Why is math important? How do statistics affect people\u2019s beliefs?<\/p>\n\n\n\n
Math is everywhere around you, even if you don\u2019t realize it. Numbers and statistics are essential for modern-day life to make predictions, solve simple problems, and answer complex science questions.<\/p>\n\n\n\n
Let\u2019s look at why math is important in everyday life.<\/p>\n\n\n\n\n\n\n\n
According to <\/strong>Naked Statistics<\/em><\/strong><\/a> by Charles Wheelan, statistics can offer insight into questions we couldn\u2019t possibly design an experiment to answer<\/strong>. For example, say we wanted to know whether exposure to a certain chemical (we\u2019ll call it chemical X) corresponds to higher rates of cancer. Ethics precludes purposefully exposing people to chemical X in a laboratory setting for the sake of science. Additionally, so many other variables impact a person\u2019s personal cancer risk that we can\u2019t possibly know if chemical X was the sole cause of anyone\u2019s cancer diagnosis. Without statistics, complex but important questions like this would remain unanswered.<\/p>\n\n\n\n To answer the question of whether chemical X is associated with higher rates of cancer, researchers could collect a large dataset including people who were and were not exposed to chemical X and record their rates of cancer diagnoses. Then the researchers could use regression analysis to determine the association between exposure to chemical X and a cancer diagnosis, independent of other factors such as smoking, exercise, family history, and so on. Statistics can even tell us what percent of a person\u2019s overall cancer risk is mathematically associated with exposure to chemical X rather than other factors.<\/p>\n\n\n\n As Wheelan explains, the ability to mathematically separate individual variables (like exposure to a particular chemical) in the complexity of the real world makes statistical analysis an invaluable part of medical and social sciences research.<\/p>\n\n\n\n When searching for the truth, statistics are appealing\u2014they seem like hard, believable numbers<\/strong>, and they\u2019re necessary for expressing certain information, such as census data. Many people take statistics at face value because they suspend their common sense<\/a> when presented with numbers, panic at the thought of complicated calculations, or feel math can\u2019t lie.<\/p>\n\n\n\n However, statistics aren\u2019t as objective as they seem.<\/strong> In How to Lie With Statistics<\/em><\/a>, author Darrell Huff explains how people who want to conceal the truth manipulate numbers<\/a> to come up with statistics that support their positions. These people\u2014advertisers, companies, anyone with an agenda\u2014often don\u2019t even have to actually lie<\/em>. Statistics is a flexible enough field that would-be liars can make their case with implications, omissions, and distraction, rather than outright falsehoods. <\/p>\n\n\n\n Not all bad statistics are manipulations or lies, of course.<\/strong> Some are produced by incompetent statisticians; others are accidentally misreported by media who don\u2019t understand the field. However, because most mistakes are usually in favor of whoever\u2019s citing the statistic, it\u2019s fair to assume that a lot of bad statistics are created on purpose.<\/strong><\/p>\n\n\n\n The manipulation of statistics just shows how much math is important, due to the power numbers hold over people. For example, say an advertiser wants to fib the truth about how many people have bought a specialty menu item at a restaurant. Maybe it hasn\u2019t sold enough to convince people it’s a customer-favorite. So the advertisement might say \u201cA million people have visited this restaurant, home of its world-famous cheeseburger.\u201d A million people might\u2019ve not eaten the burger, but that\u2019s how many people have eaten at the restaurant. The wording of the advertisement tricks people into thinking that if such a large number of people are eating there, the burger must be good.<\/p>\n\n\n\n Another reason math is important is that it encourages brain health<\/a> and sharpens your mind. Math and science involve a lot of problem-solving, so it takes brain power to do it. Just think about a simple task like baking. If you\u2019re cutting a recipe in half, you need to use math to determine the accurate measurements. Even a simple task like that boosts brain power.<\/p>\n\n\n\n In A Mind for Numbers<\/em><\/a>, Barbara Oakley discusses the two modes of thinking<\/a> that your brain uses to solve problems, and how to use them most effectively. Your brain naturally alternates between two modes of thinking: Focused and Diffuse<\/a>. <\/p>\n\n\n\n Focused-mode<\/strong> thinking occurs when your attention is focused on something, allowing you to process detailed information. However, it\u2019s susceptible to the \u201cEinstellung effect,\u201d which occurs when you are unable to solve a problem because the solution is outside the range of where you are looking for it. <\/p>\n\n\n\n Diffuse-mode <\/strong>thinking occurs when you relax your focus or let your mind wander<\/a>. It continues to process information from previous focused-mode thinking<\/a> subconsciously, but differently: It can circumvent the Einstellung effect<\/a> by allowing you to mentally step away from detailed problems and see the big picture<\/a>. It can also generate creative ideas and creative solutions to difficult problems, by connecting diverse concepts in your brain.<\/p>\n\n\n\n However, once you devise a creative solution with diffuse mode, you still have to switch to focused mode to carry out the solution, because diffuse-mode thinking doesn\u2019t process information in enough detail for full implementation.<\/p>\n\n\n\n Solving any difficult problem requires an exchange of information between your brain\u2019s focused-mode and diffuse-mode functions.