Right, but no where on this infographic does it mention the federal inmates are ignored from the state statistics. The state graphic simply says “inmates”, it doesn’t specify that it is only a subset of inmates physically housed within each state. You can easily look up the number of federal inmates located within each state or even facility, so it isn’t impossible to find the information. OP didn’t even seem to realize the datasets were that different, so that’s likely why it wasn’t called out in the graphic (and also why it should’ve been, since it’s not clear at all).

Hmm, I’m not sure that fully explains the difference between the state level data and the national view. The nation was 629 “a few years earlier”, yet somehow the state average is around half of that. Did the country really reduce their total inmate population by ~50% in a few years?

Assuming the other country data remained the same over that same time span then the US would now be ranked ~20th globally rather than 1st. That seems like way too big of a difference to just be caused by a few years difference in the data.

As others have mentioned, is the state data ignoring federal prisons? Could they be defining populations in different ways? It’s tough connecting the two datasets without fully understanding why they are so different.

Sometimes it depends on what you consider an “interview”. There may be multiple stages of an application process where you are being evaluated, but you may not actually be sitting in a room or on the phone talking to someone directly. For example, my last internship while in university that ultimately led to my first “real job” looked like this:

1. Phone interview with recruiter
2. Online multiple-choice personality assessment
3. Recorded responses to on-the-fly questions
4. In-person competency test (Excel & SQL)
5. In-person case study
6. Presentation of test & case study answers
7. General interview with a panel of managers, HR, and a director

4-7 were all on the same day, but involved different focuses.

In the traditional sense, I only had 2 interviews where I was on the phone or sitting across from HR/managers answering questions about myself. Though this obviously involved many more steps than those 2 interviews. By another count there could be as many as 7 total steps or “interviews” taking place. Though they wouldn’t necessarily be able to drop me at any point, especially part way through steps 4-7 where they already walked me through what the day would look like.

It definitely seems excessive, though many of the highest paying positions include this length of process (whether truly necessary or not). I wouldn’t solely disqualify a company based on the number of interviews, especially if the position requiring the most work is likely the best offer, which I often find to be the case.

This varies immensely based on industry, role, experience, and even quality of application. If every one of these applications has a custom-tailored cover letter & resume, to a highly demanded position for which the applicant is well qualified for then you could see offers approach 50%. If on the other side of things the field is over saturated, the position has very few barriers to entry and therefore a high applicant pool, the applicant has very little relevant experience, and little effort was put into the resume/cover letter then you’d expect an almost 0% return.

That’s not even taking economic climate or local nuisances into consideration. I wouldn’t put much weight into the results of these without knowing the answers to a lot of the questions I posed.

Sorry bud, but a crudely coloured spreadsheet is not data viz. Nevermind beautiful data viz. No one even knows what the colours here mean. Less text, more visual, and a legend would all be a good start.

When it comes to nutrition there are general guidelines that are useful for most people. I like Michael Pollan’s advice:

> Eat (real) food. Not too much. Mostly plants.

Though no 1 diet is ideal for everyone and listening to your body can certainly help with this. I prefer to eat lower carb, which leads to my body retaining less water and by extension less salt with it. Additionally, I run & weight lift regularly which also increases my salt demands.

This means I need to intake more salt to keep my levels balanced and avoid fatigue or headaches. I eat very little processed food, so unless I’m going out of my way to add salt I’m not likely to get much in me just by consuming the food as is.

You may be more salt sensitive and thus reducing your salt intake may be the right choice for you, but not necessarily everyone else.

Do you have a pre-existing health condition or family history that would make you at higher risk of heart issues related to sodium intake? If not, then your sodium intake may not matter much.

> # Low Salt Intake May Not Reduce the Risk of Heart Disease or Death

> There is some evidence showing that high salt intake may be associated with an increased risk of certain conditions like stomach cancer or high blood pressure.

> Despite this, there are several studies showing that a reduced-salt diet may not actually decrease the risk of heart disease or death.

> A large 2011 review made up of seven studies found that salt reduction had no effect on the risk of heart disease or death (16Trusted Source).

