NCU Evaluating News Articles Paper

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For this task, you will read three news articles intended for a general audience reporting the results from correlational studies. You can find the links to these articles under your weekly resources. For each of the articles, you will answer the following questions and provide justifications for your answers:

Provide a brief summary of the topic of the article.

Determine which variables are the focus of the research.

Describe how the results of the correlational analyses are presented.

Does the author of the article present the results as causal? In other words, does the author make statements that one variable causes the other?

Can you think of any additional variables that were not included in this study that may be important to consider?  Please describe the variables.

Based on what you know about correlational research, does it make sense to make lifestyle changes based on the research presented in this article? Please explain your answer.

Use one of the news articles to locate, and then read the primary source article in the NCU library. Did the news article accurately represent the research conducted? Please explain your answer.

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Everyday Health Healthy Living Personal Takes Standing vs. Sitting: Why Movement Boosts Our Health By Dr T. Jared Bunch, MD At a series of physician lectures on our modern work environments, I learned why all the physicians who presented there had thrown away their office chairs and replaced them with working treadmills: • Continuous body motion, including fidgeting, is a healthy use of daily calories and keeps our weight in check. • Our modern workplace environments that promote desk jobs and prolonged sitting are harmful to our health. Relapsed/Refractory MCL Info - Official Physician Site www.mcl-btk-inhibitor.com Learn More About Resources For A Treatment Option For R/R Mantle Cell Lymphoma. The question I want to pose to you is this: Are our modern workplaces, and the advances that make them possible, directly responsible for our worsening societal health? This question was the focus of a July 2015 study published in the European Heart Journal, conducted by researchers at the University of Queensland in Brisbane, Australia. Francisco Lopez-Jimenez, MD, also addressed the issue in an excellent editorial about the same study, Standing for Healthier Lives – Literally. Standing during work as a health benefit is not a new concept, Dr. Lopez-Jimenez points out. In a 1953 study from London published in the British Medical Journal, bus conductors who often stood during their work shifts had less coronary artery disease and lower total mortality than bus drivers who spent their days seated. ADVERTISING But in our society, jobs in which we are seated are often viewed as more advanced than jobs that require prolonged standing. Ask yourself a few simple questions: • If you see two employees traveling to work — one on a regular bicycle and the other in a luxury automobile — who likely has the higher position in the company? • Consider a second scenario: If one of your neighbors hires a maid and a lawn service, and the other spends a lot of time on the yard and doing household chores, who probably has a higher economic status? The Bigger the Chair, the Better — Not Healthier — the Job Perception is important in our society. Leaders of large corporations often have very large offices with vast comfortable seating. They also spend extensively to make large open lobbies with big couches and chairs. “In every country, the bigger and more comfortable the chair, the more important the job. Interestingly, in the English language, chair also means chief or director, making a piece of furniture a synonym of power and rank,” writes Lopez-Jimenez. Clearly, societies have placed value on sitting. But unfortunately, we live with the health consequences of this misdirected value. In most advanced societies, diabetes, sleep apnea, obesity, heart disease, and stroke are becoming epidemics. Obesity also results in higher rates of many cancers, including breast, uterine, pancreatic, and colon cancers. Even in less developed countries, the wealthier people tend to suffer from higher rates of these diseases: Their status has afforded them more opportunities to sit and, consequently, become less active. Standing Vs. Sitting Cuts Heart Disease Risks In the interesting new study from Australia, researchers recognized that excessive sitting time is associated with worse health. They asked if replacing sitting with standing was sufficient, or if additional activity and motion was still required or would provide additional benefits. Six hundred and nighty-eight people were enrolled in this study — 57 percent of them women. The average age was approximately 58. Most of us often overestimate our activity and exercise times and underestimate our sedentary