Updated: Jan. 10, 2019
1. Click on a county in the United States, or input a county in the box below the map, to see the relative probability that someone in any county has a Facebook friendship link to another county in America. Note that when the cursor hovers over a county, the likelihood of a Facebook friendship link with all counties is shown by color.
After looking closely at the map above, think about these three questions:
• What do you notice?• What do you wonder?What are you curious about that comes from what you notice in the graph?• What might be going on in this graph?Write a catchy headline that captures the graph’s main idea. If your headline makes a claim, tell us what you noticed that supports your claim.
The questions are intended to build on one another, so try to answer them in order. Start with “I notice,” then “I wonder,” and end with “The story this graph is telling is ….” and a catchy headline.
2. Next, join the conversation by clicking on the comment button and posting in the box that opens on the right. (Students 13 and older are invited to comment, although teachers of younger students are welcome to post what their students have to say.) On Wednesday, Jan. 9, our collaborator, the American Statistical Association, will facilitate a live moderated discussion from 9 a.m. to 2 p.m. Eastern time to help students’ understanding go deeper. You might use their responses as models for your own.
3. After you have posted, read what others have said, then respond to someone else by posting a comment. Use the “Reply” button or the @ symbol to address that student directly.
4. On Thursday, Jan. 10, we will provide additional background about relevant statistical concepts and about this map, which originally appeared elsewhere on nytimes.com. Students, we encourage you to post an additional comment after reading the reveal. How does the original New York Times article and the moderators’ comments help you see the graph differently? Try to incorporate the statistical terms defined in the Stat Nuggets in your response.
• Read our introductory post, which includes information about using the “Notice and Wonder” teaching strategy.• Learn about how and why other teachers are using this feature, and use the 2018-19 “What’s Going On in This Graph?” calendar to plan ahead for the 25 Wednesday releases. • Go to the A.S.A. K-12 website, which includes This is Statistics, resources, professional development, student competitions, curriculum, courses and careers.
Updated: Jan. 10, 2019
Did you know that the typical American lives within 18 miles from his or her mother? And the typical college student goes to school within 15 miles of home? Is that what you expected? Our friends are close; they are who we see at home, school, and work. The New York Times article “How Connected Is Your Community to Everywhere Else in America?” lets you see the friendship links between people in your county and the rest of the country. Notice under the county fill-in space the share of friends who live within 50, 100 and 500 miles of your county. Calculate what percentage are beyond 500 miles. Is this what you expected? What do you wonder about your county’s friends network?
The article draws from a research study by statisticians from Facebook, Harvard, Princeton and New York University. Using anonymous Facebook data from 239 million active users (73% of U. S. population), they created an index of social connectedness. Adjusting for differences in county population size, the “likelihood of friendship” is displayed on the New York Times interactive map. Darker colors represent greater connectedness as compared to the white color of minimal connectivity. Notice that the legend does not use equal intervals; it jumps from 1 times as likely (neither more or less) that any two people living in two different counties are connected on Facebook to 3 times, then 10 and 100 times. The more colored in is the map the more broad is the county’s connections. Counties with less color in the map are more isolated.
The statisticians found that social connectivity declines with distance. On average, 55% of all Facebook friendships are with individuals living within 50 miles. Check several counties and examine their “Share of friends who live within …” statistics given below the map. How could this affect people’s happiness, financial well-being and futures? Which counties have the most, and which the least, social connectivity? Do you think social connectivity is increasing or decreasing? Thinking of our own friendship links, how does your social connectivity affect you?
Here are some of the student headlines that really capture the meaning of this map: “Facebook Friend-zy Around the Country” by Greg of Hopkinton, N.H., “The Map of Far Away Friends” by Ivette of Calif., and the quintuple alliteration “Possible Popular People Places Probability” by an anonymous student.
You may want to think critically about these additional questions:
■ True or false? Give support from the map and its statistics for your answers. — Americans from counties with similar incomes, education levels or voting patterns are more likely to be connected. — Americans are more likely to be friends with people who they share beliefs than people who live near them.
