Data Science with Python

IA - 2 - Data Science Students.... Problem Description: A team of adventurers (Alex, Ben, and Chloe) are searching for a hidden treasure in a dense jungle. They have a map with cryptic clues based on mathematical principles.

Statistics Branch of science that deals with the collection, organization, analysis, interpretation, and presentation of data. Purpose of statistics is to make an inference about a population by examining a sample. Collection of Data Refers to the process of gathering information. Primary source: questionnaires, interviews. Secondary source: journals, books. Presentation of Data Organization and arrangement of data in tabular form (tables), graphical representation (graphs). Analysis of Data Application and interpretation using statistical tools to derive meaning. Inspection of Data Descriptive Statistics: Involves describing the basic features of the data in a study. Provides simple summaries about the sample and measures. Inferential Statistics: Makes judgments and reaches conclusions about populations based on samples. Population vs Sample Population: entirety Sample: only part of population Fundamental or Descriptive Statistics: Measures Of Central Tendency: Mean (average) Median (middle value) Mode (most frequent) Measures Of Dispersion/Variability: Range (difference between highest & lowest) Variance & standard deviation Measures Of Position: Quartiles & percentiles Measures Of Relationship Between Variables: Correlation coefficient Types Of Data: Primary Data – original source. Secondary Data – derived from primary. Major Characteristics Of Data Sources: Primary Source – direct from respondent; more accurate; costly; time-consuming. Secondary Source – characteristic not

“There’s No Such Thing as Sound Science” by By Christie Aschwanden was a lead science writer for FiveThirtyEight. FiveThirtyEight, Science, Dec. 6, 2017 Science is being turned against itself. For decades, its twin ideals of transparency and rigor have been weaponized by those who disagree with results produced by the scientific method. Under the Trump administration, that fight has ramped up again. In a move ostensibly meant to reduce conflicts of interest, Environmental Protection Agency Administrator Scott Pruitt has removed a number of scientists from advisory panels and replaced some of them with representatives from industries that the agency regulates. Like many in the Trump administration, Pruitt has also cast doubt on the reliability of climate science. For instance, in an interview with CNBC, Pruitt said that “measuring with precision human activity on the climate is something very challenging to do.” Similarly, Trump’s pick to head NASA, an agency that oversees a large portion the nation’s climate research, has insisted that research into human influence on climate lacks certainty, and he falsely claimed that “global temperatures stopped rising 10 years ago.” Kathleen Hartnett White, Trump’s nominee to head the White House Council on Environmental Quality, said in a Senate hearing last month that she thinks we “need to have more precise explanations of the human role and the natural role” in climate change. The same entreaties crop up again and again: We need to root out conflicts. We need more precise evidence. What makes these arguments so powerful is that they sound quite similar to the points raised by proponents of a very different call for change that’s coming from within science. This other movement strives to produce more robust, reproducible findings. Despite having dissimilar goals, the two forces espouse principles that look surprisingly alike: Science needs to be transparent. Results and methods should be openly shared so that outside researchers can independently reproduce and validate them. The methods used to collect and analyze data should be rigorous and clear, and conclusions must be supported by evidence. These are the arguments underlying an “open science” reform movement that was created, in part, as a response to a “reproducibility crisis” that has struck some fields of science.1 But they’re also used as talking points by politicians who are working to make it more difficult for the EPA and other federal agencies to use science in their regulatory decision-making, under the guise of basing policy on “sound science.” Science’s virtues are being wielded against it. What distinguishes the two calls for transparency is intent: Whereas the “open science” movement aims to make science more reliable, reproducible and robust, proponents of “sound science” have historically worked to amplify uncertainty, create doubt and undermine scientific discoveries that threaten their interests. “Our criticisms are founded in a confidence in science,” said Steven Goodman, co-director of the Meta-Research Innovation Center at Stanford and a proponent of open science. “That’s a fundamental difference — we’re critiquing science to make it better. Others are critiquing it to devalue the approach itself.” Calls to base public policy on “sound science” seem unassailable if you don’t know the term’s history. The phrase was adopted by the tobacco industry in the 1990s to counteract mounting evidence linking secondhand smoke to cancer. A 1992 Environmental Protection Agency report identified secondhand smoke as a human carcinogen, and Philip Morris responded by launching an initiative to promote what it called “sound science.” In an internal memo, Philip Morris vice president of corporate affairs Ellen Merlo wrote that the program was designed to “discredit the EPA report,” “prevent states and cities, as well as businesses from passing smoking bans” and “proactively” pass legislation to help their cause. The sound science tactic exploits a fundamental feature of the scientific process: Science does not produce absolute certainty. Contrary to how it’s sometimes represented to the public, science is not a magic wand that turns everything it touches to truth. Instead, it’s a process of uncertainty reduction, much like a game of 20 Questions. Any given study can rarely answer more than one question at a time, and each study usually raises a bunch of new questions in the process of answering old ones. “Science is a process rather than an answer,” said psychologist Alison Ledgerwood of the University of California, Davis. Every answer is provisional and subject to change in the face of new evidence. It’s not entirely correct to say that “this study proves this fact,” Ledgerwood said. “We should be talking instead about how science increases or decreases our confidence in something.” The tobacco industry’s brilliant tactic was to turn this baked-in uncertainty against the scientific enterprise itself. While insisting that they merely wanted to ensure that public policy was based on sound science, tobacco companies defined the term in a way that ensured that no science could ever be sound enough. The only sound science was certain science, which is an impossible standard to achieve. “Doubt is our product,” wrote one employee of the Brown & Williamson tobacco company in a 1969 internal memo. The note went on to say that doubt “is the best means of competing with the ‘body of fact’” and “establishing a controversy.” These strategies for undermining inconvenient science were so effective that they’ve served as a sort of playbook for industry interests ever since, said Stanford University science historian Robert Proctor. The sound science push is no longer just Philip Morris sowing doubt about the links between cigarettes and cancer. It’s also a 1998 action plan by the American Petroleum Institute, Chevron and Exxon Mobil to “install uncertainty” about the link between greenhouse gas emissions and climate change. It’s industry-funded groups’ late-1990s effort to question the science the EPA was using to set fine-particle-pollution air-quality standards that the industry didn’t want. And then there was the more recent effort by Dow Chemical to insist on more scientific certainty before banning a pesticide that the EPA’s scientists had deemed risky to children. Now comes a move by the Trump administration’s