times. When I ask some of my older male patients about their activity, their wives will often start laughing at the answers. But these researchers did not rely on self-reported times of activity: They used posture and activity monitors to accurately measure standing and activity times. When people replaced two hours of sitting a day with standing, they had changes in these important heart disease risk factors: • 2 percent lower blood glucose ( blood sugar) • 11 percent reduction in triglycerides • 6 percent lower total cholesterol • Higher levels of HDL cholesterol (good cholesterol), by 0.06 millimoles per liter (mmol/L) This suggests that just by increasing how much you stand during the day, you can greatly impact risk factors for heart disease. The authors then looked at what happens when you replace two hours of sitting with stepping. For those who have an office job, this means using a small stair stepper or workplace treadmill. The rate they chose was three METs (METS are metabolic equivalents, and the energy it takes to just sit is one MET). Three METs is a walking rate of about 2.5 to 3 miles per hour. Results associated with this simple lifestyle change from sitting to stepping were profound: • 11 percent lower blood sugar • 11 percent lower body mass index (BMI) • 7.5 cm smaller waist circumference • 14 percent lower triglycerides • Even higher levels of good (HDL) cholesterol, by 0.10 mmol/L. These findings don’t reflect the other many positive benefits with increasing your time standing and stepping: Lower stress and anxiety, better sleep, lower risk of muscle and bone loss, improved posture, improved breathing mechanics, and more. I agree completely with Lopez-Jimenez that we need to “Stand for Healthier Lives.” We also need to recognize that our societal value of sitting is misplaced and has caused public harm. Many of my colleagues, like other researchers in this area, have given up their office chairs. Some now do their computer work and charting on a walking treadmill. Australia now has an active public health campaign to reduce sitting times. These healthy choices will have far-reaching, positive consequences. I applaud companies and organizations that have already started to promote the use of standing desks and walking treadmill desks. The great news from the Australian study is that many of the negative effects of prolonged sitting can be reversed. So start now! Stand up! PHOTO CREDIT: Ezra Bailey/Getty Images T. Jared Bunch, MD is a native of Logan, Utah, and directs heart rhythm research at the Intermountain Medical Center Heart Institute. You can follow @TJaredBunch on Twitter. Dr. Bunch is also a frequent guest on The Dr. John Day Show, available on iTunes. Last Updated:8/7/2015 Important: The views and opinions expressed in this article are those of the author and not Everyday Health. See More In This Series The Heart Health Benefits of Going South for the Winter Can You Overcome Your Genetic Risk of Heart Disease? Ads by Revcontent You May Like Diabetic? Do This Immediately to Keep Blood Sugar Normal Medical Journal News Early Signs of Lung Cancer Lung Cancer | Sponsored Links Chinese Secret for Keeping Blood Sugar in Control Revealed (Watch) Medical Journal News Fast & Cheap Online Degrees for Seniors Education | Sponsored Links Sign Up for Our Healthy Living Newsletter Submit We respect your privacy. The Latest in Healthy Living Healthy Living 6 Ways to Gauge Whether Your Doctor’s Office Is Trans-Friendly Healthy Living 12 Meaningful Father’s Day Quotes to Share With Dad Healthy Living 6 Unusual Signs of Dehydration You Should Know About Healthy Living A Consumer’s Guide to Drug Discounts Healthy Living ENDO 2019: The Top Health News Headlines From March 25 Healthy Living Is Facebook Tracking Your Health Without Your Knowledge? Healthy Living Facing Common Health Threats Among African-Americans Healthy Living 5 Things Drinking Too Much Alcohol May Be Doing to Your Body Healthy Living Patients and Providers Turn to Voice Technology in Healthcare Healthy Living No Need to Go Naked: New Medical Garment Provides COVR for Patients Healthy Living How Castle Connolly Connects Consumers and ‘Top Doctors’ Healthy Living Why Marie Kondo’s Decluttering Method Is So Life-Changing, According to Experts Healthy Living Report Ranks Healthiest and Least Healthy Places to Live Healthy Living 9 Ways to Feng Shui Your Space in 2019 Healthy Living The CDC Reports a Drop in U.S. Life Expectancy Healthy Living Black Friday Deals to Help You Live Your Best Life in 2018 Healthy Living New Guidelines: Screen All Adults for Unhealthy Alcohol Use Healthy Living Should You Really Go on a Wellness Retreat? Healthy Living Mayo Clinic Stars in New Ken Burns Documentary Healthy Living Best Health & Fitness Deals (Including Labor Day Savings of Up to 50% at Eastern Mountain Sports and GNC) Wellness inspired. Wellness enabled. Select Page Causation vs Correlation by Rebecca Goldin | Aug 19, 2015 | Causality, Correlation