Qualitative, Quantitative, and Mixed Method Approaches - Essay Example

"Qualitative, Quantitative, and Mixed Method Approaches" is an engrossing example of a paper on social and family issues. Each of the two approaches; quantitative and qualitative has its own weaknesses and strengths. The quantitative research approach requires the standardization of data collection by allowing comparison (Creswell, 2003). However, the data is static unlike in a qualitative approach in which flexibility allows one to respond to the data as it is in a session (Creswell, 2003). For the issue of obesity, the qualitative approach becomes the most effective because it will require naturalistic observation like ethnography and structured interviews. Unlike the quantitative research approach in which responses will be less flexible, the researcher on obesity in children will be able to observe and record opinions, behaviors, pain points and any other type of meaningful information for the issue.

Any statistical practice will require a focused problem definition in which a population is defined and a sample is drawn (Lohr, 1999). In the case of a psychologist who wants to study women in the process of obtaining a divorce, the most effective type of random sampling will be simple random. Since he has already established that 798 couples have filed for divorce, this will be his total population and 25 couples will be his sample size. In this case, all couples will be given an equal chance of selection in the sample. This way biasness will be reduced and it will be easy to analyze the obtained results.

When studying obesity in a small size of 10 adult men, it would be effective to get a trimmed mean; a statistical measure of central tendency. This is because the total population is manageable and getting the two ends will be simple. Trimmed mean is best fitted as it is robust and efficient for mixed and heavy-tailed distributions (Arulmozhi, 2009). The trimmed mean is not affected by outliers. The limitation of trimmed mean, in this case, is in case the population is asymmetric. Unless the population is symmetric, it will be difficult to give an estimator that is not biased.

Independent variables are physical inactivity, junk food consumption, and television viewing. These variables are the ones that will determine whether a child will be obese or not. Obesity, on the other hand, is the dependent variable because it will depend on physical inactivity, junk food consumption, and television viewing. Independent variables can be controlled or manipulated to see how they will affect the dependent variable (Dodge, 2003). Other independent variables that may influence obesity are stress, income level, and poverty level. Research shows that when a person is stressed he or she tends to engage in binge eating. There are also studies that establish that poverty and income level affects the choice of food a person eats.

Determinants that will have a negative correlation with bone density, in this case, are cigarette smoking. Negative correlation occurs when two variables, and in this case bone density and cigarette smoking, are related in that when one increases, the other one decreases and vice versa (Cohen et al., 2002). Research has proved that increased smoking among adolescents decreases bone density, and this establishes a negative correlation. The determinants with positive correlation with bone density in our case are body weight, physical activity, hormones, and calcium intake. This is because increasing these variables will result in increases bone density and vice versa.