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2019-12-09 00:18:40|多金宝高手论坛 www.

  

  Updated: March 11, 2019

  1. These graphs show the sonic “fingerprints” of the Top 10 summer hits for eight years, selected from the fingerprints for 1988 - 2018. Use the example for Gloria Estefan’s “1-2-3” below to understand how to read the fingerprints.

  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 or they can have their students use this same activity on Desmos.)

  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.

  On Wednesday our collaborator, the American Statistical Association, will facilitate this 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.

  4. On April 11, we will reveal more information about the graphs at the bottom of this post. 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 graphs 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: March 11, 2019

  These graphs appeared in the New York Times article “Do Summer Songs Sound the Same?” The article appeared in print, but the interactive, online version, let’s you hear the music, see the video, and compare the sonic fingerprints.

  What’s a sonic fingerprint? It’s a radar graph (see Stat Nuggets below) that shows the relative volume, energy, cheerfulness, use of acoustic instruments and “danceability” of a song. The source of the data for these radar charts is the Spotify algorithm that is used by Spotify to pick music that is similar to your favorites. Comparing the fingerprints, Grace B of New Jersey wonders, “if having one characteristic over another would make a top hit more successful? Or, are characteristics of songs different due to the time period in which they are released?” What do you think?

  Check out the article’s two time series graphs. They support the journalists’ premise that summer hits before 2000 sounded very different from each other. Then, from about 2000 to most recently, many hits were “bubble-gum anthems” that sounded the same. Most recently, hits are breaking out of the generic pop sound. But, don’t take the writer’s word for it. Listen to the hits and look at their fingerprints. What’s going on with these graphs?

  Here are some of the student headlines that really capture the main ideas of these graphs: “21st Century: Hit With the Same Old” by Mia of New Jersey and “From Unique to Clone” by Gabrian of Hopkinton, NH.

  You may want to think critically about these additional questions.

  • In a radar chart, what signifies an outlier? An outlier is a song that has sonic characteristics significantly different than most other songs. For each of the 8 years, which characteristics are the most distinctive and which are the most similar? What generalizations can you make about the 5 characteristics?

  • The article proposes that from about 2000 to most recently, summer chart-toppers have been rather homogeneous with what seems like “mathematical songwriting” of generic, teen-oriented pop. In the past few years, there’s been more diversity with such hits as “Nice for What” by Drake, “I Like It” by Cardi B, “Bad Bunny” and J Balvin, and “Psycho” by Post Malone. What’s your opinion?

  • What is your favorite summer song? Make your own radar chart for it. You do not need to have the Spotify algorithm. Just estimate where on the spoke each value may be. You can use the dashed circle, which is the average, as a reference. Compare your radar chart to the charts of your classmates’ favorite songs.

  Below in the Stat Nuggets, we define and explain mathematical terms that apply to these graphs. Look into the archives to see past Stat Nuggets.

  Thank you for participating in “What’s Going On in This Graph?”, which is intended to help you think 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 graph, 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, April 17 to notice and wonder about our last graph of the 2018-19 school year on whether baseball star players are worth what they are paid. We look forward to your responses between 9 a.m. - 2 p.m. Eastern Time during the live online moderation.

  ________

  Stat Nugget for “Do Summer Songs Sound the Same?”

  RADAR CHART & FINGERPRINT

  A radar chart displays in a two-dimensional graph three or more quantitative variables for a single observation. Each of the observation’s variables are represented on axes or spokes which start at one central point. The data values for each variable are represented by the distance from the center of the chart. This distance is the ratio of the data value to the maximum data value for the spoke’s variable. A line connects the data values for each variable making a star-shaped “fingerprint.” We can use a radar chart to determine which observations are most similar and which observations are outliers. The chart has other names including a star, web, spider, cobweb or polar chart.

  In the Summer Hits graphs, we see the fingerprints for the Top 10 summer hits for 8 years. For each hit, there are 5 variables – loudness, energy, “danceability,” “acousticness” and valence (cheerfulness). The dashed circle surrounding the center denotes the average of all songs, with values beyond the circle being above average. Each song’s fingerprint shows its relative characteristics. Songs with similar fingerprints have similar shapes. The stacks of the 10 most popular summer hits show how similar the hits are, with blue stacks having hits that are quite similar to each other, pink stacks being quite different, and purple stacks being in between.

  ALGORITHM

  An algorithm is a set of rules or procedures to solve a problem or perform a task.

  In the Summer Hits graphs, the songs’ fingerprints were generated by using the algorithm that Spotify created to generate music recommendations. Spotify’s algorithm scores songs on characteristics, like those shown in these radar charts, to determine how similar songs are.

  _________

  The graphs for “What’s Going On in This Graph?” are selected in partnership with Sharon Hessney, a Boston mathematics teacher. Ms. Hessney wrote the “Reveal” and Stat Nuggets with Erica Chauvet, a professor at Waynesburg University in Pennsylvania, and moderated online with Heather Overstreet, a mathematics teacher at Franklin County High School, Rocky Mount, Va.

