Discussion post response

Please read and responsd to the following student post. 150 words each.

Post 1 (S.B)

Statistics can be incredibly usefully when conducting research concerning health information management. “Descriptive statistics are meant to describe a large amount of data by illustrating the data with charts, graphs, and tables in a way that the data is summarized and organized.” (Health Information Management, 2016). Inferential statistics is used differently. Rather than describing the data it is “used to test a hypothesis and draw conclusions and the population.” (Health Information Management, 2016).

Statistics are a driving force in the healthcare industry as more emphasis is placed on such concerns as research, risk analysis and improving patient satisfaction. These areas can be examined closer by using statistics to understand the data being generated. Statistics can be used to understand relationships between populations and disease, whether preventative care is beneficial or if building a new urgent care in a specific location would be prudent. The possibilities for research increase as the amount of data increases.

“The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research.” (Belle, Thiagarajan, Soroushmehr, Navidi & Najarian, 2015). Descriptive statistics can help organize the information, while inferential statics can be used to understand the relationships between the data being produced.

Belle, A., Thiagarajan, R., Soroushmehr, S. R., Navidi, F., Beard, D. A., & Najarian, K. (2015). Big Data Analytics in Healthcare. Biomed Research International, 2015370194. doi:10.1155/2015/370194

Oachs, Pamela K. and Watters, Amy, L. (Eds.). (2016). Health Information Management Concepts, Principles and Practice.

Post 2 (J.E)

Descriptive statistics make data easier to comprehend by description and summarization (Conner, 2017). The specific parts of a set of data are interpreted by conducting summaries and short observations, that assist in uncovering patterns in the sample (Conner, 2017). Some common types of descriptive statistics are mean, mode, and median which are central tendency measures (Conner, 2017). The main part of frequency distribution for a set of data is used by these measures (Conner, 2017). Dispersion and measures of variability describe the spread of values along a set of data but are less commonly used (Conner, 2017).

Inferential statistics are used to make an educated guess on the characteristics of a data sample and allow one to generalize beyond the data that is present (Halfens, 2013). There are a variety of sample types such as, probability, simple random, stratified or systematic (Halfens, 2013). The tests conducted generally fall under parametric and non-parametric tests (Halfens, 2013). Parametric tests need many assumptions, such as requiring normally distributed data (Halfens, 2013). Non-parametric tests are more lenient on assumptions, allowing the use of uncommon variables at the cost of reduced accuracy compared to parametric tests (Halfens, 2013).

A common inferential statistical method is the chi-squared test (Halfens, 2013). This categorical test compares the differences between the observed information and the frequencies that are expected (Halfens, 2013). Frequencies that have no relationship between the two variables fall under expected frequencies (Halfens, 2013). When there is a probability that the two means are similar to each other, a probability is given (Halfens, 2013). It is concluded that there is a significant difference between the two means when the probability value is less than 0.05 (Halfens, 2013). Other inferential statistic methods include, ANOVA/ANCOVA, Wilcoxon, Mann-Whitney, among others (Conner, 2017).

Al-Benna, S. A.-A. (2010). Descriptive and inferential statistical methods used in burns research. Burns, 36, 343-346. doi:10.1016/j.burns.2009.04.030.

Conner, B. &. (2017). Descriptive statistics: Use these tools to analyze data vital to practice-improvement projects. American Nurse Today, 12(11), 52-55.

Halfens, R. &. (2013). Back to basics: an introduction to statistics. Journal Of Wound Care, 22(5), 248-251.