danaleeling

Monday opened with the usual weather sites and terminology coverage. The Nissan made a return to the parking lot for the first time this term  The climate change playlist was updated with an altered focus. A new Curiosity Stream video on the environmental effects of climate change led the list. That was followed by a recent documentary, Inside Vanuatu : A country being lost to rising levels by channel 4 news. The video was told from the point of view of 24-year-old Grace Malie, a Rising Nations Initiative youth delegate for Tuvalu. I felt that this video would connect better than the usual string of science videos. I then let a pre-existing video in the list wrap up with a report on record breaking heat.  This term a new song titled Clouds led off the Thursday clouds playlist . Another new addition was a recent StarTalk video on clouds that was used to preface the 8:00 AM class, essentially a stall to buy time for other students to arrive as the v

I went with the light blue marbles for no particular reason. Although the mean for the marbles is typically between 5.1 and 5.2 grams, a split based on that yielded too few heavy marbles. The light blue marbles split roughly 27 light and 24 heavy on a split between 5.0 and 5.1. Marbles 5.0 or lighter on one side 5.1 or heavier on the other. Spring term I excluded 5.0 and 5.1 marbles, but that also necessitated using a mix of colors. And that eliminated the finding that students might be able to detect differences of 0.1 grams. Spring term had a very small sample size which actually proved educational as the seventh student stopped the p-value below 0.05. That said, the spring term also came within one pair of a 100% success rate which would be too good a result in some sense. I want something that has a sense that random luck achieved whatever result was obtained.  At 13 students the p-value was 0.09 and we failed to reject the null hypothesis. Two

 The 9.2 paper aircraft distances data and 10.1 Fibobelly data powered both 10.2 and 10.3.  Paper aircraft distances data in Desmos Desmos was used alongside the spreadsheets to convey the concepts in 10.2 and 10.3. Fibobelly data Class began with the water in a jar demonstration. A couple students knew that the water would not fall out. But most were surprised. The article  Antidepressants or running therapy : Comparing effects on mental and physical health in patients with depression and anxiety disorders provided an example of a modern study that includes both p-values and Cohen's effect size d. The study is a nice example where failing to reject the null hypothesis (antidepressants: 44.8 %; running: 43.3 %; p = .881) was a successful result.

Sunny warm weather with no rain all day meant an outside class. One pregnancy under a tropical sun and high humidity along with one student with a foot injury from stepping on glass meant a short walk. I present the presentation on leaf shapes to the class and carried the Tripltek, but the daylight was really too bright for the Tripltek.  I looked to gain the most coverage in the minimum of distance. So across the road we went to the Hibiscus tiliaceus, Glochidion ramiflorum, Cordyline fruticosa, and Macaranga carolinensis. I could not juggle the leaves, the lecture, and the Tripltek all in the field. So that did not work as well as I hoped. I think I might have gotten away with it if I knew the actual order I would hit the leaf shapes in. I needed cordate, linear, deltoid-orbicular peltate, elliptical in roughly that order. The leaf shapes are currently alphabetical which did not work at all in the bright sunshine. Too, the Tripltek has no range on the WiFi, s

This term I opened with a playlist on rocks and minerals followed by a presentation on the use of AI to interpret images including images of rocks. Something about the introduction stretched the laboratory to a full three hours, with one student finishing after five hours.  At the very start I again covered RMSE zero errors. Students still are not realizing that when they obtain an RMSE zero analysis that an error has occurred. Then followed the playlist and the present. Emylia, Sucie, Kapualani  My guess is that the up front emphasis on using AI apps to make identifications drove identifying each and every rock. In prior terms students struggled to make identifications from images of rocks collections and simply have up identifying the rocks. Mirabella, Darsen  Brian. The 8:00 section got off to a late start, not getting started until around 8:30. Students only really began working on identifications around 9:30, perhaps in

 The angiosperm presentation was expanded to include taxonomy. This included an overview of taxonomic levels and a look at a number of plant families. With the additional material and the explanation of the assignment, the class went to 16:30.

 This term a revised Desmos provided a visualization of the experiment. A new set of header variables and changes in the functions below automatically generate the graphic.  Desmos Spreadsheet This term I stumbled into the FORMULATEXT function which generates an automatic reporting of the functions in use. The dynamically updating calculations is also displayed.  The new population mean is now 556.61 or 557 cm.  An explainer shared to the online students: Today the residential class threw 18 paper airplanes from the second floor of the A building on the national campus. The 18 airplanes were predicted to fly an average of 556 cm away from the building based on a pre-existing known population mean flight distance. This population mean was based on 868 aircraft thrown during 44 prior terms back to 2012. The aircraft flew a sample mean distance of 607 cm with a sample standard deviation of 514 cm. The standard error of the mean was 121 cm. With a t-critical of 2.110 [=TINV(0.05,18-1)], th

Students were given samples of five marbles each. Each sample generated a sample mean for the marble masses. The class as a whole acted as the population.  I arrived early and passed out marbles as students entered. I opted to play Wintergatan to open the session. Spreadsheet As in prior terms I did not preload names, entering them on the fly. I handled all data entry from the tablet. Ten students each had five marbles. Treating the 50 marbles as the population allowed calculation of the population mean. Using Cathleen's sample as an example sample (a function captures the name of the second student) yields a sample mean that is different from the known population mean. Yet that is the best estimate of the population mean if the population mean is unknown. Which is usually the case.  Cathleen's sample standard deviation is less that the population standard deviation (technically the spreadsheet is displaying STDEV not STDEVP, but