is not causation, Savvy stats reporting | 23 comments J ournalists are constantly being reminded that “correlation doesn’t imply causation;” yet, conflating the two remains one of the most common errors in news reporting on scientific and health-related studies. In theory, these are easy to distinguish—an action or occurrence can cause another (such as smoking causes lung cancer), or it can correlate with another (such as smoking is correlated with high alcohol consumption). If one action causes another, then they are most certainly correlated. But just because two things occur together does not mean that one caused the other, even if it seems to make sense. Unfortunately, intuition can lead us astray when it comes to distinguishing between the two. For example, eating breakfast has long been correlated with success in school for elementary school children. It would be easy to conclude that eating breakfast causes students to be better learners. Is this a causal relationship—does breakfast by itself create better students? Or is it only a correlation: perhaps not having breakfast correlates highly with other challenges in kids’ lives that make them poorer students, such as less educated parents, worse socio-economic status, less focus on school at home, and lower expectations. It turns out that kids who don’t eat breakfast are also more likely to be absent or tardy—and absenteeism plays a significant role in their poor performance. This may lead one to believe that there is not a causal relationship. Yet breakfast may encourage kids to come to school (and on-time), which then improves their performance in school, and so perhaps encourages attendance, which then results in better performance. In a recent literature review, there were mixed results suggesting that the advantages of breakfast depend on the population, the type of breakfast provided, and the measurement of “benefit” for the kids. Breakfast seems to have an overall positive impact on cognitive performance, especially memory tasks and focus. Not surprisingly, the benefit seems greater for kids who are undernourished. But the clear message here is that a causal relationship has been extremely hard to establish, and remains in question. Many studies are designed to test a correlation, but cannot possibly lead us to a causal conclusion; and yet, obvious “reasons” for the correlation abound, tempting us toward a potentially incorrect conclusion. People learn of a study showing that “girls who watch soap operas are more likely to have eating disorders”— a correlation between soap opera watching and eating disorders—but then they incorrectly conclude that watching soap operas gives girls eating disorders. It is entirely possible that girls who are prone to eating disorders are also attracted to soap operas. There are several reasons why common sense conclusions about cause and effect might be wrong. Correlated occurrences may be due to a common cause. For example, the fact that red hair is correlated with blue eyes stems from a common genetic specification that codes for both. A correlation may also be observed when there is causality behind it—for example, it is well established that cigarette smoking not only correlates with lung cancer but actually causes it. But in order to establish cause, we have to rule out the possibility that smokers are more likely to live in urban areas, where there is more pollution—and any other possible explanation for the observed correlation. In many cases, it seems obvious that one action causes another; however, there are also many cases when it is not so clear (except perhaps to the already-convinced observer). In the case of soap-opera watching anorexics, we can neither exclude nor embrace the hypothesis that the television is a cause of the problem—additional research would be needed to make a convincing argument for causality. Another hypothesis might be that girls inclined to suffer poor body image are drawn to soap operas on television because it satisfies some need related to their poor body image. Or it could be that neither causes the other, but rather there is a common trait—say, an overemphasis on appearance in the girls’ environment—that causes both an interest in soap operas and an inclination to develop eating disorders. None of these hypotheses are tested in a study that simply asks who is watching soaps and who is developing eating disorders, and finding a correlation between the two. How, then, does one ever establish causality? This is one of the most daunting challenges of public health professionals and pharmaceutical companies. The most effective way of doing this is through a controlled study. In a controlled study, two groups of people who are comparable in almost every way are given two different sets of experiences (such one group watching soap operas and the other game shows), and the outcome is compared. If the two groups have substantially different outcomes, then the