<\/strong> Sometimes multiple cycles are required. So start by deliberately focusing on the problem and then deliberately divert your attention, allowing your brain to switch to diffuse mode. Repeat as needed, alternating between modes until you solve the problem. Here are a few things you can do to intentionally switch to diffuse-mode thinking:<\/p>\n\n\n\n Your hunter-gatherer brain isn\u2019t designed for complex math<\/strong>, says Rolf Dobelli in The Art of Thinking Clearly<\/em><\/a>. This means you can\u2019t instinctively grasp complex math concepts, but understanding these concepts is increasingly important for modern life.<\/p>\n\n\n\n To demonstrate why math is important in modern life, here are some situations in which struggling with math negatively impacts your decisions:<\/p>\n\n\n\n Averages are one of the complex math concepts that your brain isn’t evolutionarily prepared for, Dobelli explains. One of the biggest pitfalls when working with averages is ignoring the distribution: <\/strong>the original set of numbers used to calculate the average. Without knowing the distribution, averages are misleading because they don\u2019t show the outliers: the extremes at either end of the distribution that drastically change the average. To get a true average, these outliers must be removed, Dobelli says. This isn\u2019t instinctive, but it\u2019s important for modern life because outliers are increasingly common.<\/p>\n\n\n\n Statistics is another area of math that you\u2019re not evolutionarily primed for, Dobelli says. One statistical error is self-selection bias<\/a>, in which the nature of the participants in a study influences its outcome.<\/strong> Specifically, <\/strong>people only join studies they\u2019re comfortable with responding to, which alters your data, Dobelli says. Those who might provide embarrassing or somehow \u201cundesirable\u201d responses simply won\u2019t take part, narrowing your study\u2019s scope and skewing the results.<\/p>\n\n\n\n Philip E. Tetlock, the author of Superforecasting<\/em><\/a>, believes using math and numerical probability estimates in forecasts is critical. In the 1950s, the CIA<\/a> forecasting team discovered this after delivering a report forecasting the likelihood of the Soviet Union invading Yugoslavia. The report concluded that an attack was a \u201cserious possibility.” When a State Department official later asked the director of the forecasting team what they meant by \u201cserious possibility\u201d in terms of odds, he estimated the odds at 65 to 35, much higher than how the State Department had interpreted it. <\/p>\n\n\n\n This miscommunication was understandably alarming. The director of the forecasting team, Sherman Kent, took the problem back to his team and asked them each to put a number on \u201cserious possibility.” Though they had all collectively approved of the phrasing in the official report, every single team member assigned a different numerical value to those words. Kent was horrified: Not only were the forecasters not on the same page, but their forecasts were being used to inform foreign policy. If their reports were misunderstood, there could be global consequences. <\/p>\n\n\n\n That claim may sound dramatic, but it\u2019s exactly what happened in 1961 when President Kennedy commissioned the Joint Chiefs of Staff to report on his plan to invade Cuba. The final report predicted a \u201cfair chance\u201d of success, and the government went ahead with what became the Bay of Pigs disaster. After the fact, it was clarified that \u201cfair chance\u201d meant three-to-one odds against<\/em> success, but President Kennedy interpreted the phrase more positively and acted accordingly. <\/p>\n\n\n\n Another sector that relies on math and numbers is meteorology. It has embraced the clarity of numbers, and most of us are now accustomed to seeing weather forecasts in terms of percentages. Although miscommunicated numbers in weather don\u2019t seem as drastic as invading Cuba, it could still have dire consequences. People rely on percentages (read as \u201cchances\u201d) in forecasts to prepare for severe weather, such as tornadoes and hurricanes. Accurate forecasts can warn people to get to shelter before the storm arrives in their area, potentially saving lives.<\/p>\n\n\n\n Numbers don\u2019t just disappear when you finish math class. Math is a crucial life skill that\u2019s important for jobs and solving problems, no matter how big or small. Just imagine a life where you don\u2019t use math\u2014it\u2019d be nearly impossible to function because we wouldn\u2019t be able to tell time, cook, or travel.<\/p>\n\n\n\n What are other reasons why math is important? Let us know in the comments below!<\/em><\/p>\n","protected":false},"excerpt":{"rendered":" Why is math important? How do statistics affect people\u2019s beliefs? Math is everywhere around you, even if you don\u2019t realize it. Numbers and statistics are essential for modern-day life to make predictions, solve simple problems, and answer complex science questions. Let\u2019s look at why math is important in everyday life.<\/p>\n","protected":false},"author":14,"featured_media":121305,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[15,24,25],"tags":[452],"class_list":["post-121304","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-education","category-society","category-statistics","tag-guides","","tg-column-two"],"yoast_head":"\n2. Math Influences People\u2019s Beliefs<\/strong><\/h2>\n\n\n\n
3. Math Sharpens Your Brain<\/strong><\/h2>\n\n\n\n
4. Math Is Everywhere in Modern Life <\/strong><\/h2>\n\n\n\n
The Distribution of Averages<\/strong><\/h3>\n\n\n\n
Self-Selection Bias<\/strong><\/h3>\n\n\n\n
5. Math Helps Make Forecasts<\/strong><\/h2>\n\n\n\n
Wrapping Up<\/strong><\/h2>\n\n\n\n