I don't really know the word for it, but I've got an extremely active learning style; classes just don't really work for me. Which is why, unfortunately, I did the least I had to in mathematics to graduate from all levels. Unfortunately, I could grasp concepts rather easily, which, in itself was part of the problem. I found this incredibly boring. I say this because once the concept was understood, it seemed like the teacher would then drone on about it for another 30 minutes and then make us do about 300 problems, with variations of the same thing over and over and over and over, for weeks and weeks on end, until any possible love for the subject was beaten out of me.

I am not blaming the teachers - I just have a style that doesn't really fit well with classes. As an impossible? bucket list thing, I just very much want to speak the language of Calculus. Is there any kind of resource anyone can imagine would help? I took Trig. I hated it at the time because of the above issue. If it had been about puzzles? Oh, I loved it. It was about repetition. I don't know that I am any good with that. I like exploration, not repetition. Which is why this may be hopeless. If it is, please be as kind as reddit can allow.

I ground out a solution, but I think there must be a more elegant way to do this.

Given line 1 r=(2,-16,19)+t(1,1,-4) and line 2 r = (14, 19,-2)+u(-2,1,2), find the equation of the line through the origin that intersects both lines.

I set them both up parametrically, point A on line 1, point B on line 2 and said the ratio of OB/OA is constant. Then I set ratio x = ratio y and isolated u, set ratio x = ratio z, isolated u, equated and solved. It worked, but gave me an extraneous solution and was a lot of algebra.

I think there must be an elegant solution to the problem, but I am not seeing it - do you? Thank you!

Hello! Help me find a video on YouTube. There was a girl, a brunette, talking about the topic. The topic was the application of integrals. I was hoping that I could find this video in the history, but it has disappeared.

Hi, I've been looking for interesting podcasts for a long time but can't find anything

I'm presently preparing for my science test because that's the first topic I want to pass. If someone could recommend any excellent YouTube videos or general study materials, I'd really appreciate it.

Hello! I'm organizing my ucas ps rn and intend to apply to the English and Linguistics department. While it is offered by some universities under that name, others provide quite distinct programs under the heading of "English linguistics and cultural studies." If my PS doesn't specifically mention that program's name but covers almost the same ground, is it still acceptable for me to apply?

Hello, everyone. I'm an international student who was accepted into the Publishing MA last week. I was wondering if anyone else here has gotten into this sub (creative writing and publishing MA and international publishing MA students can also participate!) Or if any former students are present. I'd like to discuss more about the programme because I'm still unsure if I want to commit; I just don't feel confidence about it, especially because the accomodation options aren't fantastic. I also have Discord and Instagram if anyone wants to chat there! :)

Hey guys, I would like to share a new book that might be interesting to the community!

Graph theorist Reinhard Diestel has written a book with possibly far-reaching implications for mathematical modelling in psychology:

Tangles: A structural approach to artificial intelligence in the empirical sciences
Reinhard Diestel, Cambridge University Press 2024

Publisher's blurb:

Tangles offer a precise way to identify structure in imprecise data. By grouping qualities that often occur together, they not only reveal clusters of things but also types of their qualities: types of political views, of texts, of health conditions, or of proteins. Tangles offer a new, structural, approach to artificial intelligence that can help us understand, classify, and predict complex phenomena.

This has become possible by the recent axiomatization of the mathematical theory of tangles, which has made it applicable far beyond its origin in graph theory: from clustering in data science and machine learning to predicting customer behaviour in economics; from DNA sequencing and drug development to text and image analysis.

Such applications are explored here for the first time. Assuming only basic undergraduate mathematics, the theory of tangles and its potential implications are made accessible to scientists, computer scientists and social scientists.

From the reviews:

“As a sociologist, I am impressed by Diestel’s innovative approach. Tangles open up completely new ways for empirical social research to gain insights that go beyond the usual generation of hypotheses and their verification or falsification. Tangles offer the opportunity to make the ‘big sea of silent data‘ speak for itself.“

Rolf von Lüde Universität Hamburg

Ebook, plus open-source software including tutorials, can be found on tangles-book.com.

