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Tag Archives: charts and graphs

How do you tell a story with data and maps – Beto vs Cruz?

FiveThirtyEight has an excellent article on the 2018 senate race and the possible implications for future elections. The article, What Really Happened In Texas by Kirk Goldsberry (11/14/18) analyzes voting patterns by county and compares 2014 to 2018.  Their graph copied here is the fourth in a series of maps and mostly summarizes the previous maps.

Cruz won by 220,000 votes last week. But in Harris County alone, 500,000 more people voted in the 2018 midterms than had voted in 2014. In Dallas County, 300,000 more people voted than in the last midterms, and in Travis, Bexar and Tarrant counties, 200,000 more people voted.

Indeed, aside from some noteworthy increase in voter numbers in suburban Dallas, the biggest white circles on the map above tend to hover over Beto country. Meanwhile, the darkest red counties — the places that carried Cruz back to Washington — have exhibited very little, if any, change in the number of votes cast compared to 2014. Those areas may be staunchly red, but they’re also staunchly stagnant too. O’Rourke almost won in 2018 by taking roughly 60 percent of the vote in the big five counties. This map suggests that if Democrats can repeat that feat as these places continue to grow, that may be all they need to turn Texas blue.

The data for their analysis comes from the Texas Secretary of State election results.  The 2014 data is available by following the Historical Election Results (1992-current) link. The 2018 data is available through a link along the top. This is a stats project in the making (do this for you home state). The article can also  be used in a QL course.

How does the digital divide impact secondary education for different groups?

The Pew Research Center article Nearly one-in-five teens can’t always finish their homework because of the digital divide by Monica Anderson and Andrew Perrin (10/26/18) provides insights on how lacking access to the internet impacts the ability to complete homework.  Their chart (copied here) gives the percent of school-age children by race and income without high-speed internet.  A second chart provides the results of survey about how this impacts homework. In particular,

One-quarter of black teens say they are at least sometimes unable to complete their homework due to a lack of digital access, including 13% who say this happens to them often. Just 4% of white teens and 6% of Hispanic teens say this often happens to them. (There were not enough Asian respondents in this survey sample to be broken out into a separate analysis.)

The article includes a link at the bottom for results and methodology. This includes sample sizes making this article particularly useful for statistics courses.

What is the relationship between rates of suspension by race and free and reduced lunch?

Propublica’s article, Miseducation – Is There Racial Inequality at Your School? by  Lena V. Groeger, Annie Waldman and David Eads, (10/16/18), provides data by state on the percent of nonwhite students, the percent of students who get free/reduced-price lunch, high school graduation rate, the number of times White students are likely to be in an AP class as compared to Black students, and the number of times Black students are likely to be suspended as compared to White students. The comparison is also available for Hispanic students.

The graph here was created with their data and compares the percent of students on free and reduced lunch with the number of times Black students are likely to be suspended  compared to White students (state data isn’t available for HI, ID, MT, NH, NM, OR, UT, or WY).  The red lines uses all the data where as the blue line removes the outliers of DC and ND. The blue regression line has a p-value of 0.012 and R-squared of 0.15.  This suggests that wealthier states, as measured by free and reduced lunch programs, have a greater disparity is suspensions between black and white students. The impact of outliers is instructive here and there are other scatter plots worth graphing from the article. There are also statistics projects waiting to be created with this data.

The article also has an interactive map or racial disparities by districts, but the map can be misleading based on missing data from districts. Can you see how?  This makes the map itself useful for QL courses.  R Script that created this graph. Companion csv file.

How much have child and adolescent mortality rates changed?

The World Bank report, New child and adolescent mortality estimates show remarkable progress, but 17,000 children under 15 still died every day in 2017, by Emi Suzuki and co-author Haruna Kashiwase ( 9/18/18) provides a summary, as well as a number of charts. The good news:

There has been remarkable progress in reducing mortality among children and young adolescents in the past several decades. Between 1990 and 2017, the global under-five mortality rate dropped by 58 percent from 93 deaths per 1,000 live births to 39 deaths per 1,000 live births. During the last 17 years, the reduction in under-five mortality rates accelerated to an average 4% annual reduction, compared to an average 1.9% annual reduction between 1990 and 2000. For children aged 5-14, mortality dropped by 53 percent, from 15 deaths to 7 deaths per 1,000 children.

At the same time there is work to be done:

However, while a substantial reduction from the 14.3 million in 1990, an estimated 6.3 million children under age 15 still died in 2017, mostly from preventable causes.

The charts on the page are interactive but can’t be downloaded. On the other hand, the data is easily available and charts can be made for download. The chart here was made at the World Bank’s DataBank.  Note that the European Union has a lower under 5 mortality rate than the U.S. There are numerous variables to choose. Data can be downloaded and charts for download can be highly customized.

How much have fall temperatures risen?

According to the Climate Central post, Fall Warming Trends Across the U.S. (9/5/18), the average fall temperature for the U.S. has risen nearly 3°F since 1970 (see their graph copied here).  Why does this matter:

Insects linger longer into the fall when the first freeze of the season comes later in the year. A new study from the Universities of Washington and Colorado indicates that for every degree (Celsius) of warming, global yields of corn, rice, and wheat would decline 10 to 25 percent from the increase in insects. Those losses are expected to be worst in North America and Europe.

The article has a drop down menu to select cities across the U.S. to see a graph similar to the one copied here for the selected city.  They don’t post the data that was used to create the graphs but they do explain their data sources under methodology.