■ The article discusses how there are several powerful boundaries to social connectedness. For each of these, find an example and explain how the boundary affects the friendship connectivity. — State lines — History, such as the Dust Bowl and the Great Migration — Natural boundaries, such as rivers and mountain ranges — Destinations, such as military facilities, universities and retirement communities
■ Some say that this country is divided by politics, by urban vs. rural, and by the coasts vs. the heartland. But maybe distance is the major divider with people being friends with those who they live nearby. Running the cursor over the map, find a county whose residents have friends relatively close in distance and another county whose residents have friends who are very dispersed. What do you think caused this difference?
■ Input the county you live in and note the percentages of friendships that are within 50, 100 and 500 miles. How does this compare to the national percentages of 55%, 63% and 70%, respectively? Why do you think your community is more or less connected than the nation as a whole? How do you think this difference affects you and your community?
Below in the Stat Nuggets, we define and explain mathematical terms that apply to this map. Look into the archives to see past Stat Nuggets.
Thank you for participating in “What’s Going On in This Graph?”, which encourages thinking more critically about graphs and the underlying data. Critical thinking is an essential element of statistics, the science of learning from data. Data visualizations, like this map, are an important part of statistics. They help us to understand and learn from data.
Keep noticing and wondering. We continue to welcome your responses.
Join us Wednesday, Jan. 16, to notice and wonder about college loans. The interactive graph will be released on Thursday, Jan. 10. We look forward to your responses between 9 a.m. - 2 p.m. Eastern time during the live online moderation.
Stat Nuggets for “How Connected Is Your Community to Everywhere Else in America?”
MAP AS A GRAPH
A map can be a graph when the map shows data or statistics with their geographic relationship.
In the social connectivity map, the relative probability that someone in any U.S. county has a Facebook friendship with someone in the selected county is the statistic shown on the map. The color of the county indicates the level of connectivity with darker colors representing greater connectivity.
Statistics are numerical summaries of data.