EPA to repeal a 2015 rule on wetlands protection by disregarding particular studies. (To name just a few examples.) Doubt merchants aren’t pushing for knowledge, they’re practicing what Proctor has dubbed “agnogenesis” — the intentional manufacture of ignorance. This ignorance isn’t simply the absence of knowing something; it’s a lack of comprehension deliberately created by agents who don’t want you to know, Proctor said.2 In the hands of doubt-makers, transparency becomes a rhetorical move. “It’s really difficult as a scientist or policy maker to make a stand against transparency and openness, because well, who would be against it?” said Karen Levy, researcher on information science at Cornell University. But at the same time, “you can couch everything in the language of transparency and it becomes a powerful weapon.” For instance, when the EPA was preparing to set new limits on particulate pollution in the 1990s, industry groups pushed back against the research and demanded access to primary data (including records that researchers had promised participants would remain confidential) and a reanalysis of the evidence. Their calls succeeded and a new analysis was performed. The reanalysis essentially confirmed the original conclusions, but the process of conducting it delayed the implementation of regulations and cost researchers time and money. Delay is a time-tested strategy. “Gridlock is the greatest friend a global warming skeptic has,” said Marc Morano, a prominent critic of global warming research and the executive director of ClimateDepot.com, in the documentary “Merchants of Doubt” (based on the book by the same name). Morano’s site is a project of the Committee for a Constructive Tomorrow, which has received funding from the oil and gas industry. “We’re the negative force. We’re just trying to stop stuff.” Some of these ploys are getting a fresh boost from Congress. The Data Quality Act (also known as the Information Quality Act) was reportedly written by an industry lobbyist and quietly passed as part of an appropriations bill in 2000. The rule mandates that federal agencies ensure the “quality, objectivity, utility, and integrity of information” that they disseminate, though it does little to define what these terms mean. The law also provides a mechanism for citizens and groups to challenge information that they deem inaccurate, including science that they disagree with. “It was passed in this very quiet way with no explicit debate about it — that should tell you a lot about the real goals,” Levy said. But what’s most telling about the Data Quality Act is how it’s been used, Levy said. A 2004 Washington Post analysis found that in the 20 months following its implementation, the act was repeatedly used by industry groups to push back against proposed regulations and bog down the decision-making process. Instead of deploying transparency as a fundamental principle that applies to all science, these interests have used transparency as a weapon to attack very particular findings that they would like to eradicate. Now Congress is considering another way to legislate how science is used. The Honest Act, a bill sponsored by Rep. Lamar Smith of Texas,3 is another example of what Levy calls a “Trojan horse” law that uses the language of transparency as a cover to achieve other political goals. Smith’s legislation would severely limit the kind of evidence the EPA could use for decision-making. Only studies whose raw data and computer codes were publicly available would be allowed for consideration. That might sound perfectly reasonable, and in many cases it is, Goodman said. But sometimes there are good reasons why researchers can’t conform to these rules, like when the data contains confidential or sensitive medical information.4 Critics, which include more than a dozen scientific organizations, argue that, in practice, the rules would prevent many studies from being considered in EPA reviews.5 It might seem like an easy task to sort good science from bad, but in reality it’s not so simple. “There’s a misplaced idea that we can definitively distinguish the good from the not-good science, but it’s all a matter of degree,” said Brian Nosek, executive director of the Center for Open Science. “There is no perfect study.” Requiring regulators to wait until they have (nonexistent) perfect evidence is essentially “a way of saying, ‘We don’t want to use evidence for our decision-making,’” Nosek said. Most scientific controversies aren’t about science at all, and once the sides are drawn, more data is unlikely to bring opponents into agreement. Michael Carolan, who researches the sociology of technology and scientific knowledge at Colorado State University, wrote in a 2008 paper about why objective knowledge is not enough to resolve environmental controversies. “While these controversies may appear on the surface to rest on disputed questions of fact, beneath often reside differing positions of value; values that can give shape to differing understandings of what ‘the facts’ are.” What’s needed in these cases isn’t more or better science, but mechanisms to bring those hidden values to the forefront of the discussion so that they can be debated transparently. “As long as we continue down this unabashedly naive road about what science is, and what it is capable of doing, we will continue to fail to reach any sort of meaningful consensus on these matters,” Carolan writes. The dispute over tobacco was never about the science of cigarettes’ link to cancer. It was about whether companies have the right to sell dangerous products and, if so, what obligations they have to the consumers who purchased them. Similarly, the debate over climate change isn’t about whether our planet is heating, but about how much responsibility each country and person bears for stopping it. While researching her book “Merchants of Doubt,” science historian Naomi Oreskes found that some of the same people who were defending the tobacco industry as scientific experts were also receiving industry money to deny the role of human activity in global warming. What these issues had in common, she realized, was that they all involved the need for government action. “None of this is about the science. All of this is a political debate about the role of government,” she said in the documentary. These controversies are really about values, not scientific facts, and acknowledging that would allow us to have more truthful and productive debates. What would that look like in practice? Instead of cherry-picking evidence to support a particular view (and insisting that the science points to a desired action), the various sides could lay out the values they are using to assess the evidence. For instance, in Europe, many decisions are guided by the precautionary principle — a system that values caution in the face of uncertainty and says that when the risks are unclear, it should be up to industries to show that their products and processes are not harmful, rather than requiring the government to prove that they are harmful before they can be regulated. By contrast, U.S. agencies tend to wait for strong evidence of harm before issuing regulations. Both approaches have critics, but the difference between them comes down to priorities: Is it better to exercise caution at the risk of burdening companies and perhaps the economy, or is it more important to avoid potential economic downsides even if it means that sometimes a harmful product or industrial process goes unregulated? In other words, under what circumstances do we agree to act on a risk? How certain do we need to be that the risk is real, and how many people would need to be at risk, and how costly is it to reduce that risk? Those are moral questions, not scientific ones, and openly discussing and identifying these kinds of judgment calls would lead to a more honest debate. Science matters, and we need to do it as rigorously as possible. But science can’t tell us how risky is too risky to allow products like cigarettes or potentially harmful pesticides to be sold — those are value judgements that only humans can make.

