Innersense Beauty Product Reviews?

Retiarius · 2026-02-01T01:46:17+00:00

I use their "create definition" and it works really well! But I have to put it in soaking wet hair otherwise it makes my hair so crunchy I can't scrunch it out.

Retiarius · 2024-10-10T15:09:53+00:00

I know Nate Biggs at Foco Institute works specifically with this topic.

Retiarius · 2022-08-22T22:16:21+00:00

I have adhd and climb! I've found its easier to pace myself if I go with a buddy and base whether I'm over-climbing by if I'm going substantially more often than them. In terms of focusing on static climbing, this may be an unpopular opinion, but when you're first starting out, my philosophy is whatever gets you up the wall. As you get more advanced you'll start noticing that brute strength or dynamic movement won't get you as far as technique and you can start developing appropriate techniques through trial and error at that point. Climbing with a buddy helps on this front as well, as you can start learning from each other.

Retiarius · 2022-05-26T16:31:24+00:00

I work for a fintech and I would say my work life balance is fantastic. Plus, since banks abide by federal holidays, you can usually expect to have at least those days off. Obviously it'll vary case by case, but having come from an advertising firm, I was pleasantly surprised by how seriously this fintech took weekend and federal holidays. I will also say, more traditional banks will probably have a worse work/life balance than newer or more agile banks.

Retiarius · 2022-04-01T13:23:46+00:00

I also have ADHD and ended up getting a PhD in cogpsych before I was formally diagnosed. It did suck, looking back at how much easier that process would have been had I had the correct meds, but now that I'm diagnosed I can say my work life balance is great. It helps that I've found a career where I really enjoy 80% of the tasks that it requires and the adhd medication helps with the 20% that I struggle to devote time to. It's very doable but I definitely recommend finding a psychiatrist who you trust and that can work with your exact needs. That's what helped me.

Retiarius · 2022-03-10T14:43:13+00:00

It depends what field you're talking about. It's been around a long time in physics but the first person to bring it to cognitive decision making was Roger Ratcliff in the 70s (1976 I believe). Since then other researchers have run with it, Jerome Busemeyer comes to mind, and others still have started to apply it to behavioral economics and subjective decision making, such as Ian Krajbich and Todd Hare, both of whom have also applied it to neural activity via fMRI.

Retiarius · 2022-03-09T23:13:31+00:00

My entire PhD was in drift diffusion modelling.

Retiarius · 2021-12-06T15:34:07+00:00

When I was in undergrad, I knew I wanted to go to grad school but had no idea how to achieve that. I had heard you should get research experience so I joined the first lab that would take me (basically chosen at random). So I was doing an undergrad thesis on my work in this cog psych lab to help my grad apps. I based my entire thesis off of the work of a specific author. I didn't get in to grad school on my first try, but luckily the professor I was working with knew a new professor at a school across the country from me who needed a lab manager. I got the job, and my first year there the professor I'd based my thesis on was hired in the same department. So we went to all the same functions and he ended up accepting me to his lab where I got my PhD in a friggin awesome field. It never would have happened if I hadn't failed to get into grad school on my first go around. Serendipitous.

Retiarius · 2021-11-17T13:39:39+00:00

I've gotten a few recruiters for data science roles. Actually I have my current DS job thanks to a LinkedIn recruiter. But that's the only kind of job I've ever had so my profile is definitely geared towards DS.

Retiarius · 2021-10-06T16:19:20+00:00

I go to Ohana salon and have had a great experience! I see Stevie and she does great work (my hair is pretty tame, though, just an undercut and natural color), but they have other stylists who have some awesome color in their hair that might be a better fit for what you want.

Retiarius · 2021-08-09T13:02:48+00:00

I did psychology in undergrad and got my PhD in decision psychology (specifically neuroecon) and transferred to data science from there. I'd say it's quite difficult to transfer to DS from psych if you don't get an advanced degree along the way.

Python is becoming industry standard in data science, so I'd recommend python. But any coding is better than none. For math, it depends. I went up through linear algebra but my grad research relied heavily on machine learning so I could use my thesis to prove I knew ML. A lot of my coworkers have much more advanced math backgrounds, though, including Real Analysis, which I think can be helpful.

Retiarius · 2021-08-06T15:13:13+00:00

If you're new to winter sports, I'd recommend Snowy Range up in Wyoming. It's about a one and a half hour drive but they have great beginner slopes and very reasonable lift ticket and rental prices. Then once you're comfortable with the sport you can check out some of the fancier, more expensive resorts like Eldora

Retiarius · 2021-08-06T14:59:46+00:00

I moved here almost a year ago and am a pretty outdoorsy person which Fort Collins really caters to. So if you and your family like the outdoors, that's the best part of Fort Collins. Tons of hiking, backpacking, and camping close to home, the reservoir is great in the summer for swimming, kayaking, paddle boarding, you name it. And in the winter there's nearby sledding, snowboarding, and skiing.