B:

  

  多金宝高手论坛 www.【在】【赛】【事】【对】【抗】【过】【程】【中】,【双】【方】【战】【车】【必】【然】【会】【出】【现】【这】【样】【那】【样】【的】【问】【题】; 【陈】【晨】【这】【边】,【还】【是】【对】【面】【江】【大】【那】【边】,【几】【乎】【都】【是】【脸】【色】【惨】【白】【得】【像】【纸】【一】【样】! 【刺】【耳】【的】【金】【属】【摩】【擦】【声】,【不】【停】【地】【回】【荡】【响】【彻】; 【轰】【鸣】【声】【徘】【徊】【响】【彻】【中】,【两】【方】【战】【车】【死】【死】【地】【胶】【着】。 【滔】【滔】【的】【河】【水】【面】【上】,【呼】【啸】【的】【拂】【风】【声】,【响】【彻】【不】【绝】,【吹】【彻】【得】【岸】【边】【卷】【起】**【尘】【杀】【四】【起】; 【依】【靠】【陈】

  “【现】【在】【的】【情】【况】【就】【是】【这】【样】【了】。”【众】【人】【望】【着】【叶】【子】【毫】【无】【意】【识】【的】【身】【体】,【感】【到】【了】【一】【阵】【阵】【的】【担】【忧】。 “【他】【身】【体】【的】【各】【项】【指】【标】【都】【很】【正】【常】,【但】【就】【是】【醒】【不】【过】【来】。”【炫】【炫】【十】【分】【着】【急】【的】【看】【着】【屏】【幕】【上】【的】【数】【据】【说】【道】。 “【看】【来】,【人】【类】【的】【科】【技】【是】【无】【法】【解】【释】【这】【边】【的】【情】【况】【了】。”【达】【芬】【妮】【转】【身】【看】【向】【了】【巨】【树】【周】【围】【的】【传】【送】【门】。 “【对】【啊】,【也】【许】【那】【些】【亚】【特】【兰】【蒂】【斯】【人】

  【梦】【梦】【的】【话】【陈】【彦】【斌】【一】【点】【都】【不】【反】【对】,【因】【为】【他】【看】【到】【的】【这】【些】【奇】【怪】【的】【族】【落】,【其】【实】【力】,【不】【论】【是】【哪】【一】【个】【都】【不】【在】【天】【庭】**【之】【下】。 【这】【时】【候】【狼】【魔】【兽】【还】【抱】【着】【冰】【棺】【跟】【里】【面】【的】【美】【女】【述】【说】【心】【事】,【陈】【彦】【斌】【也】【不】【好】【意】【思】【打】【搅】。 “【咱】【们】【先】【看】【一】【下】【具】【体】【情】【况】,【也】【免】【得】【一】【会】【儿】【万】【一】【出】【了】【事】【情】,【咱】【们】【逃】【跑】【的】【时】【候】,【会】【左】【右】【为】【难】。”【看】【着】【眼】【前】【混】【乱】【不】【堪】【的】【战】【斗】,

  【结】【局】【很】【匆】【忙】,【心】【里】【还】【是】【有】【不】【少】【遗】【憾】【的】。 【这】【一】【路】【走】【来】,【十】【分】【感】【谢】【各】【位】**【爱】【的】【陪】【伴】。 【因】【为】【有】【你】【们】,【我】【感】【到】【十】【分】【欣】【慰】,【现】【在】,【我】【们】【该】【说】【一】【声】【再】【见】【了】。 【有】【缘】【再】【聚】【吧】,【谢】【谢】【能】【看】【到】【这】【里】【的】【你】【们】。

  “【小】【孩】【子】【无】【辜】,【你】【要】【是】【还】【有】【点】【儿】【人】【性】,【就】【放】【了】【晴】【晴】。” 【热】【气】【氤】【氲】,【程】【历】【的】【脸】【偶】【尔】【很】【模】【糊】,【他】【冷】【呵】【一】【声】,“【你】【还】【真】【不】【怕】【死】【了】。” 【我】【凄】【然】【一】【笑】,“【于】【先】【生】,【还】【有】【一】【句】【话】,【想】【对】【你】【说】。” 【我】【称】【他】“【于】【先】【生】”,【他】【眼】【中】【掠】【过】【一】【丝】【波】【澜】。【他】【一】【定】【会】【想】【到】【晓】【如】,【这】【是】【于】【尧】【两】【个】【字】【的】【出】【处】;【或】【许】【吧】,【他】【还】【会】【想】【到】,【我】【们】【相】【识】多金宝高手论坛 www.【尹】【舒】【枫】【整】【个】【人】【的】【精】【神】【状】【态】【特】【别】【差】,【脸】【上】【也】【失】【去】【了】【往】【日】【的】【神】【采】,【看】【上】【去】【颇】【有】【些】【狼】【狈】【的】【样】【子】。 【君】【临】【天】【看】【到】【她】【的】【这】【个】【样】【子】,【心】【里】【感】【觉】【到】【十】【分】【心】【疼】,【直】【接】【就】【上】【前】【阻】【止】【了】【她】【的】【行】【为】,【让】【她】【不】【能】【够】【再】【继】【续】【糟】【蹋】【自】【己】【的】【身】【体】。 “【你】【不】【要】【拦】【着】【我】,【你】【知】【不】【知】【道】【现】【在】【外】【面】【的】【情】【况】【有】【多】【么】【紧】【张】,【留】【给】【我】【的】【时】【间】【根】【本】【就】【不】【多】【了】,【我】【必】【须】【要】

