Statistics constitute part of daily life since most of the activities and encounters of we go through on daily basis comprise of statistical information ( Wild, Utts & Horton, 2018 ). There are different types of statistics as applied in varied contexts including but not limited to academics, health care, management, general research and problem solving. For this reason, it is essential to understand different types of statistics and how to apply them so as to optimally benefit from the goals of statistics in every situation. Determining the kind of statics use depends on the contexts in which the statistics have to be used and their applicability to the specific contexts. For instance, qualitative research uses statistics that are different from qualitative research. The aim of this paper therefore, is to determine the kind of statistics and statistical techniques to be used in different contexts by first of all reflecting upon the learning of this module followed by a review three studies. Under every study, focal information include the types of statistical techniques that were utilized by the researcher, reasons why the researcher selected the statistical techniques used and possibilities of other statistical techniques that would have been applicable in similar contexts to yield better results.
Lessons from the Module
In this module, I learnt about the nature, essence and applicability of different types of statistics. I learned that statistics is a science or practice that involves systematic collection and analysis of both numerical and descriptive data in large sizes or quantities especially for the purposes of making inferences about proportions using those in a representative sample ( Mai, 2016 ). Statistics consist of data consisting of aggregates of truth or facts. In determining the statistics of a particular phenomenon, the researcher must do it in relation to how it is affected by other variables. Therefore, statistics are yielded after examining the relationship between independent and dependent variables and how they are affected by intervening variables. Additionally, there is an aspect of accuracy in statistics since the rules of inference should be met. I also learned that statistics are collected with a predetermined purpose and in a systematic manner. Further in this module, I learned of different types of statistics based on the procedures used to collect them such as regression, Analysis of variance (ANOVA), Correlation, Chi-squared test, factor analysis, Mann–Whitney U, Regression analysis, Pearson product-moment correlation coefficient and Mean square weighted deviation (MSWD) among other types (Pyrczak, 2016). Lastly, I learned that these statistical tests are applied depending on a number of factors including the purpose of the study/statistics, the contexts including characteristics of the population being studied, and tools available for use among other pertinent factors.
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Analysis of the Paper
This section identifies three distinct studies and analyzes statistical techniques that the researchers used in those studies, possible reasons for their choices and alternative approaches applicable to the same studies. These studies include; the study by Anne Andermann (2016), Bharath Chakravarthy, Shyam Shah and Shahram Lotfipour (2013) and Bodson et al., (2017).
First Study: Taking action on the social determinants of health in clinical practice: a framework for health professionals.
The study by Andermann (2016), “Taking action on the social determinants of health in clinical practice: a framework for health professionals” is aimed at establishing possible remedies to some of the social factors that undermine the health of some groups of individuals in the community. The study uses descriptive statistics as the main approach to the collection and analysis of data. This is because it is conducted within the community and the main form of statistics required is descriptive in nature. It takes into account the perceptions, opinions and views of the community members. It is therefore qualitative in nature. According to Palinkas et. al., (2015), qualitative research studies require in-depth investigation of participants and regards paramount the contexts and other factors that are likely to affect the participants and their responses, hence the effect to the study.
The researcher selected descriptive statistics in order to effectively yield the kind of data that was required. Additionally, descriptive statistics are in direct conformity to the requirements of the qualitative studies and this is a typical qualitative study (Cox, D. R. (2018). Selecting a different technique would mean either compromising the outcomes of the study or adjusting the nature of the study to fit into the ideal contexts of a different method. For instance, in the case of this study, perceptions cannot be analyzed in numerical forms unless the study is changed or the ultimate purpose of the study becomes difficult to achieve.
Alternatively, the researcher would have used correlation studies instead of descriptive statistics to yield better results. This is because correlation studies are another statistical technique that conforms to the requirements of both quantitative and qualitative study. Apart from just analyzing the views, perceptions, ideas and opinions of individuals, correlation studies advances on the efficiency of descriptive statistics by comparing the same phenomenon across populations and contexts (Bryman, 2017). This would effectively portray the nature of the outcomes in relation to the participants’ contexts and also makes the process of decision-making based on the yielded outcomes easier compared to the use of descriptive statistics.
Second Study: Adolescent drug abuse - Awareness & prevention
The second study in this analysis was conducted by Chakravarthy, Shah & Lotfipour (2013) on the prevalence of drug abuse among adolescents and the extent to which awareness and prevention efforts have been made to reduce this prevalence. The study involves a combination of both descriptive and correlation statistics. Descriptive statistics explains the prevalence of drug abuse among youths and how youths are generally experiencing the phenomenon of drug abuse. Correlation studies are applied substantially to compare the prevalence of drug abuse among youths in relation to other groups of individuals in the contexts of the study. The findings are therefore completely descriptive and comparative in nature.