In the social connectivity map, the data are anonymous Facebook friendship links between pairs of users from April 2016, grouped together at the county level. There are two statistics: the Social Connectedness Index, a measure of the number of links for each county pair, and the Likelihood of Friendship, the relative probability of friendship which adjusts the index for the population size of the counties so that the likelihood is per person and not the total number of connections.
Two quantitative variables are associated if they tend to vary together in a predictable way. (The term correlated is reserved for associations that are linear.) Even if two variables have a strong association, this alone is not enough to conclude that changes in one variable cause changes in the other variable. Other variables may cause this association.
In the social connectivity map, a county’s social connectivity may be associated with distance, mobility, income, health and more, but we cannot say that the social connectivity causes these outcomes.
The graphs for “What’s Going On in This Graph?” are selected in partnership with Sharon Hessney. Ms. Hessney wrote the “reveal” and Stat Nuggets with Roxy Peck, a professor emerita at California Polytechnic State University San Luis Obispo, and moderated online with Heather Johnson, an associate professor of math education at the University of Colorado Denver.B:
100期跑狗归图“【睡】【得】【这】【么】【死】【吗】？“【房】【间】【里】【安】【静】【得】【掉】【根】【针】【都】【能】【听】【得】【见】，【陈】【一】【成】【蹑】【手】【蹑】【脚】【的】【走】【向】【张】【泽】【希】【的】【床】。 【床】【上】【空】【空】【的】，【只】【有】【两】【个】【整】【整】【齐】【齐】【摆】【放】【着】【的】【枕】【头】，【陈】【一】【成】【疑】【惑】【的】【皱】【了】【皱】【眉】，【他】… 【去】【哪】【儿】【了】？ “【叮】【咚】。“【微】【信】【的】【消】【息】【声】【传】【了】【过】【来】。 【陈】【一】【成】【打】【开】【手】【机】，【是】【爸】【爸】【发】【来】【的】【消】【息】，【一】【张】【照】【片】，【爸】【爸】，【妈】【妈】，【张】【叔】，【还】【有】…
【唐】【西】【宿】【与】【白】【伶】【官】【思】【索】【至】【此】，【皆】【是】【神】【色】【微】【惊】。 【王】【策】【见】【二】【人】【神】【色】【变】【动】，【已】【是】【知】【晓】【了】【二】【人】【心】【中】【猜】【测】，【便】【是】【要】【开】【口】【直】【言】。 【燕】【武】【阳】【于】【一】【旁】【却】【是】【对】【着】【王】【策】【轻】【轻】【摇】【首】。 【王】【策】【见】【之】，【随】【即】【便】【是】【了】【然】，【收】【声】【不】【言】。 【张】【太】【平】【见】【王】【策】【与】【燕】【武】【阳】【姿】【态】，【亦】【晓】【二】【人】【所】【想】，【他】【向】【着】【二】【人】【开】【口】【说】【道】： “【这】【二】【人】【可】【信】？” 【王】【策】【与】【燕】
“【诸】【位】，【今】【天】【我】【将】【你】【们】【请】【到】【这】【里】【来】，【我】【想】【各】【位】【也】【是】【心】【里】【面】【也】【是】【心】【中】【明】【了】【的】【吧】！”【大】【厅】【之】【中】，【一】【名】【紫】【绶】【金】【印】【的】【青】【年】【也】【是】【对】【着】【在】【座】【的】【而】【十】【余】【人】【笑】【道】。 【只】【是】【这】【青】【年】【的】【笑】【容】【虽】【然】【和】【煦】，【但】【是】【在】【其】【他】【人】【看】【来】，【却】【是】【透】【着】【一】【股】【让】【人】【不】【寒】【而】【栗】【的】【感】【觉】，【今】【天】【过】【来】【多】【半】【是】【要】【破】【财】【免】【灾】。 【都】【说】【不】【到】【首】【都】【不】【知】【道】【自】【己】【官】【小】，【作】【为】【前】【汉】【的】