  【玉】【歌】【交】【了】【十】【块】【下】【品】【灵】【石】【后】,【进】【入】【城】【中】【兴】【致】【勃】【勃】【的】【逛】【了】【起】【来】。【玫】【瑰】【仙】【城】【不】【愧】【为】【十】【大】【仙】【城】【之】【一】,【比】【起】【偏】【远】【的】【海】【啸】【城】,【这】【里】【更】【加】【的】【繁】【华】,【城】【中】【灵】【气】【更】【加】【充】【足】,【比】【缥】【缈】【仙】【宗】【内】【门】【也】【不】【差】。【街】【上】【人】【来】【人】【往】,【热】【闹】【无】【比】。【城】【池】【中】【心】【一】【座】【最】【高】【的】【建】【筑】,【是】【玫】【瑰】【仙】【城】【的】【标】【志】【性】【建】【筑】,【每】【到】【一】【个】【时】【辰】,【钟】【楼】【会】【钟】【鸣】【一】【次】。【见】【天】【色】【还】【早】,【玉】【歌】【打】

  “【说】【出】【你】【们】【真】【正】【的】【意】【图】!”【王】【廷】【之】【主】【直】【接】【开】【门】【见】【山】【地】【说】【道】。 【那】【金】【莲】【仙】【妖】【媚】【的】【眸】【子】,【快】【速】【地】【转】【动】【了】【一】【下】,【笑】【道】:“【王】【廷】【之】【主】【不】【愧】【是】【一】【方】【枭】【雄】,【做】【人】【做】【事】,【也】【是】【快】【人】【快】【语】。” “【既】【然】【如】【此】,【那】【我】【便】【直】【说】【了】。” “【我】【圣】【族】【的】【生】【存】【环】【境】,【越】【来】【越】【恶】【劣】,【每】【天】【都】【有】【大】【批】【的】【圣】【族】【勇】【士】【无】【端】【死】【去】。” “【所】【以】,【我】【代】【表】【圣】

  【自】【从】【明】【熙】【的】【封】【印】【出】【现】【裂】【痕】,【秦】【婠】【的】【日】【子】【就】【变】【得】【水】【深】【火】【热】【起】【来】。 【明】【熙】【不】【仅】【觉】【醒】【了】【部】【分】【记】【忆】,【实】【力】【也】【变】【得】【越】【来】【越】【强】【了】! 【整】【个】【人】【还】【成】【了】【资】【深】【病】【娇】,【天】【天】【都】【想】【把】【秦】【婠】【关】【在】【小】【黑】【屋】【里】。 【秦】【婠】【一】【看】【情】【况】【不】【妙】,【果】【断】【溜】【了】。 【谁】【知】【这】【一】【溜】,【接】【下】【来】【的】【位】【面】【就】【成】【了】【修】【罗】【场】。 【穿】【到】【原】【始】【位】【面】,【过】【去】【时】【明】【熙】【已】【经】【从】【炮】【灰】**

  【大】【风】【起】【兮】【云】【飞】【扬】?【安】【得】【猛】【士】【兮】【守】【四】【方】? 【很】【抱】【歉】【的】【是】,【此】【时】【此】【刻】【的】【环】【境】【里】【不】【仅】【没】【有】【什】【么】【大】【风】【起】【兮】,【更】【没】【有】【什】【么】【猛】【士】。【只】【有】【一】【名】【死】【士】,【满】【脑】【子】【里】【都】【是】【进】【攻】【和】【鲜】【血】。 【然】【就】【在】【这】【名】‘【死】【士】’【刚】【迈】【出】【向】【死】【的】【第】【一】【步】【时】【候】,【周】【围】【的】【所】【有】【开】【始】【扭】【曲】【且】【不】【断】【崩】【塌】。【熟】【悉】【的】【尘】【埃】【气】【味】【扑】【鼻】【而】【来】【呛】【得】【我】【忍】【不】【住】【的】【咳】【嗽】。 【模】【糊】【的】【人】【影】