Please write 3 DQ response about 150-200 length after reading 3 peoples` posting with example and reference
Since most data collection is completed by humans, it stands to reason that there can be errors. The reason we use statistics is to prove a hypothesis based on data collection. There are many points in the data collection phase that can lead to a misrepresentation of the data, like asking questions that can be interpreted multiple ways, or using a sample that does not truly define a large group. This is why so much research has to be peer reviewed to be recognized as valid. What I find most frustrating is when companies or advertisement agencies use statistics to give validity to their product. So I’m going to touch on the sensitive subject of Planned Parenthood and abortions. According to Planned Parenthood only three percent of their services are abortions. “Out of the 10.6 million services, 327,653 of them were abortion procedures,” (Lee, Washington Post, 2015). What the problem was is that each service was listed separately, but many people received multiple services per visit. “A woman may get a pregnancy test, birth control and a pap smear, but she would be counted three times, once for each service, in the annual report,” (Lee, Washington Post, 2015). What the Planned Parenthood report does not show is how many visits were for an abortion, verses a well women’s exam. Many people have found this to be misleading.
DQ Response Your Name September 17, 2016 Your Institution of Affiliation Response to M.B`s post I totally agree with your article about the need for strong statistical data in data analysis and decision making. I know that all of us are aware of the fact that most people neglect the numbers presented to them and instead they follow their instincts. Yes, subjective (and instinctive) thinking and decision making works most of the time in our daily lives. But, I believed that this method of using trial and error in order to learn should be discouraged in a field where human lives are at stake. The field of healthcare should mostly be based in objective, logical, fact-based, and scientific decision making to prevent, if not mitigate, the possibility of something going w