Make a multiple choice quiz for my year 8 science students based on the science in this transcript from a video: 3°C 0:04 It can be the difference between snow and sleet 0:08 Wearing a jacket or not 0:11 In your day-to-day life, it may not seem significant 0:15 But 3°C of global warming would be catastrophic 0:20 Heatwaves, droughts, extreme precipitation, even fire 0:25 3°C of warming is really disastrous 0:28 The scary thing is, the world is well on its way there 0:32 Since the industrial revolution, the Earth has warmed between 1.1°C and 1.3°C 0:40 This is a problem that babies you pass in the street will have to live with 0:46 Children born today... 0:47 ...are up to seven times more likely to face extreme weather than their grandparents 0:52 If global temperatures do rise by 3°C... 0:55 ...what would their world look like? Climate change is already having devastating effects 1:03 Rising sea levels 1:05 Desertification 1:07 Hollywood has always enjoyed imagining the end of the world 1:11 While blockbusters like this are clearly fiction... 1:14 ...this film will show the scenario we all face... 1:17 ...unless more drastic measures are taken to stop burning fossil fuels 1:30 In some parts of the world the effects of inaction are already clear 1:35 The slums of Bangladesh’s capital are filling up with climate migrants 1:41 Minara comes from Bhola District, an area in southern Bangladesh 1:46 There, like many other parts of the country... 1:49 ...rivers swollen by heavier rain and melting Himalayan glaciers... 1:53 ...are washing away people’s homes 1:56 Many, like her, have lost everything 2:00 Our home in Bhola had endless amounts of land 2:03 There was lots of space for farming, we had a spacious house 2:08 There were different types of fruits, vegetation and trees growing at home 2:12 We used to eat the fruit from our own trees 2:18 I can’t eat them now because they don't exist anymore 2:21 Since the river flooded for the third time, I had to flee to Dhaka 2:26 Life was much better back home 2:29 It was unbearable to live through, truly intolerable 2:33 We didn’t have the time to save anything at all 2:38 1.1°C to 1.3°C of global warming has already transformed Minara’s life 2:45 It’s one of the reasons why so many migrants like her... 2:47 ...are moving to the city each year... 2:50 ...nearly 400,000 according to the last estimate 2:53 And climate models show there could be much worse to come How climate modelling works 3:02 Climate scientist Joeri Rogelj... 3:04 ...has spent the last ten years modelling future climate scenarios... 3:08 ...for the United Nations 3:10 The models we use to carry out this exercise... 3:13 ...really represent the state of the art... 3:15 ...of our current knowledge of climate change and where we are heading 3:19 Joeri’s projections use data collected by hundreds of scientists around the world 3:26 Here this is the 3°C level... 3:28 ...and so there is at least a one-in-four chance that under current policies... 3:32 ...we would hit 3°C by the end of the century 3:36 This is just one of the scenarios Joeri looks at 3:40 Another one imagines that all policy promises are kept 3:44 The most optimistic assumes that all promises have been kept... 3:47 ...and net-zero targets are met 3:50 Where our best estimate ends up around 2°C at the end of the century... 3:54 ...there is still a one-in-20 chance that we end up with 3°C instead 3:59 One would not be entering a plane if there is a one-in-20 chance... 4:03 ...that the plane will crash Nowhere is safe from global warming 4:07 A rise of 3°C would affect everyone 4:10 Even wealthy cities in rich countries wouldn’t be immune to the consequences 4:15 European capitals like Paris and Berlin... 4:18 ...would bake under more extreme heatwaves 4:22 Frequent storm-surges in New York could turn parts of the city desolate 4:27 In many ways, cities magnify, intensify climate events 4:33 Cities are hotter than the places around them... 4:36 ...they tend to be more vulnerable to flooding 4:39 And you can get a really bad event in a city in a way that you can’t in the countryside 4:46 And because of their denser populations... 4:49 ...disasters in a city affect far more people 4:52 Some cities might be badly prepared for the changes coming 4:56 But they have the means to adapt 4:59 Cities tend to be wealthier than surrounding places 5:03 They have a lot of amenities 5:05 A city that has taken seriously the risks of a 3°C world... 5:08 …wouldn’t necessarily be a worse place to be in a 3°C world 5:12 But a city that hasn’t prepared for these sort of eventualities... 5:16 ...that might be a really nasty place The impact of prolonged droughts 5:20 So far, many developed cities have got off lightly... 5:24 ...but some rural parts of the world are suffering disproportionately 5:29 Smallholders—small-scale farmers—are particularly vulnerable to climate change 5:35 And there are over 600 million around the world 5:38 Smallholders with farms under two hectares... 5:40 ...produce around a third of the global food supply 5:46 Central America’s “Dry Corridor”... 5:48 ...supports a mix of smallholdings and medium-sized farms 5:53 Sandwiched between the Pacific Ocean and the Caribbean Sea... 5:56 ...the area is prone to droughts 6:08 Israel Ramírez Rivera is a smallholder in Guatemala 6:12 Here, climate change is making the dry seasons longer, and more severe 6:18 This is the biggest ear of maize that this plot could deliver 6:23 He depends on his crops of corn and beans 6:26 But they’re getting harder to grow 6:30 The surrounding mountains... 6:32 ...used to provide us with native food... 6:38 ...and now that isn’t an option anymore... 6:41 ...due to climate change and its effects 6:46 Nearly two-thirds of the smallholders in the Dry Corridor now live in poverty 6:52 The impact of all of this for us... 6:59 ...malnutrition among children 7:03 We’ve lost a few 7:07 For my crops especially, the midsummer heat is harder than before 7:16 The plant dries up and can’t provide us... 7:19 ...with the necessary food provision 7:24 Severe droughts in Central America... 7:26 ...are now four times more likely than they were last century 7:30 Many families from here have gone to the States 7:37 The economic despair and debts... 7:44 ...have pushed many people from this community to do this journey 7:53 Migration from Guatemala to the United States has quadrupled since 1990 7:59 Not all of this has been due to climate change 8:02 But longer droughts would force even more to move 8:05 In a 3°C world, annual rainfall in this region... 8:09 ...could drop by up to 14% 8:12 At 3°C, over a quarter of the world’s population... 8:16 ...could endure extreme droughts for at least a month of the year 8:19 Northern Africa could see droughts that last for years at a time Rising sea levels, storm surges and flooding 8:24 But for some, too much water will be the problem 8:29 10% of the world’s population lives on a coastline... 