Although the strength of this study is in the fact that it regards adolescents in the context of the entire society which also constitutes other groups of individuals, it fails to offer exact statistics of the community in which the research was conducted, the numerical representation of data of the adolescents who are affected (or are at high risk of being affected) by this issue and the trend of drug abuse among adolescents overtime (including previous years). Further to justify the need of this trend, the outcomes obtained have been used to make a prediction of this situation in the near future. However, it would be more appropriate if this prediction was to be made based on a combination of information both at a time of research and information in the past. Therefore, the study would have involved a numerical representation of data in addition to the descriptive statistics used. Additionally, there was need to include statistics of the details from health care and other centers such as Drug Enforcement Administration (DEA) and National institute of Drug Abuse (NIDA) in US. These statistics could have sufficiently supplemented the achievement of the ultimate goal of this study.
Third Study: Religion and HPV vaccine-related awareness, knowledge, and receipt among insured women aged 18-26 in Utah
Another research by Bodson et al., 2017 was conducted with an aim of investigating associations that exist between religious practices and awareness about human papillomavirus (HPV) vaccine-related awareness, understanding, and receipt of knowledge among young women in Utah. This study was conducted as part of a larger survey conducted among women of ages n18 to 26 sampled from the University of Utah clinics by use of mail regarding their attitudes and it majorly entailed the use of vaccines together with HPV-related vaccination awareness and beliefs. Knowledge, attitude and receipt were also among the pertinent aspects that were given utmost attention. Therefore, this study used inferential statistics which uses a sample to represent and make conclusions based on the entire population from which the sample is obtained.
Inferential statistics was applicable to this study since the population size was too huge to be used as a whole for this study. However, inferential statistics was unable to yield all the necessary information that was ideal and necessary in the contexts of the study. First, the study was scientific and therefore required numerical description of data, which inferential statistics could not completely cover. Additionally, making conclusions based on such a sample for the purposes of making necessary adjustments and improvements in the area of health care is somewhat critical and requires a combination of approaches including but not limited to correlation studies, case studies and other types of quantitative and qualitative studies.
I can therefore, commend that this study served the primary purpose for which it was intended which entailed investigating how religious and other cultural standpoints influence decision-making on the issues of taking HPV vaccine among youths aged 18 to 26 years in Utah. However, I would recommend that the study involves both qualitative and quantitative approaches to data collection based on the grounds that it is a scientific study taking place in the contexts of the society and thus has to take into consideration the role of perceptions, wishes, ideas, opinions and points of view. Additional methods that would have been utilized to perfect on this study other than the survey method that was used include correlation and descriptive statistics. Correlation studies are used to convey information in a quantitative form whereas descriptive statistics are used to convey information or data that is qualitative in nature (Schabenberger & Gotway, 2017).
Conclusion
In summary, this analysis has presented a detailed review of various types of statistical methods and their applicability in varied contexts. In the initial section of this paper, there is a critical reflection on the lessons gained from this module. These lessons are diverse but the paper has described them in brief. Major lessons include the nature and applicability of descriptive and inferential statistics. The basic difference between the two is that descriptive statistics convey a detailed nature of a phenomenon without making actual conclusions, majorly because the data obtained is too diverse to be applied to a particular population. Inferential statistics differ from descriptive statistics in the sense that the later goes ahead to make judgments about a particular course of action and the findings of research concluded are regarded as the source of absolute truth. In the succeeding section of the paper, there is a brief review of three articles. The first article is a research paper in the area of health care in relation to the community. This study uses descriptive statistics which is appropriate statistical method but would have been supplemented by correlation studies to increase the scope of the study. The second study is obtained from the area of drug and substance abuse among youths. This study uses both correlation and descriptive statistics but is limited in the fact that it does not offer sufficient numerical information required for judgments and decision-making. The last study is obtained from the area of religion in relation to HPV vaccination and prevention. This is a scientific study that would have required a combination of both statistical and descriptive information.
References
Andermann, A. (2016). Taking action on the social determinants of health in clinical practice: a framework for health professionals. Canadian Medical Association Journal , 188 (17-18), E474-E483.
Bodson, J., Wilson, A., Warner, E. L., & Kepka, D. (2017). Religion and HPV vaccine-related awareness, knowledge, and receipt among insured women aged 18-26 in Utah. PloS one , 12 (8), e0183725.
Bryman, A. (2017). Quantitative and qualitative research: further reflections on their integration. In Mixing methods: Qualitative and quantitative research (pp. 57-78). Routledge.
Chakravarthy, B., Shah, S., & Lotfipour, S. (2013). Adolescent drug abuse-Awareness & prevention. The Indian journal of medical research , 137 (6), 1021.
Cox, D. R. (2018). Applied statistics-principles and examples . Routledge.
Mai, J. E. (2016). Looking for information: A survey of research on information seeking, needs, and behavior . Emerald Group Publishing.
Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health Services Research , 42 (5), 533-544.
Pyrczak, F. (2016). Making sense of statistics: A conceptual overview . Routledge.
Schabenberger, O., & Gotway, C. A. (2017). Statistical methods for spatial data analysis . CRC press.
Wild, C. J., Utts, J. M., & Horton, N. J. (2018). What is statistics?. In International Handbook of Research in Statistics Education (pp. 5-36). Springer, Cham.