> Another review with over 7,000 participants showed that reduced salt intake did not affect the risk of death and had only a weak association with the risk of heart disease (17Trusted Source).

> However, the effect of salt on the risk of heart disease and death may vary for certain groups.

> For example, one large study showed that a low-salt diet was associated with a reduced risk of death but only in overweight individuals (18Trusted Source).

> Meanwhile, another study actually found that a low-salt diet increased the risk of death by 159% in those with heart failure (19Trusted Source).

> Clearly, further research is needed to determine how decreasing salt intake may affect different populations.

> But it’s safe to say that reducing salt intake does not automatically decrease the risk of heart disease or death for everyone.

Edit: Salt and sugar are very different things. One is an addictive compound that provides no nutritional value beyond pure energy and the other is a non-caloric essential micronutrient necessary to sustain basic bodily functions and required in higher amounts for optimal performance, especially for athletes.

Using enough salt (and other seasonings) on foods, especially meat, and giving it sufficient time to soak in is a huge game changer. Simply putting some salt & pepper on your chicken breast and letting it sit in your fridge for 2-24hrs ahead of cooking will make a MASSIVE difference in how it tastes.

Edit: This applies moreso for even larger cuts of meat that require more salt and more time to fully absorb.

That’s how cooking works! Salt brings out the flavour in foods, almost everything needs to be salted at some point and it’s usually best to salt things earlier on rather than tossing some on at the end.

Most evidence actually suggests that girls choose to go into certain STEM roles at lower rates than men for a variety of reasons, most of which are NOT inherently biological and the “biological” reasons don’t present until much later in life after the other factors could already skew the results. Here are some excerpts from a meta analysis conducted on the topic.

> Successful careers in math and science require many types of cognitive abilities. Females tend to excel in verbal abilities, with large differences between females and males found when assessments include writing samples. High-level achievement in science and math requires the ability to communicate effectively and comprehend abstract ideas, so the female advantage in writing should be helpful in all academic domains. Males outperform females on most measures of visuospatial abilities, which have been implicated as contributing to sex differences on standardized exams in mathematics and science.

There are differences in performance between men and women for certain areas, though being a good SWE or other technical role requires a variety of skills, men generally perform better at one type and women generally perform better another. Anecdotally, as someone working in tech I find my female co-workers to be more organized and have better communication skills that make them easier to work with and often perform quality work more consistently.

> A wide range of sociocultural forces contribute to sex differences in mathematics and science achievement and ability—including the effects of family, neighborhood, peer, and school influences; training and experience; and cultural practices. We conclude that early experience, biological factors, educational policy, and cultural context affect the number of women and men who pursue advanced study in science and math and that these effects add and interact in complex ways. There are no single or simple answers to the complex questions about sex differences in science and mathematics.

If you read the above, 3 of the 4 categories contributing to the differences in STEM achievement are unrelated to biology. Meaning these differences are NOT generally “natural” as you incorrectly suggested. Early experience, such as being told you don’t have the ability to pursue STEM due to your “natural abilities” is one such influence that reduces performance and drives women away from the field. So literally the behaviour you’re exhibiting is a contributing factor to why your program has so many men and few women. Next time, stop being an ass and do some research before parroting harmful sexist ideas that are clearly NOT supported by the literature, or at very least don’t make up the majority of differences.

I don’t think people believe the accounting practices are shady per se. It’s more so that the system is broke if a company can generate 10s of billions in revenue AND profit while only paying a few % (1.5% of revenue in this case) in taxes. I don’t care what legal or illegal means are used to get there. They simply should be paying a much more substantial amount of their profits towards the government and therefore society at large. Especially in a case where some these companies are causing tremendous harm like many pharmaceutical companies today.

Ok, so are you suggesting they pay more than this to the IRS? If so, how would we find THAT number? And I’m still not seeing how this is “good” for society at large.

Wait, how does employee compensation make their taxes negligible and why is this good?

I would rebuttal this point a bit, since eliminating an axis and replacing it with labels directly on the data points can be an example of improving the data-ink ratio of a data viz, which is generally regarded as a positive in the field.

Edit: Obviously eliminating the axis and having 0 labeling is a no no since the values need to be specified.