As a whole, statistics can be divided into two main categories. They are descriptive and inferential. They are different, but both are important in the field of the Social Sciences. Both descriptive and inferential statistics can help Social Scientists get a snapshot of either a certain population or sample of a population. The crux of the differences between descriptive and inferential statistics are how they are defined, how they are applied by Social Scientists and the amount of care a Social Scientist must take in using them.
Descriptive statistics has been defined by C. Urdan (2010) as “statistics used to describe the characteristics of a distribution of scores" (p. 10). An addition to that definition is the fact that descriptive statistics “summarize the data with the purpose of describing what occurred in the sample” (Allua & Thompson, 2009). Descriptive statistics is literally just the numbers for that population or sample. One example of this is saying “suicide is a big factor [in premature deaths of people with mental illnesses], accounting for 30 to 40 percent of early deaths. But 60 percent die of preventable or treatable conditions” (Garey, 2013). As you can see, descriptive statistics draw no conclusions about the data collected, it is just the what is collected.
Inferential statistics are “statistics, derived from sample data, that are used to make inferences about the population from which the sample was drawn” (Urdan, 2010, p. 11). Inferential statistics “refer to the use of sample data to reach some conclusions (i.e. makes some inferences) about the characteristics of the larger population that the sample is supposed to represent" (Urdan, 2010, p. 2). An example of an inferential statistic would be saying "9...
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... Scientists and the amount of care a Social Scientist needs to take in order to properly utilize them. It is important to know the distinctions between descriptive and inferential statistics because without knowing the differences, a Social Scientist could run the risk of improper use of their collected data. Proper use of data is key to being a worthwhile Social Scientist and helps to advance the field of Social science.
Works Cited
Allua, S., & Thompson, C. B. (2009). Inferential Statistics. Air Medical Journal, 28(4), 168-171. doi: 10.1016/j.amj.2009.04.013
C. Urdan. (2010). Statistics in Plain English. New York, NY: Taylor & Francis Group.
Garey, J. (2013, August 10). When Doctors Discriminate. The New York Times.
May, C., & Post, J. (2013). Psychiatrists Have Obligation to Counter Stigmatizing Remarks. Psychiatric News. doi: 10.1176/appi.pn.2013.3b27
...us advances in this field, while we still consider it a stigma even to be referred to a psychiatrist. Mental illness is just another biological or sociological problem, which needs to be dealt with on time, before it’s too late, by a specialist.
Davey, Graham. "Mental Health & Stigma." . Psychology Today, 20 Aug. 2013. Web. 20 Apr.
This stereotype contributes to the stigma individuals’ face and encourages social exclusion and intolerance, especially in schizophrenia (Ray & Brooks Dollar, 2014). Ken sought out help and went to the emergency room because he recognized he was severely depressed. There, the doctor promised he would not be put in restraints, yet when he was taken to the hospital, he was placed in restraints because it was company policy (Steele & Berman, 2001). Due the stigma that individuals with mental illness are violent, Ken was not treated fairly (Stuart & Arboleda-Florez, 2012). Stuart and Arboleda-Florez (2012) are very credible authors to be writing on the effects of stigma in mental health. Both authors have experience in psychiatry, combatting stigma and mental health issues.
Clients experienced stigma in regards to three factors including discrimination, stigma related to disclosure of their mental illness, and rejection of any positive aspects regarding their mental illness. When clients experienced any type of stigma mentioned above, this caused a regression in their treatment. This study found that 89.7% of the participants in the study experienced discrimination for their diagnosis, and 88.4% felt uncomfortable when disclosing their diagnosis (2015). This article supports Rosenhan’s findings that suggest the inpatient staff members’ attitudes and preconceived notions about the psuedopatients and patients created an environment that cultivated depersonalization. Treating those with a diagnosis as “insane” and avoiding contact (or abusing the patients in much more severe circumstances) caused clients to experience stigma and therefore regress in their treatment (1973), much like the participants in the study conducted in San
The final chapter of this book encourages people to be critical when taking in statistics. Someone taking a critical approach to statistics tries assessing statistics by asking questions and researching the origins of a statistic when that information is not provided. The book ends by encouraging readers to know the limitations of statistics and understand how statistics are
Throughout her presentation, she explains how public stigmas, once again, cause label avoidance pushing many who need help away from treatment. She then goes on to explain how these stereotyped behaviors cause discrimination towards people with a mental illness from employment to housing which only leads to the creation of more stigmas. Finally, she states how the impact of stigmas is associated with the reduction of self-esteem, overall poor health, and problems with interpersonal relationships (Willits). By using this presentation I am able to connect what we have learned about mental health stigmas to my article. First off, for example, Morris explains how psychiatric units invoke people to imagine a frightening place where insane patients are strapped down and poked and prodded for care (Morris). This stereotypical idea relates to how Willits described general stereotypes associated with mental illness such as crazy and dangerous (Willits). On top of that, Willits explained how these stigmas have negative consequences for patients (Willits). This relates to Morris’s explanation on how the stigma around institutions has caused these units to shut down forcing many people to be homeless or live in jail
This essay will attempt to outline and explain the effects that stigma attached to mental health issues may have on one’s life and strategies for over coming self-stigma as well as public stigma. I will first explain stigma in the context of mental health and briefly explain the detriments this can have on a person’s life followed by a more in-depth analysis of the aforementioned stigmas. I will follow this up with strategies and models for disabling both public and self-stigma as a result of mental health.
