Quantitative Methods - Assignment Example

In this problem, where what influences the prices of a second hand car is determined; confounding variables could be colour, style, fuel, mot and condition. The main dependable variables could be the age, mileage and engine size. There are two methods to manage confounding, by analysis and design (Gravetter and Forzano 2012). By design comprises inclusion, randomization and exclusion decisive factors; by analysis comprises stratified and matched testing. Matching is more proficient to control confounding when the sample range is small.

In this case, Inflation could be an unwanted factor that affects prices and it is hard to avoid (Richardson 2011). Y denotes dependent variable, indicating a quantity that differs from entity throughout the sample, and is the key focus of interest. X1. Xk are independent variables, which also differ from various entities, and are contemplated to be correlated with Y. Lastly, ε is the residual expression, which denotes the composite impact of all other kinds of individual variances not explicitly recognized in the model (Black 2012).

In this regression, looking at age alone, it cannot provide explain much explanation though it shows correlation of second hand cars prices dependency (Richardson 2011). Looking at mileage only, it can explain more of the observed car prices variation in buying and selling costs. However, variations in mileage and age jointly can explain a bigger percentage of the variation in prices. The reason they can clarify more jointly than the computation of what they can elucidate individually is that mileage masquerades the effect of age in this data set.

When both are incorporated in the regression model, the impact of mileage is alienated from the impact of age, and the latter impact then is observed (Richardson 2011). In business, to be competitive, there must be a design quality into processes and products. Business must allow a process of