So from my understanding, we can produce a bootstrap distribution from a single sample taken from a population. However, I'm confused as to how the margin of error of the bootstrap distribution can be estimated as the same of that as the sample distribution. This leads me to two questions:

a.) Shouldn't the margin of error of the bootstrap distribution be larger than that of the actual sample distribution (just like there is an error between the sample and population)?

b.) Also, if the point of statistics is ultimately to make an inference about the population, how is making a bootstrap distribution useful? If we happen to select non-ideal sample, wouldn't the bootstrap distribution made from that sample also not be (or be even worse of) a representation of the population?

I'm not sure if my questions made sense as I struggled on how to word my own confusion. Thanks in advance!

Hi, I recently read a statement along the lines of "if statistics were invented in the computational era, complicated statistical tests would never have been invented". The Statement then went on suggesting that bootstrapping approaches would have been used from the start.

How do you think this statement holds up? Is bootstrapping straightly superior to classic statistical testing? Could all statistical tests be replaced by bootstrapping? And if so, is this the future of data science?

I would also like some interesting literature regarding this topic, if anybody has some suggestions

Say I have a 2-class classification problem. I have 100 samples altogether in my data, and I train and test a classifier with 5-fold cross-validation. To estimate mean accuracy and confidence intervals, I resort to bootstrapping.

I this example, the sample I bootstrap on consists of 100 binary values that represent right or wrong prediction on my test samples, pooled across the 5 folds (80 training samples and 20 test samples per validation folds x 5 folds = 100 test samples).

Now, to bootstrap, I draw 100 samples with replacement, over 999 resample instances and then I compute the 2.5%ile and 97.5%ile values of the mean from each resample. So far so good!

My question is the following: Since I had only 20 samples per cross-validation fold, my resolution for the classifier accuracy is 1/20 ~ 5%. If I take all 5 folds together, my resolution is 1/100 ~ 1%. In other words, prior to bootstrapping, if I simply report the mean classifier accuracy, I cannot report 93.2%: the best I can resolve the accuracy to is 93%.

However, now that I have bootstrapped 999 times, does my resolution of the mean accuracy improve to 1/99900 ~ 0.001%?

The question applies to any summary statistic and not just the mean (e.g. 95% confidence intervals, as mentioned in the above example).

It probably makes no difference to my current article, but I'd like to get it right.

Thanks for your input!

[Edit: Typos and language]

"Anna has had offers from several siblings to get out. Since she hasn't, she must want to be in the cult"

"I was part of xyz and at 19, I left and haven't spoken to my family since. If I can do it, any of the Duggars can do it."

I've seen these comments on DS. These comments make me so angry because they're so shitty.

"Sally knows she gets cat calls when she dresses a certain way. At this point, it's her fault that it keeps happening to her."

"If I can figure out how to not live in abject poverty and work in retail forever, anyone else could too. People who think burger flippers deserve a living wage are entitled."

Honestly, the second set of comments give me the exact same vibes as the first examples. But am I wrong?

^pls ^go ^ahead ^and ^tell ^me ^if ^you ^think ^I'm ^wrong

Writing bootstrapping code was a giant pain.

I've been having a look in my sentry performance section. Most stuff is mostly as expected, but what strikes me is that app.bootstrap takes about half of my overall response time.

Anyone got any tips on how I would go about looking into seeing what's taking so long, and how could I potentially speed this up?

Thanks!

Edit: this is from production. Running Laravel 8.x and php-fpm (8.0) natively on CentOS.

Edit2: it looks like tweaking OPCache has helped a lot

A massive thank you to everyone who's contributed to this! Really appreciate all your input!

https://preview.redd.it/axjt0k95fo581.png?width=2128&format=png&auto=webp&s=b8e385deb4ec4bfed894d4c4d68d3a11efd325f8

A. The company makes enough that you just bought a new house in a very expensive market… what are we bootstrapping?

B. I’m convinced the phrase “bootstrapping” was made up by business owners to dangle hope of better conditions that will likely never be seen by any individual employee…

C. I’m done now thanks lol

How will ethereum 2.0 make sure that new validators or validators that come back online will choose the correct version of the chain?

Apparently people do "bootstrapping" where we take a small sample, and then resample from it with replacement over and over again. But we already know Everything there is to know about that sample. We can just count the elements of it, so what does bootstrapping actually accomplish?

Furthermore, why do we have to simulate the samples? If we know how many elements of each type there are in the sample, can't we just calculate with a closed equation what the bootstrap distribution would be, since again We know exactly what is in the sample?

Update: Thanks for all your helpful comments. Basically my confusion was due to a failure of imagination on my part; I didn't realize how commonly difficult/impossible closed-form solutions to pretty simple questions about sampling distributions were.

I've recently changed jobs and am getting back into primarily managing UNIX/Linux machines after spending 11 years working in vendor support on a proprietary NAS system. The NAS system primarily used a proprietary OS and then Debian rather than RHEL although the external WebGUI system used CentOS.