8:32 ...that’s less than 10 metres above sea level 8:35 For these coastal inhabitants, a 3°C world would spell disaster 8:40 By 2100, global sea levels could have climbed by half a metre from 2005 levels 8:46 Low-lying cities like Lagos would be especially vulnerable... 8:49 ...with up to up to a third of the population displaced 8:54 And in Fiji, rising waters are already upending lives 9:04 You can see the graveyard there, it’s all under water now... 9:08 ...due to this rising sea level and climate change 9:15 The village of Togoru in Fiji is being swallowed by the sea 9:19 Barney Dunn, the village headman, has seen over half the village disappear 9:24 Relatives’ houses have been abandoned, and family graves are now under water 9:29 We have been asked by the government to relocate... 9:32 ...but no one wants to relocate... 9:34 ...because we have our great-great-grandparents down there in the sea 9:39 This is the place we’ve been brought up in 9:41 ...it’s not easy to leave 9:44 Past attempts to build a seawall haven’t worked 9:48 But Barney sees building a new one as the village’s only hope 9:52 If they do that, maybe we can save whatever is left 9:56 But if we don’t have the seawall, then it will be keep eroding and time will come... 10:01 ...maybe in ten,15 years, Togoru will be all eroded 10:05 Rising seas also mean storms cause more floods 10:11 And many more countries could suffer 10:14 The Philippines and Myanmar are just two countries... 10:17 ...that will also see an increase in storm surges in a 3°C world 10:21 To escape, many will move… 10:24 …often, to urban areas Extreme heat and wet-bulb temperatures 10:27 Half the world’s population already lives in cities... 10:31 ...almost a third in slums 10:36 For them, a 3°C world could be deadly 10:40 Minara has moved to Dhaka to escape the impact of climate change 10:44 But life could get even worse for her 10:47 I’m struggling a lot nowadays 10:49 The heat during the day is unbearable 10:52 Even late at night it doesn’t cool down 10:57 The heat is getting more intense every day 10:59 I mean, it’s going to get much worse 11:03 I can barely survive it now, how will I live through it in the future? 11:08 Dhaka is getting hotter 11:11 In the last 20 years the average daytime temperature... 11:13 ...has crept up by nearly half a degree 11:17 Days that approach 40°C are now being reported 11:20 And high so-called wet-bulb temperatures are on the rise 11:26 A wet-bulb temperature is a measure of heat and humidity 11:30 Humans cool themselves by sweating… 11:32 But in these conditions, when relative humidity is near 100%... 11:36 ...sweat doesn’t evaporate well 11:38 So people can’t cool down… 11:41 ...even if given unlimited shade and water 11:45 At a high wet-bulb temperature, the body can’t lose heat... 11:49 ...and so it gets hotter and hotter... 11:51 ...and the body is designed to work at a given temperature 11:53 And if it gets too hot inside, you will die 11:58 The human limit for wet-bulb temperatures is 35°C... 12:02 ...around skin temperature 12:04 Dhaka will have a much higher chance... 12:05 ...of reaching dangerous wet-bulb temperatures... 12:07 ...if global warming reaches 3°C 12:12 You can’t really adapt to that 12:14 You have to get out. If the temperature is so high that you can’t work... 12:20 ...can’t do hard manual labour outside for significant parts of the year... 12:25 ...then many places will become functionally no longer part of the economy 12:33 Jacobabad in Pakistan, and Ras al Khaimah, in the United Arab Emirates... 12:37 ...have already recorded deadly wet-bulb temperatures 12:40 More of the tropics and the Persian Gulf... 12:43 ...as well as parts of Mexico and the south-eastern United States... 12:47 ...could all get to this threshold by the end of the century 12:50 Climate modelling might show us the weather Increased migration and conflict 12:52 But it doesn’t show us its other effects on society 12:56 Established migration patterns could change 12:59 Climate disasters may exacerbate reasons people cross borders 13:03 Within countries, more people will move to cities 13:07 In a 3°C world, tens of millions of people a year... 13:10 ...could be displaced by disasters made worse by climate change 13:15 When people are displaced by climate... 13:18 …they may well go to cities... 13:19 ...because cities are the places that attract people from the countryside already 13:25 A lot of people who can get to the developed world... 13:28 ...not least because the developed world tends to be less hot, will give that a go 13:35 As migration around the world increases... 13:38 ...there could be more competition for fewer resources 13:42 Water—already a highly contested resource—will be a focal point 13:47 Turkey’s new Ilisu dam has reduced the flow of water into Iraq 13:53 China lays claim to rivers vital to India and Pakistan 13:57 The prospect of a water-conflict makes people very uneasy 14:03 How national tensions would exacerbate those sorts of reactions... 14:08 ...in a 3°C world... 14:09 ...is the sort of thing that no one should really want to find out 14:14 I think you’d have to be incredibly sanguine... 14:16 ...not to think that the sort of climate extremes that we talk about... 14:19 ...in a 3°C world wouldn’t lead some places... 14:22 ...to the brink of societal collapse 14:25 Those lucky enough to escape unrest... Adaptation and mitigation are crucial 14:28 ...would still have to adapt to a radically different world 14:32 People can adapt to climate change in all sorts of ways, one of the most obvious ones... 14:37 ...is air conditioning 14:39 But other ways to adapt at a local or regional level... 14:42 ...I mean, one of the most obvious is diversifying agriculture 14:47 There are physical things you can do, like seawalls 14:52 The fact that people can adapt and that adaptation will reduce suffering... 14:57 ...doesn’t mean that it will eliminate suffering 15:00 Suffering is built into this whole process of heating up the planet 15:06 Adaptation will only get the world so far 15:09 The best way to deal with a 3°C world... 15:12 ...is not to go to a 3°C world 15:14 And that’s why increasing efforts on mitigation are important 15:17 It’s why working towards negative emissions... 15:20 ...that could bring down the temperature after it peaks are important 15:25 Once you get to a 3°C world, you are in real bad global trouble 15:33 The scale of change needed... 15:35 ...and the slow progress of governments so far... 15:38 ...means 3°C of warming is uncomfortably likely unless more is done 15:44 Despite existing pledges, greenhouse-gas emissions... 15:48 ...are still set to rise by 16% from 2010 levels by 2030 15:54 The need to act has never been clearer 15:57 There’s still time to reduce emissions, so that a 3°C world remains fiction... 16:02 ...rather than becoming fact

