You have seen that the net cost comparisons I prepare for this website only include cost and aid data for non-resident students at publicly funded schools, and I leave your in-state schools to you. But a couple years ago, I prepared cost and aid comparisons at both income levels for five universities within the University of California system, this time from the perspective of in-state families. In essence, I moved my sample families south and did their data as California residents, and the net cost variability among the five schools surprised even me. These five schools caught my eye as I reviewed the New York Times College Access Index for that year. I was struck by the fact that all five of the top colleges and universities in America, listed according to the percentage of their graduates who received Pell Grants, were universities in the University of California system. I think the Times included some pointless, "why-bother" data showing average aid at the schools. Why bother with averages when NPCs give you the real thing? So, I ran their NPC's for my sample families, and here are the results:
What a variance! And that's among five universities in the same university system. Obviously, UCLA was the most generous school - and UCSD the least generous school - at both income levels, but let's put your brand new expected-loan-calculation skills to work on these two schools. UCLA's Remaining Balance was approximately equal to the Expected Family Contribution at both incomes, resulting in no expected annual need for loans, and making it's expected loans over four years zero. UCSD's Remaining Balance, however, was about $6,000 over the EFC at both incomes, resulting in expected annual loans of $6,000, and making it's expected loans over four years about $24,000 resulting in loan payments of about $240 per month for ten years. Now, is that variance as glaring today as it was in 2016? I'm leaving that answer to you Californians. But does that table show the value for all American families of doing their own NPC data at their target schools? Absolutely!
A. THE ITALIAN VARIANT MOVES WEST
To illustrate what looks to me like the march of the Italian Covid-19 Variant from New York to California, I'd like you to look at the Daily Deaths graphs on each of the following webpages. This comparison will work best if you open each webpage as a separate tab in your browser so you can go back and forth. I'd also recommend that you use a larger screen device, because it might be difficult to click back and forth on your phones. By the way, I'm not providing screenshots of these graphs because, if you open them for yourselves, the data will automatically be updated to the moment you open each page.
You will need to scroll down to find the Daily Deaths graph on each webpage. And I think you'll find it helpful to then click on the "Seven-Day Moving Average" box below each graph to take the bumps out of the data.
For comparison purposes, let's start with Italy itself, the birthplace of the Italian Variant: https://www.worldometers.info/coronavirus/country/italy/ Scroll down to the Daily Deaths graph, click the Seven-Day Moving Average box, and take a look. That's the classic look of that graph with deaths climbing steeply, rounding over, and fading down a slope. That's what's supposed to happen with a single wave pandemic.
Now, let's check California's Daily Deaths curve: https://www.worldometers.info/coronavirus/usa/california/ Scroll down to the Daily Deaths graph, click the Seven-Day Moving Average box, and take a look. That's a mess, and that's what I think a Second Wave of a more deadly CV-19 variant would look like. You'll see that, matching New York, California's Daily Deaths reach a preliminary peak in late April and began to slope down. But, instead of continuing to trend lower, Daily Deaths stabilized and then began to trend up more steadily in July reaching a record level at the end of the month - 70 daily deaths higher on July 31 than the previous record on April 22. Where will it go from here? We'll just have to see. Now, let's look at Washington: https://www.worldometers.info/coronavirus/usa/washington/ Again we see the classic ramp-up and slope-down that we want to see, but the slope-down ended in June, and the trend has gone slowly upwards since then. Now, let's look at Idaho: https://www.worldometers.info/coronavirus/usa/idaho/
Good news? No. Good time to wear a mask? Yes, indeed.