Renaud, R. (2014a, April 10). Unit 10 - Understanding Statistical Inferences [PowerPoint slides]. Retrieved from the University of Manitoba EDUA-5800-D01 online course materials.
The two different types of stigma have different effects on the attitude towards those with mental health issues. The public stigma can lead to discrimination and prejudice. The prejudice and discrimination that result from the public stigma can prevent those diag...
Stereotypes and stigmas promote a dangerous, single-minded perspective. These incomplete or half-truths are often far more duplicitous than lies, as they are more difficult to detect. When these perspectives remain unchecked, they can result in far-reaching, adverse consequences. It is the individual’s duty to refuse to perpetuate this single story perspective. Due to misinformation presented by the media, the stigma surrounding mental illness has created a discriminatory single story perspective; however, through honest and open dialogue, particularly with those suffering from these diseases, these stereotypes can be abolished.
Quantitative methods in the social sciences are an effective tool for understanding patterns and variation in social data. They are the systematic, numeric collection and objective analysis of data that can be generalized to a larger population and seek to find cause in variance (Matthews and Ross 2010, p.141; Henn et al. 2009, p.134). These methods are often debated, but quantitative measurement is important to the social sciences because of the numeric evidence that can be used to drive more in depth qualitative research and to focus regional policy, to name a few (Johnston et al. 2014). Basic quantitative methods, such as descriptive and inferential statistics, are used regularly to identify and explain large social trends that can then
...atistics that was established plays on the emotion of the audience as they feel sympathy for the large amount of women that had died because of their first pregnancy. Furthermore statistics also increases the credibility of the article in two ways. Firstly, using statistics establishes that extensive research has been done making the audience believe that the stats provided are factual and reliable. Secondly, using statistics from reliable sources such as World Health Organization rises the credibility of the article. The article that I have chosen is credible because the author John Flynn used statistic from different sources as well as quotes from experts to back up his statement, and also most importantly statistics sticks with the audience even after reading the article. Hence statistics are one important factor that makes an article credible and reliable.
This chapter taught me the importance of understanding statistical data and how to evaluate it with common sense. Almost everyday we are subjected to statistical data in newspapers and on TV. My usual reaction was to accept those statistics as being valid. Which I think is a fair assessment for most people. However, reading this chapter opens my eyes to the fact that statistical data can be very misleading. It shows how data can be skewed to support a certain group’s agenda. Although most statistical data presented may not seem to affect us personally in our daily lives, it can however have an impact. For example, statistics can influence the way people vote on certain issues.
Researchers, professionals and others use statistics to prove their claims or findings. Even though statistics are not an absolute fact because the conclusion is mostly drawn from a sample group – representative of a specific population subjected to the research, it is commonly used as the basis of decision making or alternating choices in daily living, studies, works, scientific research, politics and other planning. The inventor of a documentary film called “An inconvenient truth”, Mr. Al Gore, for instance, in his campaign to educate people about the climate change, used statistics to alert people that everyone on earth is polluting the environment and should participate in solving the problem. He collected data from many different countries with an in...
The social sciences have and will continue to be in the future will play an important role in studying and solving problems for both society and its individuals. The disciplines that it encompass vary widely but often need to come together to solve issues and study certain facets of humanity. For my personal use social science is a tool to better understand others, be more sensitive to issues that people may face and to anticipate the way people and society may act in certain situations. A social science lens can be productive in that it helps people be more indiscriminate though understanding people and their behavior. I hope to use the socials sciences to impact other people’s lives in a positive manner. The social sciences to me when used in a well-intended manner are able to not only explain phenomena but also be a solution and or make a situation better. The intent of this essay is to better understand and define the social sciences, touch on the many disciplines of the science in addition to its relationships with other scientific areas.