Some Arctic Dinos Lived in Herds By Sid Perkins Just as interesting, however, is how this was discovered. Scientists didn’t look at a single fossil bone. Instead, they analyzed a large number of preserved footprints on a mountainside located toward the southern end of central Alaska. Anthony Fiorillo works at the Perot Museum of Nature and Science in Dallas, Texas. As a vertebrate paleontologist, he studies the fossils of creatures with backbones. In 2007, he was part of a research team exploring Denali National Park. “We rounded the corner and there they were,” he recalls. Thousands of footprints had been preserved in stone. “It was amazing.” Dinosaurs died out more than 65 million years ago (not counting birds, their modern-day relatives). So, it’s a bit surprising that scientists know so much about these ancient creatures. Now, a new study reveals that a certain type of duckbilled dinosaur lived in the Arctic year-round. These animals also traveled in herds that included many age groups, they find. The creatures even appear to have gone through a “teenage growth spurt.” Those tracks pepper a steep patch of exposed rock about twice as long as a football field and up to 60 meters (roughly 200 feet) wide. They sit at least 160 kilometers (100 miles) north of the Gulf of Alaska. Between 69 million and 72 million years ago, that now-rocky material was muddy sediment on a floodplain near a seacoast, Fiorillo explains. The hadrosaurs walked across the squishy mud. Later, the footprints they left turned to stone. Previous studies suggested adult duckbills took care of their young, says Fiorillo. The new evidence that these dinosaurs truly traveled in herds with multiple age groups confirms that parents cared for their young well beyond the time they left the nest, his team concludes. The researchers published their findings June 30 in Geology. © Science News for Students Thousands of tracks cover this rocky mountainside in Alaska’s Denali National Park. They provide a wealth of information about the size, age and lifestyle of certain dinosaurs. COURTESY OF PEROT MUSEUM OF NATURE AND SCIENCE EVIDENCE FOR HERDS O F DINOSAURS Small meat-eating dinosaurs called theropods had left behind a few of the tracks that Fiorillo’s team found in Denali. Birds had left some others. But the vast majority came from creatures called hadrosaurs. These large plant-eating duckbilled dinosaurs had been quite common during the Cretaceous Period. That helps explain one of their nicknames: “cattle of the Cretaceous.” For the new study, the researchers focused only on the hadrosaur tracks. More than half of the footprints were preserved so well that they had clear impressions of the skin on the dinosaurs’ feet. Most tracks had a similar level of preservation. That suggests all were probably left within a short period. Other fossils in the nearby rocks, including insect burrows, suggest these hadrosaurs had left their footprints during the summer. These are trace fossils — evidence of ancient life other than a preserved carcass or bone. At the time these dinosaurs lived, Fiorillio says, the average temperature in the warmest months was between 10° and 12° Celsius (50° and 54° Fahrenheit). That’s about what conditions are like today along the border between Canada and the lower 48 U.S. states, he notes. The team measured a large sample of the duckbills’ footprints. They fell into four distinct size ranges. The largest tracks, presumably made by adults, measured about 64 centimeters (25 inches) across. The smallest tracks, 8 centimeters (3 inches) wide, were likely left by young duckbills. They would have been no more than a year old. Tracks of two other size groups were probably made by juveniles and near-adults. These data suggest the community of hadrosaurs included four different age groups. © Science News for Students A hadrosaur footprint made roughly 70 million years ago. For scale, the long blue bar at right is 10 centimeters long; each small blue or white bar measures 1 centimeter. COURTESY OF PEROT MUSEUM OF NATURE AND SCIENCE © Science News for Students THESE DINOSAURS DIDN’T MIGRATE About 84 percent of the tracks sampled for the new study had been left by older hadrosaurs — adults or near-adults. Roughly 13 percent came from the youngest members of the herd. And a mere 3 percent came from herd members considered to be juveniles, says Fiorillo. The rarity of tracks by these tweens suggests that the young of this species had a rapid growth spurt. If true, they would have spent relatively little time at this vulnerable size — and therefore left very few tracks. “What’s really neat is how many small tracks there are,” notes Anthony Martin. An ichnologist — or expert in trace fossils — he works at Emory University in Atlanta, Ga. Other scientists had analyzed fossil bones from duckbills. These studies had hinted that the equivalent of adolescent hadrosaurs would have experienced growth spurts. But the new findings are “the best evidence that I’ve seen,” says Eric Snively. He’s a vertebrate paleontologist at the University of Wisconsin- La Crosse. “This is a great study,” he adds, “and further evidence that juvenile hadrosaurs grew up in an eye-blink.” Also previously, researchers had proposed that Arctic dinosaurs migrated farther south for the winter. That’s because even if the region was much warmer than it is today, nights in the high Arctic would have been 24 hours long. So, with no sunshine for several months, Alaska would have had long periods of very bleak, chilly weather. But finding juveniles in the herd strongly suggests that these dinosaurs remained in the Arctic all year. That’s because adolescents and preadolescents wouldn’t have had the strength or stamina to make those long treks, Fiorillo maintains. Field work is often harsh. Paleontologists studying the dinosaur footprints here on an Alaskan mountainside sometimes worked in cold and fog. COURTESY OF PEROT MUSEUM OF NATURE AND SCIENCE © Science News for Students The presence of very young dinosaurs might have been expected, he notes: If this were a nesting region, the babies would have hatched sometime just before summer. And remember, that’s when these tracks were left. But that wouldn’t explain the juveniles, he says. The team’s findings “suggest that these dinosaurs were overwintering in Alaska somehow,” says Snively. At the time, the average temperature in the region remained above freezing even during the winter, he notes. But, he adds, “this study raises interesting issues about how the dinosaurs could live in the region when it was pretty dark for several months at a time.”