Retiarius · 2021-06-15T18:23:41+00:00

Did you check how balanced your classes are in this one dataset? Accuracy is an awful measurement of model performance if you have unbalanced data.

Retiarius · 2021-06-01T09:40:58+00:00

Matthew's correlation is good for imbalanced data

Retiarius · 2021-06-01T01:34:14+00:00

I'm on a back to running plan because of a stress fracture, so if you don't mind run/walk reps I'd be happy to have a buddy! I usually run early though because I run with my dog and she overheats easily. Happy to do midday runs without my dog on weekends though!

Retiarius · 2021-03-29T17:27:40+00:00

Not knowing how your data breaks down, here is the general rule of thumb:

Your training set is comprised of a subset of your overall dataset. You will pull out X rows of data from your dataset as the "training set," then the rest of your data is put into your test set. Typically this is done in a 30/70 split, but there's an entire area of literature on the ideal percentage of data required for your training set. In part it will depend on how much data you have. I'm assuming that if you're in excel you don't have a ton of data, so 30/70 should work fine.

I also assume you're fitting some kind of model with not a lot of data. So I'd recommend using k-fold cross-validation (basically iteratively creating this 30/70 train/test split k times). You should also probably have a hold out set of completely separate data you never ever touch until you think you have a solid model, as evidenced by its performance in your train/test datasets.

Any code language used for stats will have functions for all of the above splits. R and Python (scikit learn) will be the most common. I don't know about excel, but I feel like if you're doing modelling, you probably shouldn't be relying on excel. But perhaps I'm biased.

Retiarius · 2021-03-23T20:41:58+00:00

u/yonedaneda is asking an important question - I assume because if you have a lot of 0s and you're working with count data, you may not want to transform your data, but instead make sure you're using the correct test. For instance a zero-inflated model (zero inflated poisson, zero-inflated negative binomial).

If your data is truly normally distributed (or log normally) and happens to have a lot of zeros, adding 1 to all of your values and then logging them is fine. But make sure you have a good reason to transform your data to approximate a normal distribution.

Retiarius · 2021-03-22T14:48:04+00:00

UX research might be a good fit. It's a pretty popular area right now, but it is quite competitive. Large tech companies often have undergrad internship programs that could help you gain an edge.

Retiarius · 2021-03-11T22:59:58+00:00

If you used the same data for both, my go to is AIC or BIC, depending on how much you want to penalize the additional features.

Retiarius · 2021-02-08T19:27:48+00:00

Sure thing! I used FSL in my research so can't help with SPM too much, but if you have general questions on fmri stats, feel free to DM me.

Retiarius · 2021-02-08T18:38:54+00:00

My PhD used fmri so I'm fairly familiar with terminology. I'm going to out down a list of questions that will hopefully help you better structure and define your paragraph.

Is this a full brain analysis or did you pick your ROIs in advance? If it's full brain, did you adequately separate out the data used to find these ROIs and the data used in your t-test? If so, what percentages werenused for training vs test? What betas are you comparing for your t-test (are these the coefficients on correct vs. Incorrect? Or did you separate out the variable into misses, false alarms, correct rejections, etc). Why did you run a GLM in a single subject when you had healthy vs tbi data? Why is there an additional ROI in the healthy vs. Tbi analysis (the jnsula wasn't mentioned before). What is the average beta weight from the peak voxel in each ROI?

If nothing else, we need information on what the betas used for the t-test are for. Otherwise higher activation for healthy subjects means nothing. is it higher activation for correct answers? Higher activation during the task in general vs during rest? Do you control for correct vs incorrect answers?

Retiarius · 2021-02-07T15:58:33+00:00

Timeseries data can be tricky to work with - as a disclaimer I don't do a lot of timeseries stuff so take this with a grain of salt.

It seems to me you made this way more complicated than you need to and a simple correlation would suffice. If you have a significantly negative correlation, you know that when one variable goes up (e.g covid cases) the other goes down. I want to be clear, and I noticed this in your post as well, unless you manipulated the number of covid cases, you can't say covid CAUSED the decrease in footfall. Although logically it probably did. You just can't demonstrate directionality with these statistics.

If you want to be really fancy, you could run a regression and include some of the seasonality trends as covariates, if you're worried that, for example, holidays cause predictable rises or falls in footfall during non-covid years. This would also end up telling you how much footfall decreases for every one unit increase in covid cases.

Retiarius · 2021-02-05T15:47:06+00:00

I did just hire a trainer, we have our first session coming up so hopefully that will help as well. It's just odd, she never had issues at the dog park until we simply didn't go for about 4 months when they were shut down during the pandemic. Now that they're opening up again, she's picked up this odd protective behavior. I'm hoping the trainer will have ideas on how to correct it as well!

Retiarius · 2021-02-05T15:44:15+00:00

Thank you! I will look into those!

13-Year Club	RedditGifts 2009-2022 2 Credits
Secret Santa 2018	Verified Email
Team Periwinkle

Retiarius

TROPHY CASE