Coefficient Of Determination Puns

For example, a data set can have a regression model based on either power curve or log curve. Why is it inappropriate to see which curve will fit better by comparing their R^2 values?

Thanks in advance

It took me a while to figure out that correlation (r) can be found by taking the root of R^2 since they are apparently r and R are the same thing? I know this is a really simple question but I haven't found an answer yet and I was hoping someone could give me a quick explanation!

I was instructed to write an SOP for the determination of molar absorbance coefficient of Lysozyme, based on similar lab practicals we have previously performed (Determination of molar absorbance coefficient of methylene blue) but the problem is, we were already provided with a stock of methylene blue, were told exactly what wavelength to measure it in, how many ml of water it was disolved in, and it's molecular weight.

The only helpful thing we were told is to use the chemical manufacturers site for information, which helped a little bit I must admit.

 

Lets assume I have access to the lyophilized powder of human lysozyme, where do I go on from here if I wanna determine the molar absorbant coefficient? If anybody can provide me with a direction I would be forever grateful.

I would like to determine these values in order to validate my CFD results

I know this probably sounds really basic, but I am confused about how to determine a numerical coefficient when the variable is in the numerator of a fraction.

For "x/-2" - Would the coefficient be -1/2 or 1?

Thank you for your help!

Hi guys, so I'm super stuck on a homework question that asks to use Undetermined coefficients to find the general solution of:

y''+y=2tcos(t)

After attempting to find the particular solution, I notice that everything ends up cancelling out, so I'm left with 0 = 2tcos(t) which is not true.

Any help is much appreciated

hello,

i have 10 conditions that affects the complexity of a certain task, i'm looking for a way to "weight" the importance of each condition to determine the combined affect of all tasks on the time spent on the task (that means the output of the problem is a relation between the conditions and the time spent on the task)

i do have 1000 data line of tasks with their respective time noted in an excel sheet,

the problem seems to refer to deep learning algorithms but i'm looking for an excel tool that may help me determine (with a marge of error) the coefficients/weights of these conditions

thank you all in advance,

EDIT : adding a photo showing the input data of the problem ( https://ibb.co/m04R6o )

Goal : forecast the hour spend on a future task

Link to Statistics.

Base AD Ranked: 8th lowest > 2nd Lowest

AD growth Ranked: 29th (using lowest of Rank of Champions with 3AD) > 5th lowest.

AD Value at lvl18 Ranked: 21st > 3rd.

The last time Sona was 'actually' Buffed was in Patch 8.9, Base attack & power chord damage were increased . Before that, she had mini reworked buffed in 6.14 which was the last time there was a pleasant healthy change. Buffs otherwise from then to now have been buffs into gutted nerfs.

Personally I dont like the intent of the new "buff to Sona support" as it's pretty much a bandage to cover the inconsistency issues of top lane.

For various reasons I need to stratify my models. My fit statistics show that negative binomial is the more appropriate model due to overdispersion. When running the negative binomial the estimate for the non-stratified data is 1.8 but the estimates for the models stratified by gender are males: 1.7 and females: 1.6. This is because (as I understand) each negative binomial regression model has a different dispersion parameter. What would you suggest in this scenario? Relative comparability between multiple different models from the same dataset, with different levels of stratification, is essential.

I don't know where to go for starting heat transfer coefficients (convective and contacts specifically). It's been a couple years since I sold my heat transfer books.

One set of variables I would like in particular are the contacts between components. Currently we are just using bonded contact, and I know that's a bit of stretch. A resource with some ranges for different contacts between different materials would be great.

If anyone has a resource they can recommend I would greatly appreciate it! A book on amazon perhaps?

Dyatlov uses this phrase to emphasize that discussion about the positive void coefficient should be focused on its magnitude, not on it being positive.

>Both in the INSAG experts’ report and in other documents there is mention of the void coefficient of reactivity, whereas what should have been mentioned is the void coefficient of inadmissible magnitude. It turns out that after the accident at the Leningrad power station in 1975, the Scientific and Technical Council of the Ministry took a decision to set this at no more than 0.5%, a fact which the creators of the reactor “successfully managed” to forget. They were quite happy with the calculated curve 1 in Fig II-12 of INSAG-7 Annex II (curve 1 of Figure 3 in this article).

The RBMK reactor: dependence of the reactivity level p on the coolant density y. 1: design calculations; 2: actual dependence at the time when the accident occurred on 26 April 1986; 3: current status after improvements.

>Curve 2 of Figure 3 is shown in INSAG-7 as the actual dependence at the same time of the accident on 26 April. This is a Jesuitical approach – neither a lie nor the truth. A similar void effect existed at all RBMK reactors, and not only on 26 April. The curve was obtained several years prior to the accident by an employee of the Kurchatov Institute, V. Ivanov, and was subsequently confirmed by measurements. The administration did not believe Ivanov. They understood that an explosion threatened, but they did not check this out either by calculation or by experiment. So there you have it. One might ask why Ivanov did not squeal? Only one person squealed, and that was V. I. Volkov, who was quickly disposed of with an invalidity pension.

