READ AND FOLLOW DIRECTIONS ! THERE ARE TWO DIFFERENT PART OF QUESTIONS THAT NEED TO BE ANSWER! SUBJECT :

PART 1

Read the following Articles:

In Spring 2015 a researcher published the results of a study on the benefits of eating chocolate to help lose weight. This article spurred many news media reports on the benefits of chocolate, for example, http://www.dailymail.co.uk/femail/article-3018945/New-study-reveals-eating-chocolate-doesn-t-affect-Body-Mass-Index-help-LOSE-weight.html. in the Daily Mail. I personally saw a segment on The Today Show reporting the original article's findings.

In May, the author released news that his published student was not based on science but essentially "junk". His point is individuals including the media need to be skeptical of what they read and make sure the results are based on good science. Too often data can be manipulated in a way to prove a particular argument, especially in media coverage. http://www.npr.org/sections/thesalt/2015/05/28/410313446/why-a-journalist-scammed-the-media-into-spreading-bad-chocolate-science.

Question

What are your thoughts on these manipulations?

What can you do to help distinguish between statistical conclusions that are likely to be valid and those that are seriously flawed?

Would you have believed the original study?

THEN RESPOND TO A CLASSMATE POST: My thoughts on these manipulations is that it shouldn't be happening, and people, especially reporters of important information, should commit to the responsibility of providing truthful and reliable information. Although, this study teaches us, as an audience, needs to pay more attention to the sources of the information we're consuming. We have a responsibility to make sure we are getting the correct information. What I can do to help distinguish statistical conclusions to be valid or flawed is to look into the sources of these statistics and seeing if the conclusions align with other facts we know on the certain topic. I don't think I would have believed the original study because I tend to overthink and question things that are so far from what I grew up knowing. I don't think a conclusion like this would come about after years thinking otherwise.

PART 2

Read the following Articles:

What's the Difference Between Data Science and Statistics?.-Not long ago, the term "data science" meant nothing to most people-even to those who worked with data. A likely response to the term was: "Isn't that just statistics?" These days, data science is hot.The Harvard Business Review called data scientist the "Sexiest Job of the 21st Century..https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century" Another article titled "What is Data Science?" -https://datascience.berkeley.edu/about/what-is-data-science/.

Question

So what changed?

Why did data science become a distinct term?

What distinguishes data science from statistics?

THEN RESPOND TO A CLASSMATE'S POST: Data science emerged as a distinct term due to the exponential growth in data availability, advances in computational power, and the development of new technologies for data processing and analysis. Unlike traditional statistics, which focuses on collecting, analyzing, and interpreting data to make informed decisions, data science combines statistical methods with computer science, machine learning, and domain expertise to extract insights and build predictive models from large, complex datasets. The interdisciplinary nature and practical applications of data science in various industries have led to its recognition as a unique and valuable field, distinct from traditional statistics.