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Regression refers to a statistical technique that analysts deploy to evaluate the relationship that exists between an independent and a dependent variable. The outcome of a regression analysis facilitates the prediction of the value of the dependent variable for a known value of an independent variable (Samprit & Hadi, 2006). The predictability aspect of regression analysis is of significant value when undertaking daily activities such as decision-making, analysis of problems, risk assessment and research activities (Wang & Chaman, 2003). This paper discusses a few day-to-day or work situations that involve the use of regression, either consciously or not.

The use of regression is evident on an everyday basis. For instance, in a business context, proper dressing associates with financial success, using celebrities on commercial advertisements strives to reach a wider audience, and physical attendance of an employee translates to employee productivity. It is apparent that these associations base on a quantitative regression analysis that attempts to derive at a formula for explaining how the situations relate. As a result, it allows for making accurate predictions when designing a commercial advertisement or estimating the levels of employee productivity. For instance, in the domestic level, the use of regression can take various forms such as comparing the cost of power consumed and the types and number of appliances in a household, and evaluating daily expense with the size of the household. As a result, a person can use regression to predict the level of household expenditures. In the school context, regression can be used to determine how student attendance affects academic outcomes and measure the effectiveness of instructional strategies using academic performance. Similarly, learning institutions can predict academic performances when deploying certain strategies.. Predictions can also be used in forecasts such as expected time of arrival during travels, or sales and profit forecasts by companies. In addition, regression can also be used in health care for determining the dosage required for people with different variables such as weight and age (Wang & Chaman, 2003).

In conclusion, the goal of regression is to establish the nature of relationship between two variables. Once the relationships established, predictions can be made that facilitate in the process of decision-making and analysis of problem situations. In addition, prediction capabilities of regression play an integral role in everyday activities by facilitating the risk assessment and facilitating research.

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