Anorexia Research and Hypothesis Testing

Anorexia Research and Hypothesis Testing

Abstract
Teenage anorexia in females within the US and Europe is a significant concern for health professional, and families. Identifying true causes of this disease will allow for health service professionals to develop accurate and effective treatment plans. Utilizing hypothesis testing for the determining the viability of various null hypotheses will aid in this endeavor.Anorexia Research and Hypothesis Testing

1) Purpose of null hypothesis testing and provide examples of a null hypothesis that may be tested within a data set.
A null hypothesis may function as a useful statistical tool for determining the factors and/or causes that may lead to the development of anorexia in teenage girls. Utilizing hypothesis testing, a null hypothesis will be compared to an alternative hypothesis by application of a statistical t-test and/or f-test. A qualitative study of a significant population of individuals may lead to a determination of true cause. Furthermore, the Null Hypothesis may be considered as a control. For example, if one assumes that the leading cause for teenage anorexia is socio-cultural stressors, then this is the Alternative hypothesis and the null hypothesis is that socio-cultural stressors are not the leading cause (Nilsson et.al, 2007).Anorexia Research and Hypothesis Testing

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2) Explain the logic of hypothesis testing and the role of the null hypothesis.
The scientific method always utilizes incorporation of a hypothesis. Subsequently, the hypothesis should be tested using a data set that will be composed of a significant number of variables. The null hypothesis will be true when there is no data that demonstrates a significant difference between the proposed hypothesis/cause and a normal outcome.

1) Differentiate between descriptive and inferential statistics and how they support the human services research process.
Descriptive statistics may be used for determining a quantitative conclusion within a particular data set. In contrast inferential statistics will consider cause and effect of an outcome of an attribute within that data set. With human services research, both should be employed to determine quantitative information and to draw conclusions.

2) Provide an example of a study that is a logical follow-up to your data set that yields useful descriptive data.
The study conducted by Nilsson et.al, presents useful descriptive data for quantifying causes of teenage anorexia occurrences. (see references section)Anorexia Research and Hypothesis Testing

3) Provide an example of a study that is a logical follow-up to your data set that yields useful inferential statistics.
The study performed by (Exterkate et.al, 2009) provides statistical information that may be used to conduct inferential analysis for determining correlation of specific socio-cultural images and their correlation to teenage anorexia in females.

4) Provide an example of a null hypothesis inspired by your data set that adds to the human service community’s knowledge. Proving true or false the null hypothesis: Family and self image does not contribute to female teenage anorexia will help physicians and therapists to identify accurately and treat the underlying factors of this disorder.Anorexia Research and Hypothesis Testing

In conclusion, ruing out these causes will allow clinical and human service workers to identify and address true influences.

References
Exterkate, C. C., Vriesendorp, P. F., & Jong, C. A. (2009). Body attitudes in patients with eating disorders at presentation and completion of intensive outpatient day treatment.Eating Behaviors. doi:10.1016/j.eatbeh.2008.10.002
Nilsson, K., Abrahamsson, E., Torbiornsson, A., & Hägglöf, B. (2007). Causes of Adolescent Onset Anorexia Nervosa: Patient Perspectives. Eating Disorders. doi:10.1080/10640260701190642

Anorexia Research and Hypothesis Testing