different experiences may have caused the different outcome. There are obvious ethical limits to controlled studies: it would be problematic to take two comparable groups and make one smoke while denying cigarettes to the other in order to see if cigarette smoking really causes lung cancer. This is why epidemiological (or observational) studies are so important. These are studies in which large groups of people are followed over time, and their behavior and outcome is also observed. In these studies, it is extremely difficult (though sometimes still possible) to tease out cause and effect, versus a mere correlation. Typically, one can only establish a causal relationship if the effects are extremely notable and there is no reasonable explanation that challenges causality. This was the case with cigarette smoking, for example. At the time that scientists, industry trade groups, activists and individuals were debating whether the observed correlation between heavy cigarette smoking and lung cancer was causal or not, many other hypotheses were considered (such as sleep deprivation or excessive drinking) and each one dismissed as insufficiently describing the data. It is now a widespread belief among scientists and health professionals that smoking does indeed cause lung cancer. When the stakes are high, people are much more likely to jump to causal conclusions. This seems to be doubly true when it comes to public suspicion about chemicals and environmental pollution. There has been a lot of publicity over the purported relationship between autism and vaccinations, for example. As vaccination rates went up across the United States, so did autism. And if you splice the data in just the right way, it looks like some kids with autism have had more vaccinations. However, this correlation (which has led many to conclude that vaccination causes autism) has been widely dismissed by public health experts. The rise in autism rates is likely to do with increased awareness and diagnosis, or one of many other possible factors that have changed over the past 50 years. Language further contorts the distinction, as some media outlets use words that imply causality without saying it. A recent example in Oklahoma occurred when its Governor, Mary Fallin, saidthere was a “direct correlation” between a recent increase in earthquakes and wastewater disposal wells. She would have liked to say that the wells caused the earthquakes, but the research only shows a correlation. Rather than misspeak, she embellished “correlation” with “direct” so that it sounds causal. At times, a correlation does not have a clear explanation, and at other times we fill in the explanation. A recent news story reports that housing prices in D.C. correlate with reading proficiency. Many stories can be crafted to explain the phenomenon, but most people would be reluctant to conclude that a child’s reading proficiency could cause the price of their house to be higher or lower, or vice-versa. In contrast, a news story reporting that “30 years of research found a positive correlation between family involvement and a student’s academic success” in Florida feels like it has the weight of causality. The big difference between these two different correlations is our own belief in a likely mechanism for family to contribute to better grades. In general, we should all be wary of our own bias: we like explanations. The media often concludes a causal relationship among correlated observances when causality was not even considered by the study itself. Without clear reasons to accept causality, we should only accept the existence of a correlation. Two events occurring in close proximity does not imply that one caused the other, even if it seems to makes perfect sense. Rebecca Goldin is Professor of Mathematical Sciences at George Mason University and Director of STATS.org. She received her undergraduate degree from Harvard University and her Ph.D. from the Massachusetts Institute of Technology. She taught at the University of Maryland as a National Science Foundation postdoctoral fellow before joining George Mason in 2001. Her academic research is in symplectic geometry, group actions and related combinatorics. In 2007, she received the Ruth I. Michler Memorial Prize, presented by the Association for Women in Mathematics. Goldin is supported in part by NSF grant #1201458. 