A statistics project could have students create this graph for their hometown.  One way to obtain the data was noted in our post, What do we know about nighttime minimum temperatures?: Go to  NOAA’s Local Climatological Data Map. Click on the wrench under Layers. Use the rectangle tool to select your local weather station. Check off the station and Add to Cart. Follow the direction from their being sure to select csv file. You will get an email link for the data within a day.  Note: You are limited in the size of the data to ten year periods. You will need to do this more than once to get the full data set available for your station.

 

 

What do we know about plastics?

The Our World in Data article Plastic Pollution by Hannah Ritchie and Max Roser (Sept 2018) is a detailed summary of plastics with 20 charts.  For example, one of the charts is a time series of plastic production (downloaded and posted here) showing that, in 2015, the world produced 381 million tons of plastic. In the same year, only 20% of the plastic was recycled (second chart in the article).  There is information on plastic waste generation.

Packaging, for example, has a very short ‘in-use’ lifetime (typically around 6 months or less). This is in contrast to building and construction, where plastic use has a mean lifetime of 35 years.7 Packaging is therefore the dominant generator of plastic waste, responsible for almost half of the global total.

Who produces the most plastic waste?

… we see the per capita rate of plastic waste generation, measured in kilograms per person per day. Here we see differences of around an order of magnitude: daily per capita plastic waste across the highest countries – Kuwait, Guyana, Germany, Netherlands, Ireland, the United States – is more than ten times higher than across many countries such as India, Tanzania, Mozambique and Bangladesh.

As always with Our World in Data, the data associated with each graph is downloadable.

How many 90+ degree days will your hometown have in the future?

The New York Times interactive article How Much Hotter Is Your Hometown Than When You Were Born? By Nadja Popovich, Blacki Migliozzi, Rumsey Taylor, Josh Williams and Derek Watkins, allows the reader to input a birth year and hometown and provides a graph with historical 90+ degree days and predictions for the future. For example a person born in 1970 in NYC would get the graph copied here.  In 1970 the expectation was six 90+ degree days, today it is 11, and by 2050 it will be 24 with a likely range of 15 to 30.

THE NEW YORK AREA is likely to feel this extra heat even if countries take action to lower their emissions by the end of the century, according to an analysis conducted for The New York Times by the Climate Impact Lab, a group of climate scientists, economists and data analysts from the Rhodium Group, the University of Chicago, Rutgers University and the University of California, Berkeley. If countries continue emitting at historically high rates, the future could look even hotter.

The future projection shown here assumes countries will curb greenhouse gas emissions roughly in line with the world’s original Paris Agreement pledges (although most countries do not appear on track to meet those pledges).

There are related human health impacts:

Worldwide, high temperatures have been found to increase the risk of illness and death, especially among older people, infants and people with chronic medical conditions. Lower-income populations, which more often lack access to air conditioning and other adaptive technologies, are also more likely to suffer the impacts of extreme heat. In America, so are people of color.

The article has other graphs and quantitative information which can be used in  QL based course.

How distracting are cell phones?

The extensive article by Pew Research, How Teens and Parents Navigate Screen Time and Device Distractions by Jingjing Jiang (8/22/18), presents detailed data on cell phone use.  For example,

And 51% of teens say they often or sometimes find their parent or caregiver to be distracted by their own cellphone when they are trying to have a conversation with them.

As they look at their own lives and those of their peers, most teens see things that worry them. Roughly nine-in-ten teens view spending too much time online as a problem facing people their age, including 60% who say it is a major problem.

The article has eight charts, one of which is reposted here.  There is a complete methodology section, which is perfect for a stats class, with enough information to use the data for statistical tests.

Where are women less likely than men (ages 30-70) to die of a major disease?

The Our World in Data post, Why do women live longer than men?  by Esteban Ortiz-Ospina and Diana Beltekian (8/14/18) answers the question with the graph copied here.

As the next chart shows, in most countries for all the primary causes of death the mortality rates are higher for men. More detailed data shows that this is true at all ages; yet paradoxically, while women have lower mortality rates throughout their life, they also often have higher rates of physical illness, more disability days, more doctor visits, and hospital stays than men do. It seems women do not live longer than men only because they age more slowly, but also because they are more robust when they get sick at any age. This is an interesting point that still needs more research.

Interestingly, it seems that  except for Bhutan it is only countries in Africa where women are more likely to die of a major disease.  The article is an excellent example of telling a story with data while also posing questions.

The evidence shows that differences in chromosomes and hormones between men and women affect longevity. For example, males tend to have more fat surrounding the organs (they have more ‘visceral fat’) whereas women tend to have more fat sitting directly under the skin (‘subcutaneous fat’). This difference is determined both by estrogen and the presence of the second X chromosome in females; and it matters for longevity because fat surrounding the organs predicts cardiovascular disease.

But biological differences can only be part of the story – otherwise we’d not see such large differences across countries and over time. What else could be going on?

The article has three other graphs beyond this one. One compares life expectancy by country for women and men, one for life expectancy for men and women in the U.S. (and three other countries that can be selected) since 1790, and one for the difference in life expectancy at age 45 since 1790 for selected countries.  All graph can be downloaded  and the data is available for each.

How does the U.S. use its land?

Bloomberg: https://tinyurl.com/yaq3mp7m

The Bloomberg article Here’s How America Uses Its Land by Dave Merrill and Lauren Leatherby (7/31/2018). The article arrives at the graph copied here and it is worth scrolling through the article to see the graphs along the way with associated facts.

More than one-third of U.S. land is used for pasture—by far the largest land-use type in the contiguous 48 states. And nearly 25 percent of that land is administered by the federal government, with most occurring in the West. That land is open to grazing for a fee.

In exploring the graph it is interesting to note that maple syrup, highways, and golf courses, are categories big enough to be represented. Also note how much space is for cows. The article has potential to be used in a QL based course.