“【云】【母】？”【秦】【臻】【研】【究】【过】【很】【多】【族】【志】，【里】【面】【对】【云】【母】【的】【介】【绍】【都】【不】【是】【很】【多】，【她】【也】【是】【在】【找】【回】【云】【母】【后】【才】【慢】【慢】【了】【解】【几】【分】。 “【云】【母】【的】【神】【奇】，【不】【是】【常】【理】【能】【解】【释】【的】。【云】【母】【依】【附】【我】【族】【的】【同】【时】，【给】【我】【们】【带】【来】【了】【巨】【大】【的】【力】【量】，【还】【有】。。”【文】【楠】【说】【着】，【回】【头】【看】【着】【梦】【云】【兮】。 【秦】【臻】【跟】【着】【看】【过】【去】，【只】【见】【她】【身】【上】【发】【出】【淡】【淡】【的】【光】【芒】，“【这】【是】？？？”
【现】【在】【希】【望】**【也】【算】【是】【彻】【底】【毁】【了】，【没】【了】【周】【映】【蓉】【这】【个】【大】【头】，【又】【出】【动】【了】【那】【么】【多】【人】【力】【物】【力】，【现】【在】【的】【希】【望】**【已】【经】【沦】【落】【到】【了】【一】【个】【小】**，【就】【算】【想】【要】【在】【称】【大】【也】【是】【没】【有】【机】【会】【的】【了】，【至】【少】【他】【就】【不】【会】【给】【对】【方】【成】【长】【起】【来】【的】【机】【会】。 【张】【弛】【带】【着】【姚】【大】【力】【找】【上】【了】【门】【来】，【孟】【清】【这】【会】【正】【坐】【在】【院】【里】【与】【沈】【音】【闲】【谈】，【何】【阳】【出】【关】【后】，【将】【余】【下】【的】【摊】【子】【都】【包】【了】【起】【来】，【男】100期跑狗归图【时】【间】。 【就】【这】【样】【在】【混】【乱】【中】，【慢】【慢】【的】【过】【去】。 【而】【整】【个】【游】【戏】【场】。【也】【是】【在】【这】【一】【次】【又】【一】【次】【的】【怪】【物】【袭】【击】【中】，【变】【得】【越】【来】【越】【危】【险】！ 【每】【一】【次】【来】【袭】【的】【敌】【人】【都】【会】【变】【得】【更】【强】，【让】【参】【赛】【者】【们】【越】【来】【越】【感】【觉】【无】【力】【不】【说】，【这】【每】【一】【次】【战】【斗】【后】，【所】【留】【残】【下】【来】【的】【剩】【余】【怪】【物】【们】【混】【在】【一】【起】，【也】【是】【让】【这】【大】【地】【上】【变】【得】【处】【处】【充】【满】【了】【危】【机】。【就】【像】【是】【生】【活】【在】【怪】【物】【堆】【中】【一】【样】
【姜】【书】【栋】【和】【林】【逸】【之】【在】【教】【学】【楼】【汇】【聚】【之】【后】【就】【开】【始】【商】【量】【午】【饭】【吃】【什】【么】，【姜】【书】【栋】【最】【近】【体】【能】【消】【耗】【大】，【必】【须】【摄】【入】【高】【热】【量】【食】【物】。 【林】【逸】【之】【富】【贵】【气】【质】【很】【浓】【厚】，【表】【情】【玩】【味】【活】【脱】【脱】【一】【个】【富】【家】【公】【子】，【他】【全】【身】【的】【服】【饰】【不】【加】【手】【表】【都】【已】【经】【上】【万】【了】。 【姜】【书】【栋】【自】【信】【阳】【光】，【穿】【着】【更】【接】【地】【气】，【跟】【漫】【画】【里】【面】【的】【运】【动】【王】【子】【一】【样】。 【两】【个】【帅】【哥】【走】【在】【一】【起】【吸】【引】【了】【不】【少】【人】
【昆】【山】【深】【处】，【一】【片】【略】【微】【开】【阔】【的】【空】【地】【上】。 【此】【时】，【这】【片】【空】【地】【上】【正】【有】【两】【拨】【人】【相】【互】【对】【峙】【着】，【气】【氛】【显】【得】【剑】【拔】【弩】【张】，【似】【乎】【随】【时】【都】【有】【大】【打】【出】【手】【的】【迹】【象】。 “【诸】【位】【无】【缘】【无】【故】【将】【我】【二】【人】【堵】【在】【这】【里】，【用】【意】【何】【在】？” 【少】【顷】，【一】【名】【年】【轻】【人】【开】【口】【道】，【声】【音】【沉】【稳】，【没】【有】【丝】【毫】【紧】【张】。 【这】【年】【轻】【人】，【正】【是】【自】【无】【花】【谷】【离】【开】【的】【木】【洛】【圻】，【他】【的】【身】【边】，【一】【名】
“【霍】【顿】【长】【老】【被】【袭】【击】【了】，【我】【找】【到】【他】【的】【时】【候】，【他】【已】【经】【陷】【入】【沉】【睡】【中】。” 【霍】【顿】，【掌】【管】【血】【族】【后】【勤】，【性】【格】【温】【和】，【一】【向】【是】【个】【老】【好】【人】【的】【形】【象】，【无】【仇】【无】【怨】【的】【谁】【会】【去】【袭】【击】【他】？ “【陷】【入】【沉】【睡】？【看】【来】【伤】【的】【很】【重】【啊】，【有】【什】【么】【线】【索】【吗】？” 【贝】【德】【沉】【默】【一】【会】【儿】【继】【续】【说】【道】： “【殿】【下】，【他】【的】【上】【有】【伤】【痕】，【应】【该】【是】【被】【咬】【了】。” 【阿】【锦】【挑】【眉】，【这】【年】【头】
【一】【个】【拳】【头】【大】【的】【光】【球】【擦】【着】【余】【啸】【的】【耳】【边】【打】【过】【去】，【落】【在】【海】【中】【爆】【炸】，【打】【起】【的】【水】【花】【溅】【了】【众】【人】【一】【身】，【宝】【船】【猛】【烈】【地】【晃】【动】【了】【几】【下】。 【应】【春】【堂】【的】【人】【都】【被】【震】【住】。 【余】【啸】【捋】【了】【捋】【耳】【边】【的】【头】【发】，【眨】【了】【眨】【眼】【睛】，【道】：“【蒋】【迁】【前】【辈】【生】【什】【么】【气】，【我】【是】【想】【说】，【如】【果】【前】【辈】【但】【凡】【了】【解】【一】【点】【女】【人】，【就】【不】【会】【问】【晚】【辈】【这】【个】【问】【题】【了】。 “【哪】【个】【女】【人】【不】【想】【以】【自】【己】【最】【好】【的】