23 Comments 1. Margaret Gorlin on September 3, 2015 at 1:20 pm I discovered your stat stories this morning while poking around the internet looking for good examples of bad statistics. I am still reading your stories with relish an hour after starting – they are interesting, fun, thought provoking and at a level I can use in my intro stat classes this fall. Thank you for these gems – I am planning to put them to good use this term. Reply • statsorg on September 5, 2015 at 8:34 am Thank you Margaret: We have big expansion plans in the next year! Reply • vijay on December 19, 2017 at 4:05 pm Great!!!!! Very informative and the style of presentation was extremely beautiful Reply 2. Zachary on October 8, 2015 at 4:31 pm I’m a high school student in a college level Stats course and reading this has been so interesting. I’m starting to think about a career in Stats Reply • statsorg on October 9, 2015 at 6:48 pm Good for you Zachary! The world needs more statisticians! And it’s willing to pay too! Reply • David on March 24, 2016 at 1:41 am See what you’ve caused!? Reply 3. Lexi on January 4, 2016 at 10:12 am This was a great source of information. I’m currently writing an essay for extra credit and this is the first clear explanation I have found that truly approaches the topic the way I need. Thank you so much. Reply 4. Mark on January 30, 2016 at 4:19 pm Dr. Goldin, great piece. Is there a point where the size, scope or length of time scale of the data begins to demonstrate such an overwhelming correlation that cause and effect is much more certain? I’m thinking about this in the context of business, where most of the decisions we make each day are based on correlation v. absolute certainty re cause and effect. It seems logical, for example, that correlations in larger bodies of data over longer periods of time would be inherently more reliable and potential more indicative of cause and effect than two quarters of data. Your thoughts would be greatly appreciated. Thanks! Reply 5. Yawning Enthusiast on February 24, 2016 at 1:35 pm Most readers won’t know the difference between causation and correlation. In fact, many reporters who use those two words don’t fully understand either. However, what would be the proper way to explain that not all smokers suffer from lung cancer? Reply • Uzoma on December 17, 2017 at 6:50 am By doing a controlled experiment Reply • Uzoma on December 17, 2017 at 7:01 am x causes y if the lagged values of x improve the predectibilty of the current value of y Reply 6. Shanice F-J on May 2, 2016 at 11:20 am Thank you for your help, the clearest example I’ve seen! I’m currently working on my dissertation and this really helped! Thanks Reply 7. Shanice F-J on May 2, 2016 at 11:20 am Thank you for your help, the clearest example I’ve seen! I’m currently working on my dissertation and this really helped! Thanks Reply 8. ah ha on July 25, 2016 at 5:37 pm go westfield, urban ed!!! Reply 9. ah ha on July 25, 2016 at 5:37 pm go westfield, urban ed!!! Reply 10. morfara on November 4, 2016 at 8:12 pm “If one action causes another, then they are most certainly correlated. “. Could you please elaborate a bit more on that, i.e. can one action cause another, and not be correlated? Reply 11. Bastard Beard Co on May 13, 2017 at 7:11 am Right away I am ready to do my breakfast, when having my breakfast coming over again to read more news. Reply 12. Lisa de Bie on September 19, 2017 at 1:46 pm Great! Reply 13. Lisa de Bie on September 20, 2017 at 4:02 pm Good! Reply 14. Tyler on February 13, 2018 at 3:59 am Very insightful. Your article will change the way I discuss Causation vs Correlation. Thank you! Reply 15. 車売る on March 25, 2018 at 10:45 pm Thanks for finally talking about >Causation vs Correlation
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Running head: EVALUATING NEWS ARTICLES

Evaluating News Articles
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EVALUATING NEWS ARTICLES

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Evaluating News Articles
Article 1: Causation versus Correlation by Rebecca Goldin
The article discussed causation and correlation where journalist tends to contradict the
issue on the fact that correlation does not imply causation. The association between the two has
been the most common mistake in the news. The author argues that if one action is the cause of
another, then the two are correlated. However, if two things occur together, then it does not
mean that one act caused the other. The writer provides an example of a causal relationship by
giving the instance where eating breakfast causes children to perform better in elementary
school. Besides, kids who do not take breakfast are likely to skip school, which leads to their
poor performance. The author also claims that there are points where common sense conclusion
regarding cause and effect might be wrong. She provides the example of the fact that red hair is
correlated with blue eyes. Moreover, the author claims that some correlations appear when there
is an instance of causality behind the whole thing. For example, cigarette correlates with cancer
and also causes it to smokers. Therefore, for people to determine causality, they have to conduct
a controlled study. By doing so, it becomes easier to explain correlation and causation in various
scenarios.
In the study, the variable in focus is correlation and causation. The author has used
various examples to explain the relationship between the two words. The writer has used the case
of g...


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