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413 andrew gelman stats-2010-11-14-Statistics of food consumption


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Introduction: Visual Economics shows statistics on average food consumption in America: My brief feedback is that water is confounded with these results. They should have subtracted water content from the weight of all dietary items, as it inflates the proportion of milk, vegetable and fruit items that contain more water. They did that for soda (which is represented as sugar/corn syrup), amplifying the inconsistency. Time Magazine had a beautiful gallery that visualizes diets around the world in a more appealing way.


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1 Visual Economics shows statistics on average food consumption in America: My brief feedback is that water is confounded with these results. [sent-1, score-1.386]

2 They should have subtracted water content from the weight of all dietary items, as it inflates the proportion of milk, vegetable and fruit items that contain more water. [sent-2, score-1.838]

3 They did that for soda (which is represented as sugar/corn syrup), amplifying the inconsistency. [sent-3, score-0.403]

4 Time Magazine had a beautiful gallery that visualizes diets around the world in a more appealing way. [sent-4, score-0.921]


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Introduction: Visual Economics shows statistics on average food consumption in America: My brief feedback is that water is confounded with these results. They should have subtracted water content from the weight of all dietary items, as it inflates the proportion of milk, vegetable and fruit items that contain more water. They did that for soda (which is represented as sugar/corn syrup), amplifying the inconsistency. Time Magazine had a beautiful gallery that visualizes diets around the world in a more appealing way.

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Introduction: Kaiser writes thoughtfully about the costs, benefits, and incentives for different policy recommendation options regarding a recent water crisis. Good stuff: it’s solid “freakonomics”–and I mean this in positive way: a mix of economic and statistical analysis, with assumptions stated clearly. Kaiser writes: Using the framework from Chapter 4, we should think about the incentives facing the Mass. Water Resources Authority: A false positive error (people asked to throw out water when water is clean) means people stop drinking tap water temporarily, perhaps switching to bottled water, and the officials claim victory when no one falls sick, and businesses that produce bottled water experience a jump in sales. It is also very difficult to prove a “false positive” when people have stopped drinking the water. So this type of error is easy to hide behind. A false negative error (people told it’s safe to drink water when water is polluted) becomes apparent when someone falls sick

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Introduction: In the inbox today, under the header, “Hidden Costs behind Milk & Dairy Consumption (video)”: Hey Professor Gelman, Our site’s production team recently released a short video uncovering the local and global impact that milk has on our lives. After spending some time on your posts, I noticed you talked about dairy products and milk so I thought I’d email you. Are you the correct person to contact in regards to the content on the site? If so, let me know if you’re interested in checking out the video. Thanks, Emily S. Hmmm . . . I guess I do talk a lot about dairy products and milk on this site!

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Introduction: Bernard Phiri writes: I am relatively new to glm models, anyhow, I am currently using your book “Data analysis using regression and multilevel/hierarchical models” (pages 109-115). I am using a Poisson GLM model to analyse an aerial census dataset of wild herbivores on a ranch in Kenya. In my analysis I have the following variables: 1. Outcome variable: count of wild herbivores sighted at a given location 2. Explanatory variable1: vegetation type i.e. type of vegetation of the grid in which animals were sighted (the ranch is divided into 1x1km grids) 3. Explanatory variable2: animal species e.g. eland, elephant, zebra etc 4. Exposure: proximity to water i.e. distance (km) to the nearest water point My questions are as follows: 1. Am I correct to include proximity to water point as an offset? I notice that in the example in your book the offset is a count, does this matter? 2. By including proximity to water in the model as an exposure am I correct to interpret th

5 0.12490685 179 andrew gelman stats-2010-08-03-An Olympic size swimming pool full of lithium water

Introduction: As part of his continuing plan to sap etc etc., Aleks pointed me to an article by Max Miller reporting on a recommendation from Jacob Appel: Adding trace amounts of lithium to the drinking water could limit suicides. . . . Communities with higher than average amounts of lithium in their drinking water had significantly lower suicide rates than communities with lower levels. Regions of Texas with lower lithium concentrations had an average suicide rate of 14.2 per 100,000 people, whereas those areas with naturally higher lithium levels had a dramatically lower suicide rate of 8.7 per 100,000. The highest levels in Texas (150 micrograms of lithium per liter of water) are only a thousandth of the minimum pharmaceutical dose, and have no known deleterious effects. I don’t know anything about this and am offering no judgment on it; I’m just passing it on. The research studies are here and here . I am skeptical, though, about this part of the argument: We are not talking a

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Introduction: Visual Economics shows statistics on average food consumption in America: My brief feedback is that water is confounded with these results. They should have subtracted water content from the weight of all dietary items, as it inflates the proportion of milk, vegetable and fruit items that contain more water. They did that for soda (which is represented as sugar/corn syrup), amplifying the inconsistency. Time Magazine had a beautiful gallery that visualizes diets around the world in a more appealing way.

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Introduction: Paul Alper writes: For years I [Alper] have been obsessed by the color of the line which divides oncoming (i.e., opposing) traffic because I was firmly convinced that the color of the center line changed during my lifetime. Yet, I never could find anyone who had the same remembrance (or interest in the topic). The other day I found this this explanation that vindicates my recollection (and I was continuously out of the U.S. from 1969 to 1973): The question of which color to use for highway center lines in the United States enjoyed considerable debate and changing standards over a period of several decades. By November 1954, 47 states had adopted white as their standard color for highway centerlines, with Oregon being the last holdout to use yellow. In 1958, the U.S. Bureau of Public Roads adopted white as the standard color for the new interstate highway system. The 1971 edition of the Manual on Uniform Traffic Control Devices, however, mandated yellow as the standard color o

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Introduction: Image via Wikipedia Robert Zubrin writes in “How Much Is an Astronaut’s Life Worth?” ( Reason , Feb 2012 ): …policy analyst John D. Graham and his colleagues at the Harvard Center for Risk Analysis found in 1997 that the median cost for lifesaving expenditures and regulations by the U.S. government in the health care, residential, transportation, and occupational areas ranges from about $1 million to $3 million spent per life saved in today’s dollars. The only marked exception to this pattern occurs in the area of environmental health protection (such as the Superfund program) which costs about $200 million per life saved. Graham and his colleagues call the latter kind of inefficiency “ statistical murder ,” since thousands of additional lives could be saved each year if the money were used more cost-effectively. To avoid such deadly waste, the Department of Transportation has a policy of rejecting any proposed safety expenditure that costs more than $3

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Introduction: Visual Economics shows statistics on average food consumption in America: My brief feedback is that water is confounded with these results. They should have subtracted water content from the weight of all dietary items, as it inflates the proportion of milk, vegetable and fruit items that contain more water. They did that for soda (which is represented as sugar/corn syrup), amplifying the inconsistency. Time Magazine had a beautiful gallery that visualizes diets around the world in a more appealing way.

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