Dès le début de vos recherches, vous allez collecter, produire et exploiter des données. La gestion des données (Research Data Management - RDM) fait partie du processus de recherche. Elle concerne l'ensemble des opérations de collecte, description, stockage, traitement, analyse, archivage et mise en accès des données. (extrait de : Passeport pour la Science Ouverte. Guide pratique pour les doctorants ) "La science ouverte est la diffusion sans entrave des publications et des données de la recherche. Elle s’appuie sur l’opportunité que représente la mutation numérique pour développer l’accès ouvert aux publications et – autant que possible – aux données de la recherche. "Les données de la recherche sont la matière première de la connaissance. Les partager, c'est ouvrir de nouvelles perspectives scientifiques" Source : Plan national pour la Science ouverte - Ministère ESR - Juillet 2018 Source image : https://bibliotheques.univ-tlse3.fr/file/composantes-science-ouverte Cette page est une introduction à la gestion des données de recherche. Elle présente quelques concepts et étapes clés pour vous engager dans cette démarche. Consultez les liens pour approfondir vos connaissances. • What are data ? Définition des données de recherche de l’OCDE (2007) « Enregistrements factuels (chiffres, textes, images, sons) utilisés comme source principale pour la recherche scientifique et généralement reconnus par la communauté scientifique comme nécessaires pour valider les résultats de la recherche. Un ensemble de données de recherche constitue une représentation systématique et partielle du sujet faisant l’objet de la recherche ». Exemples • les images d’une ville préhistorique deviennent des données pour un chercheur qui étudie l’histoire de cette ville; • les « données » d’un linguiste peuvent être des écrits ou des discours, des enregistrements de locuteurs ; • les « données » d’un médiéviste sont des sources archivistiques, archéologiques, épigraphiques, iconographiques, littéraires ; • les « données » d’un géologue rassemblent des coupes et observations de terrain consignées sur un carnet, des résultats de carottage, des analyses d’échantillons, des données sismographiques… • • Pourquoi partager ses données ? "La science ouverte vise à construire un écosystème dans lequel la science est plus cumulative, plus fortement étayée par des données, plus transparente, plus rapide et d’accès plus universel.La science ouverte favorise également les avancées scientifiques, particulièrement les avancées imprévues, ainsi que l’innovation, les progrès économiques et sociaux, en France, dans les pays développés et dans les pays en développement. Enfin, la science ouverte constitue un levier pour l’intégrité scientifique et favorise la confiance des citoyens dans la science. Elle constitue un progrès scientifique et un progrès de société." Source : Plan national pour la Science Ouverte (2018) Les enjeux de l'Open Data • enjeux patrimoniaux o preuve et mémoire (éviter les pertes de données) • enjeux économiques o valeur économique de la donnée o réutilisation gratuite ou payante des données, exploitation des résultats de recherches antérieures (éviter de refaire ce qui a déjà été validé), o accélération de l'innovation et le retour sur investissement dans la R&D • enjeux scientifiques o de "hypothesis-driven" à "data-driven" o plus de visibilité pour le scientifique • enjeux sociétaux o participation des citoyens et de la société civile : "Citizen science" o confiance en la recherche Pour aller plus loin • Site Doranum : https://doranum.fr/enjeux-benefices/fiche-synthetique/ • Adopter de bonnes pratiques tout au long du cycle de vie des données De bonnes pratiques de gestion à toutes les étapes du cycle de vie de la donnée sont un préalable indispensable à l’ouverture des données et à leur réutilisation. • Rechercher des données Pour identifier des jeux de données (datasets) pertinents pour votre thèse, des outils de recherche sont disponibles. Suivez ces liens pour les découvrir : • Site Doranum : https://doranum.fr/acces-visualisation/rechercher-donnees/ • Site DataCC - Vos besoins, trouver des données : https://www.datacc.org/vos-besoins/trouver-des-donnees/ • Fiche CoopIST : Trouver des jeux de données via des bases pluridisciplinaires et des moteurs de recherche Pensez-aussi à consulter l'entrepôt institutionnel Data INRAE Page de présentation du portail • Choisir les bons formats et bien organiser vos données  Choisir des formats de fichier : https://www6.inrae.fr/datapartage/Gerer/Choisir-des-formats-de-fichier  Nommer et organiser vos fichiers de données : https://www6.inrae.fr/datapartage/Gerer/Nommer-et-organiser-ses-fichiers-de-donnees Pour aller plus loin • Jaouen, G.- Gérer ses données. Pourquoi, Comment ? Séminaire - Guadeloupe, du 25 au 27 Novembre 2019 – CRAG INRA • Bien décrire et documenter ses données La description d’un jeu de données se fait à l’aide de métadonnées (*) qui doivent apporter suffisamment d'éléments (sur la collecte des données, les unités de mesure employées...) pour chercher et trouver le jeu de données, juger de sa qualité/fiabilité, et pouvoir le comprendre ou le réutiliser dans un autre contexte. (*) Définition des métadonnées : Ensemble d’informations structurées qui décrit, explicite, localise une ressource informationnelle, dans le but d’en faciliter la recherche, l’usage, et la gestion. Source : NISO. Understanding Metadata. 