The eBook comes in two versions: an abridged 'fun' edition for readers who'd just like to dip in and get a feel for what's new (and there's plenty of that!), and the full eBook edition which includes the mathematical background needed (which is not much).

Table of Contents and an introduction for social scientists (Ch.1.2), are at tangles-book.com/book/details/ and arXiv:2006.01830. Chapters 5 and 13 are specifically about tangle applications in the social sciences.

The software part of tangles-book.com says they invite collaboration on concrete projects. They have made a big effort to smooth newcomers' access - interactive or read-only tutorials, detailed instructions on how to set up the software. The software documentation and tutorials all refer to the book for reference. But if you have that next to you, the tutorials are fun and easy to work through!

https://preview.redd.it/yx6zapc4ue4d1.png?width=2074&format=png&auto=webp&s=7d239465fe86420253ec6371c27c9a5b0880adb5

Hey, math enthusiasts! I'm a little stuck, so I could really use your combined knowledge. I've been looking for the best essay writing service that caters to math students for the 2024–2025 school year. My search has been drawn out and a little disappointing because the more well-known services appear to be spamming other subreddits without providing any concrete evidence of their ability to handle math-related projects. Nor have the reviews I've read been all that compelling. I'm contacting you in the hopes that someone may be aware of a hidden treasure — a dependable, reasonably priced, and experienced writing service for math essays and papers. I would be very grateful for any advice!

The age of the enlightenment is at an end: reason is bankrupt?

http://gamahucherpress.yellowgum.com/wp-content/uploads/The-age-of-the-enlightenment-is-at-an-end.pdf

or

https://www.scribd.com/document/552377365/The-Age-of-the-Enlightenment-is-at-an-end-reason-is-bankrupt

https://en.wikipedia.org/wiki/Transition_(linguistics) https://en.wikipedia.org/wiki/Level_of_measurement

Hi all

I am just about to put my research in for ethical approval but calculating the power in order to determine the appropriate sample size is a little confusing.

The primary aim of the study is to identity if any relationships exist among the variables I am using. This analysis is fine I have this part sorted.

A secondary aim is to investigste group differences. When data is collected I will have three groups and they will be tested on multiple measures - In total there are about 7 measures with 5 of them being questionnaires and 2 task based.

One of the tasks I am using in this study is novel in this particular area I am applying it to but effect sizes are considered small. Going by what I remember in stats I'm probably going to have to use a MANOVA. However, the effect sizes for sample calculations change from d to f^2 (if I'm correct). So does this mean I should be putting in 0.105 into the f^2 part of g power with the following

F tests. Priori MANOVA - Global effects

Any help would be appreciated.

Hi mathpsych,

As a part of an exam project at my CogSci bachelors I am conducting a research experiment that investigates the effect of hormonal contraception on perserverance in a series of cognitive battery tasks (anagrams, HMT-S etc). The study is based on a previous study by Sarah Hill (link), but I want to approach the analysis from a baysian perspective.

Now to my question: In my model, I want to take both reaction times and accuracy into account. When I do research on this, decision diffusion models are by far the prevalent search result - however, as far as I can tell it is only applicable to fast-speeded 2-choice decision tasks (whereas some of my cognitive battery tasks are multiple choice, some are free, and reaction times will most likely vary form 30 secs to 90 secs). Is there a way to apply a decision diffusion approach to this kind of data, or should I just stick to a baysian model based on informed priors and treat the RT data in a shifted log-normal distribution?

TL;DR: I am in doubt how widely applicable decision diffusion models are, and if they can be applied to cognitive battery tasks with long reaction times and multiple choices.

I'm shootin from the hip here. Anyone know something substantial? My best guess so far...

