The role statistics have in our society
I think that statistics have an important role in our society because its used for so much. It is used to analyze, organize and summarize data and information. People often rely on statistics in business, economy, marketing, science and lots more. People analyze data from statistics and base their decisions from them. They use statistics to form their opinions on certain products, to determine whether they are trustworthy, the negative/positive impacts, and how it is if they get the product verses if they don’t get it. They basically form their opinions from the majority of other peoples opinions. People also use statistics to make future predictions that may help prepare.
New things I’ve learned after reading the article
At the end of the article I realized how much I don’t know about statistics and the things that people don’t think about. The reasoning for misleading statistics makes a lot of sense but its just that people don’t usually take that stuff into recognition and they don’t realize that the information that they are basing their opinions on could be very misleading and its very easy to misinterpret some stuff. I knew that statistics have an important role in our society and that people are constantly relying on it but I never knew that there were so many ways to scramble statistics to make them seem more impressive or shocking, to encourage you to choose a specific side and even to make you completely read the question or statement wrong.
Different types of problems with statistics
Faulty Statistics: A lot of statistics are just made up on the spot and the others are mathematically flawed. Statistics are use specific numbers and percentages and they have more authority then. That makes us less suspicious and it makes it sound more believable.
Bad Sampling: Sometimes when there are surveys, the group that answers happens to be a majority or one side and the chances are higher when the group is small. For example if you asked only 3 people a question there’s a good chance that they could all have a positive answer. So that 100% people answered yes but if you were to ask 100 people its unlikely they will all answer yes as well (depending on the question) so the percent is no longer 100% and often in statistics the group of who voted is not mentioned so you may get the wrong idea.
Unfair poll questions: This is simply when the question is asked in a way that encourages a specific answer. We know that there’s lots of ways to ask something with it meaning somewhat the same thing. Well, basically they can switch up the way the question is worded to make it seem like a negative thing when really it isn’t negative at all. This is how they will get the answer that they want and know they will receive.
Statistics that are true but misleading: Data is collected in many ways and when you collect it over a long period of time there are a lot of different ways to explain the results. For example if you were collecting data on the average hours of sleep a person gets every night every year; 2013: 9 hours, 2014: 9 hours, 2015: 8 hours, 2016: 9 hours, 2017: 7 hours. So you could say “On average a person sleeps 9 hours in 2013 and it has gone up to 7 hours in 2017.” But you could also say “In 2013 the average hours a person slept was 9 hours and in 2016 in remained the same.”
Ranking Statistics: Ranking is a problem is statistics because you can’t always tell how something is being categorized. It is based on comparisons rather than quantities. You could say “a Himalayan cat is the biggest cat breed” but if tigers, and pumas, and other felines counted in the category than the Himalayan would probably not be the biggest when they are in that category. People usually use ranking to make a statement sound more impressive.
Qualifiers on Statistics: Again this can make a statement sound more impressive than it really is. People basically take something and state that it is – for example – the fastest moving by narrowing down the category. I could say “the snow goose is the fastest herbivore bird in the entire world” but it really isn’t that fast with the qualifiers like herbivore and bird. If I removed those qualifiers and said the snow goose is the fasted in the entire world, it sounds a lot more impressive but it is definitely no longer true.
Percentages: Percentages can make a statement sound a lot more or a lot less. For example if you are asking a question to 1,000,000 people and 20,000 said yes you might to say 20,000 said yes to whatever the questions because it sounds more impressive than 20%. But sometimes with a small group and you only ask 10 people and 2 people say yes, you probably don’t want to say that 2 people said yes and you’ll choose to say 20% people said yes.