2004. Quelques liens utiles : • Site Doranum : https://doranum.fr/metadonnees-standards-formats/ • DataCC : https://www.datacc.org/vos-besoins/documenter-ses-donnees/metadonnees/ • Site DataPartage INRAE : https://www6.inrae.fr/datapartage/Gerer/Documenter-les-donnees En complément des métadonnées, la rédaction d'un fichier READ ME.txt est également recommandée. • Stocker, sécuriser, préserver ses données Bien différencier les notions de stockage et d'archivage. Anticiper pour déterminer les données à éliminer et celles qui doivent être préservées à long terme. • Dans l'environnement INRAE : https://www6.inrae.fr/datapartage/Gerer/Stocker-les-donnees • Site Doranum : https://doranum.fr/stockage-archivage/ • Site DataCC : https://www.datacc.org/vos-besoins/conserver-ses-donnees/ • Partager, ne pas partager ses données ? Dans le cadre de la Science Ouverte, il y a de plus en plus d'incitations voire d'exigences pour rendre accessibles les données, en particulier les données liées aux publications : • de l'édition scientifique : de plus en plus de revues adoptent une "data policy" (à consulter dans les instructions aux auteurs) et exigent des auteurs qu'ils fournissent les données associées aux publications, • des organismes de financement (ANR, Commission Européenne ...), • des politiques nationale (Plan national pour la Science ouverte - Ministère ESR - Juillet 2018) et institutionnelle. Mais attention, toutes les données ne sont pas partageables : assurez-vous que vos données sont bien diffusables au regard du droit et des conditions d'exercice de votre thèse et de son mode de financement (se reporter à votre contrat de thèse). Les données produites dans les organismes de recherche publics sont communicables à tous si elles n'entrent pas dans le cadre d'exceptions légales (sécurité défense, sécurité des populations, patrimoine scientifique et technique, données personnelles, données liées au secret, statistique, etc.) Liens utiles : • sur le site Data Partage, la page Partager-Publier ou la page : "Données de la recherche : qui a les droits, qui doit partager ?" • le site INRAE dédié à la protection des données personnelles et l'application du RGPD (Règlement général sur la protection des données) : https://intranet.inrae.fr/cil-dpo • Valoriser ses données Voici les principales voies de diffusion •  Partager ses données en les déposant dans un entrepôt  Choisir un entrepôt  Déposer dans Data INRAE  Partager ses données comme matériel supplémentaire d'un article (à la demande de l'éditeur)  Publier un Data Paper (article de données) : la meilleure voie en terme de visibilité des données, et pour faciliter leur réutilisation. Pour aller plus loin • Site Doranum o Dépôts et entrepôts. Comment et où déposer mes données ? o Data papers et Data journals. Comment publier mes données comme un article scientifique ? • Site DataCC o Valoriser ses données • Site CoopIST o Déposer des données de recherche dans un entrepôt o Rédiger et publier un data paper dans une revue scientifique A télécharger : Synthèse du processus de rédaction d'un article avec des données associées • Pourquoi ne pas rédiger un plan de gestion de données (PGD) pour votre thèse ? La thèse peut être assimilée à un projet et certaines universités au Royaume Uni, aux Pays-Bas et plus récemment en France préconisent la rédaction d'un plan de gestion associé à la thèse. Le PGD (ou DMP = Data Management Plan) est un outil de planification qui peut vous aider à anticiper et bien gérer toutes les étapes du cycle de vie de vos données, à limiter les risques de perte ou corruption de données, à adopter de bonnes pratiques de gestion, pour in fine produire des données respectueuses des principes FAIR, adoptés aujourd'hui par l'ensemble des acteurs de la recherche. Il est désormais exigé par la plupart des financeurs de la recherche (Commission Européenne et ANR ...) dans le cadre de projets financés. Rédiger un PGD pour votre thèse, peut être un bon exercice pour vous préparer à la future rédaction de réponses à des appels d'offre. Comment faire en pratique ? • Site DataPartage : Pourquoi et comment rédiger un plan de gestion de données ? • Site Doranum : https://doranum.fr/plan-gestion-donnees-dmp/, La minute vidéo PGD • Site DataCC : https://www.datacc.org/bonnes-pratiques/adopter-un-plan-de-gestion-des-donnees/ • Suivre une classe virtuelle INRAE : Open Class "Rédaction d'un PGD" • Produire des données FAIR ! Favoriser la production de données FAIR (Findable - Accessible - Interoperable - Reusable) est aujourd'hui un objectif soutenu par l'ensemble des acteurs de la recherche. Source : https://open-science-training-handbook.gitbook.io/book/ Si vous suivez les conseils et recommandations de cette page, vous avez toutes les chances d'avoir produit des données de qualité. Si vous préférez une version illustrée : "Pensez