Data Analysis Paper

The article is from the American Journal of Public health and provides surveys, graphs and statistics. The article has multiple authors and they are all in the medical field or professors that work at high prestige Universities like Harvard or Northwestern University.It was last modified on February of 2013.The article is a peer review journal and because of the credentials of the authors it seems reliable and credible

Biostatistics. I applied basic informatics techniques with vital statistics and public health records in the description of public health characteristics and in public health research and evaluation. [A.8] I used my knowledge of basic biostatistics to compare positive cases, test submissions, and human population to see if there was any correlation. Understanding biostatistics allowed me to make a valid and meaningful comparison of this data. The information gathered from the biostatistics gives a limited estimate of risk, and should be further evaluated to quantify this risk. The main goal of my project was to interpret the results of statistical analyses in terms of epidemiological human risk factors. [A.9]

Refer as needed to the material in Chapters 12 and 13 of the textbook. Keep the following tips in mind as you research data, as well as organize, analyze, interpret, and illustrate these data:

Daniel Fuller, Lise Gauvin, Yan Kestens, Mark Daniel, Michel Fournier, Patrick Morency, and Louis Drouin American Journal of Public Health 2013 !03;3. e85-e92. Print.

Identifying appropriate data sources to answer demographic information questions is challenging. While the widespread availability of existing data provides an opportunity for answering demographic information questions without the high expense associated with primary data collection, the data source must be chosen carefully to ensure that it can address the study question, that it has a sufficient number of observations, that key variables are available, there is an adequate confounder control and a sufficient length of the follow-up.

2) The systematic design, collection, analysis, and reporting of data and findings relevant to a specific

| Based on explicit knowledge and this can be easy and fast to capture and analyse.Results can be generalised to larger populationsCan be repeated – therefore good test re-test reliability and validityStatistical analyses and interpretation are

A percentage of results will be used to check accuracy via inputting means, standard deviations and minimum and maximum scoring of questionnaires, ensuring missing values are categorised correctly. Missing value analysis will be used to identify any trends and managed appropriately. If outliers are identified, transformation, alteration or deletion will commence. The skew and kurtosis will be tested for significance. Tests for homogeneity of variance will be performed and managed appropriately. Descriptive statistics will be obtained followed by between-subjects analyses e.g. ANOVA or MANOVA.

The authors of this article, Stafinski, T., Menon, D., a Professor & Senior Advisor/HTPU, and Philippon, D. J. are all professors from the same learning institution that is known for its credibility, School of Public Health, University of Alberta, Edmonton, AB, Canada. On the other hand, McCabe, C., is also a professor from the Academic Unit

14. Breslow L. Encyclopedia of public health. New York: Macmillan Reference USA/Gale Group Thomson Learning; 2002.

Observational epidemiology is a study of disease where “the investigator ascertains exposure and outcome without assignment to an intervention” Observational studies have made important contributions to the knowledge and understanding of health-related conditions. These studies usually involve a large group of individuals as in a community. The purpose of this type of study is to determine the

Generally this process can take up to a few days of observation to identify and tabulate the findings. Drawbacks of this method, can include the Hawthorne effect, extended periods of time and the need to be physically present at the location.

Quantitative studies are primarily numbers based. They deal with large cohort groups as well as analyze large amounts of data. “A quantitative

Data Collection is a vital aspect of any type of research study. Erroneous data collection can impact the results of a study and ultimately lead to invalid results. Data collection methods for impact evaluation vary along a scale. At the one end of this scale are quantitative methods and at the other end of the scale are Qualitative methods for data collection. Choosing a particular data collection method will depend on the accuracy of information they will yield and the practical considerations, such as, the need for personnel, time, equipment and other facilities, in relation to what is available

The objective of this chapter is to describe the procedures used in the analysis of the data and present the main findings. It also presents the different tests performed to help choose the appropriate model for the study. The chapter concludes by providing thorough statistical interpretation of the findings.