Page 37 of INSAG-7:

>The Scientific Manager and Chief Design Engineer of the RBMK-1000 reactor determined the dependence of reactor reactivity on coolant density in the core using calculation codes in order to analyse the development of the design basis accident (DBA). The DBA considered in the design was a rupture in the pressure header of the multipass forced circulation circuit (MFCC) resulting in the loss of the water and steam phases of the core coolant. According to the calculated depend

Sorry, I think I meant to say GDP per capita divided by median income.

Ok, so I am currently building a flight computer simulation using the Unity Engine and need to calculate how much lift is applied with my aircraft. Problem is, I have searched everywhere and the only non-lift necessary equation I could find was 2pi*AngleOfAttack, which only works at small angles. If anyone knows of a formula for this that would be very appreciated

I'm sorry to berate this subreddit with more questions, but I have learned a lot from everyone here and would like to say thanks in advance.

Statistics really aren't my thing; please, r/cheatatmathhomework, you're my only hope!

So question 1)

Suppose that a federal agency wants to check the temperature of region A has the same variability as the temperature in region B. Towards this, a sample of 11 temperature readings were selected from random from region A and a sample of 16 readings were selected at random from region B. Region A is 7.3, Region 7.7. a) What is the observed value of the test statistic? b) what is the critical value at 5% significance level?

For this question, I've consulted my textbook and found the null hypothesis.

H0: P1 = P2, P1-P2 = 0 H1: P1 =/= P2, P1-P2 =/= 0

Outside of this, I'm pretty much lost completely.

question 2)

Suppose that we have information about the bank lending interest rate (x) and the unemployment rate (y) in percentage. x = 11, 12.2, 14.6, 15.3, 16.7, 18.2 y = 4.2, 4.4, 4.7, 5.2, 5.5, 6

a) complete the correlation coefficient R b) construct a 95% confidence interval for the population-based coefficient P

I think I can do a, though the equation is wayyyy to difficult to type out. I have no idea how to approach b.

Thanks a bunch everybody! I appreciate it!

EDIT: Figured out how to do 2a after tinkering around a bit!

Hoping to get some clarification here:

1. So the slope coefficient tells us how much Y changes for a 1 unit change of X, but it doesn't tell us the importance of X in explaing Y. Why is that?

2. The solution is to use a t-test to see if the slope coefficient=0, but we are given a slope coefficent from the regression. What is the purpose of the test then? Is it because we've estimated the slope so we are testing to see how certain we are that the true slope isnt zero?

3. What does a slope of 0 imply? Intuitivley an increase in X has no effect on Y, so X has zero predictive power in Y...

So at Formula North I was curious of what general range teams are sitting at downforce wise, so I asked them. Here's what resulted from that:
https://i.imgur.com/PMgovV2.png

Note that these values came from a mixture of good and bad CFD and validation. Some teams provided suspiciously rough numbers like 350 [lbf] @ 60 [mph], others gave rough numbers off the top of their head, others didn't have an aero guy to represent their aero.

It averages to a value of 3.03, with the lowest being 1.9, and the highest being somewhere in the 5.4-5.9 range.

Ask me about the specifics of this situation if you would like to be more sure before you answer. This is yet another poll I am making out of pure curiosity following the recent posts around the subject and to find out for myself. I would like to see some discussion as well so I have flaired this post as such.

View Poll

I would like to determine these values in order to validate my CFD results

According to many sources [1], the void coefficient of the RBMK-reactor depends on the fuel encirchement/burnup of the nuclear fuel, the control rod insertion and additional absorbers. I would like to understand this dependency better. Below is my reasoning and understanding so far:

The water in the RBMK-reactor has the following relation to the fission rate:
i) Water absorbs a share of the crossing neutrons, which then cannot fission other atoms.
ii) Water slows down (moderates) a share of the neutrons, which allows them to fission other atoms.

Because the reactor is graphite moderated, water is not necessarily needed as a moderator. Its effect on the fission rate depends on the relative magnitude of i) and ii): If the water acts more as an absorber than as a moderator, its effect on the fission rate is negative, resulting in a positive void coefficient. Reduced water density (e.g. due to steam bubbles) will drive power up. If the water acts more as a moderator than an absorber, you get a negative void coefficient. Reduced water density will reduce power.
But to me it seems that the relative effect of i) and ii) is not altered by fuel enrichement and control rod insertion, as it is a function of the material (water) and its temperature. So why then does it nevertheless depend on those factors?

Thanks in advance for any explanations!

[1] E.g. INSAG 7, p3: https://www-pub.iaea.org/MTCD/publications/PDF/Pub913e_web.pdf