FAIR" - https://datapartage.inrae.fr/Gerer/Cycle-de-la-donnee Affiche cycle de vie des données réalisée dans le cadre des Missions QualiNous & RGPD, INRAE-ACT Vous pouvez tester le niveau de "Fairification" de vos données grâce à ces outils :  ARDC : https://ardc.edu.au/resources/working-with-data/fair-data/fair-self-assessment-tool • D'autres ressources pour se former ou s'autoformer En interne INRAE • Formation à la science ouverte OSCAR - Module "Gestion et partage des données" • Le site "Gestion et partage des données" • Des classes virtuelles d'environ 2h (Open Class) sont régulièrement proposées sur : o la rédaction des plans de gestion de données, o le dépôt et la description d'un jeu de données dans Data INRAE, o la rédaction et la publication de data papers, Sites externes • Le site DORANUM (Données de la Recherche : Apprentissage NUMérique à la gestion et au partage) propose un dispositif de formation à distance intégrant de nombreuses ressources d’auto-formation déclinées sur différents supports (textes, infographies, vidéos) et sur 9 thématiques. o Parcours interactif sur la gestion des données de la recherche (2020) o • Le site DataCC. Accompagnement à la gestion des données de recherche en physique et en chimie : https://www.datacc.org/ o Data Stories : https://www.datacc.org/reseau-datacc/data-stories/ o • Le dossier "Open Access & Open Data" réalisé par l'Ecole des Ponts - ParisTech • • The Open Science Training Handbook : https://www.ouvrirlascience.fr/the-open-science-training-handbook/

Q1. A teacher designs a lesson where students compute real-life percentages such as discounts and savings. 👉 A student calculates 15% of 200 to determine savings in a purchase. What is the correct result? A. 20 B. 25 C. 30 D. 35 Q2. In a classroom activity, learners compare numbers to find the highest common factor for grouping materials evenly. 👉 What is the GCF of 24 and 36? A. 6 B. 8 C. 12 D. 18 📘 FRACTIONS, DECIMALS, AND POWERS Q3. A learner converts fractions into percentages for data interpretation. 👉 What is 3/4 expressed as a percentage? A. 50% B. 60% C. 75% D. 80% Q4. A student models exponential growth using repeated multiplication. 👉 What is the value of 252^525? A. 25 B. 30 C. 32 D. 64 📘 ALGEBRA (EQUATIONS AND EXPRESSIONS) Q5. A teacher guides students to solve equations that represent real-life situations. 👉 Solve: 2x+8=202x + 8 = 202x+8=20 A. x = 4 B. x = 6 C. x = 8 D. x = 10 Q6. Students simplify expressions to understand relationships between quantities. 👉 Simplify: 3(x+4)−2x3(x + 4) - 2x3(x+4)−2x A. x + 12 B. x + 4 C. 5x + 4 D. 5x + 12 📘 FUNCTIONS AND GRAPHING Q7. A student analyzes a linear equation to determine its rate of change. 👉 What is the slope of y=3x−5y = 3x - 5y=3x−5? A. -5 B. -3 C. 3 D. 5 Q8. A learner evaluates functions to predict outcomes. 👉 If f(x)=2x+3f(x) = 2x + 3f(x)=2x+3, what is f(4)f(4)f(4)? A. 7 B. 9 C. 11 D. 14 📘 GEOMETRY Q9. Students explore geometric shapes and their properties through visual models. 👉 What is the sum of interior angles of a triangle? A. 90° B. 180° C. 270° D. 360° Q10. A student calculates the area of a classroom table with dimensions 8 cm by 5 cm. 👉 What is the area? A. 26 sq cm B. 30 sq cm C. 40 sq cm D. 48 sq cm 📘 MEASUREMENT AND FIGURES Q11. A learner determines the volume of a cube used in a science experiment. 👉 What is the volume of a cube with side 4 cm? A. 16 cubic cm B. 32 cubic cm C. 48 cubic cm D. 64 cubic cm Q12. Students identify shapes used in design projects. 👉 How many sides does a hexagon have? A. 5 B. 6 C. 7 D. 8 📘 STATISTICS AND PROBABILITY Q13. A teacher helps students interpret data sets using measures of central tendency. 👉 What is the mean of 4, 6, 8, 10, 12? A. 6 B. 8 C. 10 D. 12 Q14. A class experiment involves flipping a fair coin. 👉 What is the probability of getting heads? A. 1/4 B. 1/3 C. 1/2 D. 2/3 📘 WORD PROBLEMS (APPLICATION) Q15. A car travels 180 km in 3 hours during a learning task on speed. 👉 What is its average speed? A. 45 km/h B. 60 km/h C. 75 km/h D. 90 km/h Q16. Students analyze work efficiency in a project. 👉 If 5 workers complete a task in 12 days, how long will 10 workers take? A. 3 days B. 6 days C. 8 days D. 12 days Q17. A student solves a problem involving ratios in a classroom population. 👉 If the ratio of boys to girls is 3:2 and there are 30 students, how many boys are there? A. 12 B. 15 C. 18 D. 20 Q18. A learner determines the duration of a scheduled trip. 👉 A journey starts at 8:30 AM and ends at 11:15 AM. How long is the trip? A. 2 hrs 15 mins B. 2 hrs 30 mins C. 2 hrs 45 mins D. 3 hrs 15 mins Q19. A student computes simple interest for financial literacy. 👉 What is the simple interest on ₱1000 at 5% for 2 years? A. ₱50 B. ₱75 C. ₱100 D. ₱150 Q20. A learner solves a perimeter problem involving a rectangle. 👉 A rectangle has a length of 12 cm and perimeter of 34 cm. What is the width? A. 5 cm B. 7 cm C. 10 cm D. 11 cm ✅ ANSWER KEY (BASED ON YOUR REVIEWER) (All verified from your uploaded file) [ilide.info...002acd4e5a | PDF] QAnswer1C2C3C4C5B6A7C8C9B10C11D12B13B14C15B16B17C18C19C20A

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