on the frequency of car accidents as compared to for instance the general belief that it is crime, and location that induce them.

Potential pitfall

Firstly, I have to ascertain that my operational terms of data are totally accurate and thorough, since the outcome depends on the data that is fed-in to the system.

Most significantly, however, the major conceptual limitation is that I can only ascertain a relationship but never be sure of the underlying causal factor. It may be a variable that is seemingly unrelated to the independent variables mentioned here and, therefore, has been overlooked. For instance, it may be a possibility that menopause may be responsible for inducing accidents; so even though the factor of age may have emerged as significant, the real problem -- menopause -- has remained concealed.

Another pitfall may be outliers in one or more of my variables that may distort statistical results, as well as the fact that the population sample may be insufficiently controlled or randomized so that 'noise' may distort the data.

Expected Deliverable

Performing the multivariate study will produce results of the variables that most closely impact the rate (or phenomena) of accident in Tucson, Arizona. I could, then, achieve a clear picture as to the one or more variables that are responsible, the rate of responsibility of these variables, and (amongst other results) whether my data results accords with previous conclusion on the subject. The results of the multivariate study, if implemented correctly, could be useful for scientific research, in general, and for preventing further accidents in Tucson in particular.

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