• cortisol, dopamine, serotonin, adrenaline (more?) = "brain chemicals" = fuel for the "hypo/mania engine"
• The "hypo/manic engine" activates when "brain chemicals" exceed some arbitrary "initiation threshold"
• The "hypo/manic engine" itself supplies the brain with an increased supply of "brain chemicals"...more sensitive to stimuli
• An episode will escalate (like from hypomania to mania to psychosis) as the fuel for the "hypo/mania engine" increases
• An episode will terminate when the fuel runs out...when the "brain chemicals" reach an arbitrary "termination threshold"
  • the "termination threshold" is significantly lower than the "initiation threshold" and time plays a factor too...the engine shuts down slowly. AKA the "hypo/mania engine" can idle on less fuel than it takes to start it
• An episode can also terminate when the brain/body reaches some arbitrary level of strain or fatigue. (possibly adrenal fatigue?)
• The "brain chemicals" feed into eachother. For instance, an increase in cortisol means in increase in dopamine and serotonin.
  • If you block the receptors for one of the sources of fuel (antipsychotics) the engine sputters out
• There is something like a refractory period after an episode is terminated. Perhaps some inhibitory mechanisms prevent the engine from starting for an arbitrary duration.

​

I'm mostly just lookin for some theories on mania. HMU with whatever you got please :-)

similar to base ten digits being mirror neuron groups and you can think of a few digits at a time.

Hello, r/mathpsych!

I am planning to introduce a manipulation of an effort discounting task as a part of my PHD dissertation. However, I am having a lot of trouble understanding how is the subjective value computed from the choice data? As case in point, I am looking at this article: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004116

Let's take for example the simplest model, linear. On a given trial, subjective value V = M - kC, where M is reward for this trial, C is effort cost for this trial, and k is parameter to be estimated. We know M and C, but how do we know V? Further in the article, the authors say: "the softmax function was used to transform the subjective values V1 and V2 of the two options offered on each trial into the probability of choosing option 1.", but I really don't understand what is the use for it if we don't know the V in the first place. My question might sound stupid, and I apologize if that's the case, but I'd greatly appreciate if anyone could help me.

In other words, how do we get from basic information about trials and choices to the k parameter?

Hello everyone. I have a model (or theory) about perspective and knowledge representation, and I would like to have your review. Basically "perspective" is just another word of "schema", but by doing so I think this model gives us three advantages:

• Intuitive and imagery. It is simple, so it can be used to explain in therapy, or can connect with folk psychology ("look at the problem in a new perspective", etc)
• Be an intermediate framework to connect with other fields. From my understanding, the most successful model to represent knowledge is connectionism. However, its applications are still limited to purely cognitive problems (e.g. dyslexia), not to problems in other fields. It is hardly to imagine how to apply this model to explain stylistic devices or communication.
• Provide new mathematical structure to current models. The new structure in here is plane, which represents perspective. In other models, once a piece of information is regarded as a node, it is always be a node. If it regarded as an edge, it is always be so. More than that, the structure of the network is fixed, even though you can work around it by turning the nodes on or off. However, with plane, you are freely to regard it as node or edge, and the structure is fundamentally changed in each plane.

Applications will range from cognitive linguistics, memory, cognitive therapy, social psychology and clinical psychology. They will be:

• Analogy
• Writing
• Finding the balance point
• Communication and perspective taking
• The cold gaze

To be specific, here are the questions that each of them trying to answer:

• Analogy: Why do analogies help us understand a problem we don't understand? How to reason with analogy without making logical fallacy?
• Writing: How to explain a concept when the novice really lacks background? What does it mean to have a transformative writing? What does "big picture" really mean?
• Finding the balance point: Why are efforts to be adaptive become maladaptive? Why is it hard to balance between disciplinary and flexibility? How to stop the indecisiveness without worrying of doing wrong?
• Communication & perspective taking: Why do people keep misunderstand each other? Why do others keep distorting our words? Why don't we realize that we are distorting theirs? How to solve it when it happens?
• The cold gaze: How to see your core value when your mind is clouded with fantasies, ruminations, resentments, or fears?

