Quantitative Research on Marathon Times Essay Example | Topics and Well Written Essays - 2500 words

Quantitative Research on Marathon Times - judge ExampleEven though endurance contest running has increased its popularity, there exist no data concerning the relationship between marathon times, age, athletes level of fitness (expert runner, beginner), fuel (carbohydrates), weather in the course of the marathon, and the miles ran during training per week. This paper sought to find out whether the performance of marathon is linked to age, athletes level of fitness (expert runner, beginner), fuel (carbohydrates), weather in the course of the marathon, and the miles ran during training per week. The study involved 15 marathon runners. The participants were given packets of materials which were inclusive of a questionnaire. After filling the questionnaire, they were brought back for analysis. The study established that there existed some relationship among the variables.IntroductionFor decades, taking part in marathon running by people of different ages and potentials has been increa sing at a repaid rate. A research conducted in this field notes out that the approximate marathon number in U S increased to one hundred and forty in 1975 from forty-four in 1969. In this period, there was an increment in the participants by about cholecalciferol%. Even though marathon is always popular and requires enough preparation, training practice and knowledge, its effectiveness may tend to remain incomplete. More often than not, more runners come up with their programs of training through taking after marathoners who may look successful. For many years, the philosophy of humans has been adjusted to c everywhere distances that be dogged in each day so as to obtain food for sustaining the metabolism of the brain (Macarthur & North, 2005). In this regard, the high marathon popularity in humans that ar modern of all abilities and ages can be seen as a legacy of the human species evolutionary capacity to race for distances that are long and using metabolism that is aerobic (Macarthur & North, 2005). Over the last decade, the starters in marathon have increased from 8,000 to 40,000. This implies that taking part in road racing has been increasing by over 50% in the last decade. This popularity is characterized by the existence of recreational marathon racers who finish the 42,195 km in about two hours. However, marathon has a nix effect to the cardiac status and the existences of cardiac deaths that are sudden during marathon have evoked increased debate (Macarthur & North, 2005). Additionally, endurance and energy cost are the two benchmarks for obtaining exceptional performance in running. This is so because marathon runners show out an increased fractional use of oxygen. Considering the coming up of recreational marathon amid the middle-aged class, the debate concerning physiological strain also comes up. A couple of surveys done in marathoners have failed to give out information which could be conclude for the runners broad spectrum. This study e xplores the relationship between one dependent variable and several independent variables. In this regard, the dependent variable is marathon times, whereas the independent variables are age, athletes level of fitness (expert runner, beginner), fuel (carbohydrates), weather in the course of the marathon, and the miles ran during training per week. The paper seeks to develop a ternary regression model in which the variable that is dependent is explained by all the given independent variable. Method Participants The opportunity sample for this study was made up of fifteen participants. The participants were obtained from marathon runners. The participants were selected by using the fact that they had to be individuals whose age was below forty years and that they were recreational runners. The participants were also free of pulmonary and cardiac diseases. The participants of this research were volunteers. Three groups consisting of five participants were made. The three groups were g iven names according to the age range. The first group, which was the 10 to 20 years group,