The underlying philosophies are Taoism, Buddhism, postmodernism, and perhaps romanticism. The discussion section will scramble a bit about the nature of information, metaphysics, epistemology, neurocognition, semantics, and physics. However, these are just minor points; you don't need to know them, and I don't claim that I know them. You can also read my another post that is tuned for folks studying Eastern philosophy.

Here is the link: A theory of perspective. Thank you for your reading. Hope you enjoy it.

I'll be entering a quant Psych PhD program next year. I'll already have an MA in experimental psych and a minor in stats.

Instead of doing the masters in psych that many do within their first 2 years, I thought it might be beneficial to do an MS in stats. I would like to teach in both the psych and stats departments one day, and think it might also be helpful if I decide to enter industry one day.

Any thoughts/insights would be super helpful!

What are books that would help and entrepreneur on mathematical psychology or in general?

I just finished reading "An Introduction to the logic of psychological measurement" by Joel Michell where he presents fairly scathing criticisms of modern measurement theory. I've discussed this book with a few quantitative psychologists who mostly seem to think the whole axiomatic approach to measurement is silly. I was curious if anybody here is a fan of Michell's work.

Hi,

During my PhD I was using a task that is similar to the Stroop Task: there are two possible responses, three cue-distractor compatibility levels [compatible, incompatible, baseline] and I was measuring RT and accuracy. In most studies, each subject contributed 30-60 data points per condition [totaling 120-240 data point per person].

Now I want to model the results, if that is possible. I know that most of the time computational studies use a large N for each condition.

The question is, can I still use these data or I need to conduct new experiments for bigger sample? Can I pool across participants, let's say by normalizing the data?

Thanks is advance.

P.S. I don't have to use specifically LBA, I just assumed that because it has less parameters than other models it can deal better with a smaller sample size.

Hello everyone. I have an interdisciplinary paper and would like to ask mathematical psychologists for feedback. I think it is interesting for you because:

• It gives me a unified view about "meaning". It seems that currently there is no satisfactory theory about it from established knowledge.
• Anecdotally, it has helped me find my maturity, so it should have large impact on personal psychology.
• It connects deeply to other areas of pure math and theoretical physics.

You can read the paper at https://osf.io/m3x2q/. Below are my elevator pitches and excerpts from it. Thank you so much for your time.

#Elevator pitches ##For kids

What is the first step to put a giraffe into a fridge? Open the fridge. Why is that? Because at the very moment you look into the fridge, your perspective changes, and your mind is ready to think outside the box.

##For dynamical systems theorists

• When all oscillators align in the same phase, the system is clearest. However, it only becomes "meaningful" only when we see the whole trajectory of the system.
• Under a different perspective, a trajectory will be distorted and can become a point of another trajectory. This is actually special relativity theory.

##For mathematicians

Do you have any questions that you still can't answer? Maybe the applications of the irreducible representation of PSL(2,ℝ) in harmonic analysis can explain why the answer hasn't come yet.

The diagram

#Excerpts ##Choosing books When choosing books I usually imagine the book is a painting, yet I forget to bring my eyeglass. If every time I close my eyes and reopen them I see a new painting, yet I still don't feel vague with it, then that book is worth reading.

##Describing personality disorders as turbulent flow (psychodynamics)

When a smoke begins to smoulder, it first maintains its stability. But with just a little turbulence, the smoke becomes an uncontrollable chaos. Swirling currents will be generated to radiate heat outwardly, which rolls together and causes more and more energy to be lost. And after the energy is completely depleted, it will dissolve into the surroundings and leave not even a single mark behind.

##Quotes:

• The difference between the almost right word and the right word is really a large matter—it's the difference between the lightning bug and the lightning. (Mark Twain)
• Mathematics is the art of giving the same name to different things (Poincaré)

Poetry is the art of giving different names to the same thing (unknown poet responding to Poincaré)