In my new role, RHEL 7 and 8 are the primary GNU/Linux distro they are using. I've used various Linux distros in the past (including Redhat) but my primary UNIX system experience was Sun Solaris up to version 10 so I need to get more tuned in to the current "Redhat way."

I have a single Dell PowerEdge T40 at home and I'd like to rebuild that with RHEL 8.5 and then keep the configuration of it in version control (git most likely). Once the server is in place I'll start using it to build other systems - perhaps set it up as a PXE boot build server etc. For a bootstrapping situation like this how would people approach trying to do this in an infrastructure as code approach? What tools are the most appropriate for this sort of situation? I'd imagine ansible will be a likely candidate?

TIA

I'm currently bootstrapping on an idea. It is very early days. I've spent a few months on it thus far. It's a development heavy product and I feel that going alone is too slow as I have to switch context between product, design, engineering. I've been looking out for co-founders but the people I'll like to work with are not available at the moment.

I started reaching out to past contacts and colleagues to ask if they might be interested to help out on the side. They are people who would make great employees but not necessarily inclined to be or suited as co-founders.

One of them has shown interest and started helping out of their own goodwill.

I intend to rope in one or two more people to help. What are some good ways to compensate them for their time?

My current train of thought is to explicitly state that I will give them some form of compensation if a seed round has been raised:

• I'll offer them a job. The equity will vest earlier, depending on when they started helping.
• If they don't take a job, I will offer a token sum. Perhaps I'll base this amount on 0.5 to 1 month worth of salary.

What other options are there that I can consider?

Thanks!

I have a killer idea. Validated.

What I need to know is, should I be bootstrapping this, or getting an angel investor to fund this project?

I’ve got friends who have bootstrapped and succeeded, and I’ve got friends who have had angel investors that have succeeded. And all of them have different opinions.

Ideally, I need some funding to pay for my living, while I continue to build the software over the next 6-8 months. Some have even recommended a personal loan for now, while I build.

I’m at my wits end - maybe someone could share their success story with me, and how they got it off the ground?

TIA

SaaS businesses need lots of time to establish their presence and build a community around their products. Besides time, they also need a substantial amount of capital to build a strong foundation for growth, after which they need to keep making profits to scale. Some SaaS owners rely on outside investments, while others chose to brace the storm on their own.

It’s impossible and quite unfair to say which is better, but what we can do is look at the main pros and cons of both options:

Bootstrapping (+) :

• Executive ownership
• Complete decision-making freedom, especially regarding capital
• Limited finances create smart, disciplined spending habits
• More time and focus on perfecting the product, rather than making returns ASAP

Bootstrapping (-) :

• Not suitable for every business
• Competitors with funding have a greater chance of success
• Slower business growth
• Personal risk - less guarantee that personal investments will pay off

Investments (+) :

• Faster business growth
• Greater capacity to make ‘expensive’ decisions
• ‘Big’ investors bring credibility to the business
• Increased pool of knowledge, skills, experience, or networks

Investments (-) :

• Take away some ownership from the entrepreneur
• Decreased autonomy in decision making
• (usually) Interest rates, which increase personal liability
• Less financial discipline

SaaS founders and entrepreneurs, which path did you take in creating your SaaS startup, and do you believe that one is better than the other?

Anyone seen the LBP just added today in osmo zone? doesnt say anything about what kind of APR it provides.

• Start Weight
  10 ATOM : 90 CMDX
• End Weight
  50 ATOM : 50 CMDX

This is confusing me since I'm essentially doing simulations of simulations, which feels incorrect right off the bat.

What I'm trying to do: figure out how many samples I will need to collect so that the bootstrapped confidence intervals of my metric of interest (i'll call MOI) are within a certain lower limit (no formula exists to calculate this directly).

What I've done:

1. Run a data simulation for some N patients where a score predicts whether they are sick (in this case I simulate it to have an AUC of ~0.92). With a massive sample size, the MOI is 10, so I'm considering that the "true" value.

2. Run the boot() package in R to bootstrap the CI for for MOI using 1000 replicates (I focus on the bias-corrected and accelerated CI) - I want to see what initial N (sample size) I need so that my confidence interval lower bound is reliably above a certain value (5). The upper bound doesn't matter.

With n=200, I get an estimate of 9, and the boot() package gives me a CI of [5 - 17]. However, this of course depends on the seed...the next run gives 29 [12 - 93], the next 10 [4.8 - 19].

With n=500, I run the script many times and the lower limit never dips below 5. But how do I eloquently do this - i.e. repeatedly simulating the data, bootstrapping the data, then checking the distribution of results until I find an N where <5% of these (fake) studies have a lower CI for MOI that is <5...is this ludicrous?

edit: initial post had some weird numbers - fixed

This me: https://twitter.com/tylertringas This is what I do: https://calmfund.com/ This is where I write sometimes: https://tylertringas.com/

Looking forward to chatting with you all for the next few hours.

Let me clarify my questions:

1. My understanding is that the bootstrap approach resamples a dataset to create many [simulated] samples - but how does it select which values in a simulated resample? Lets say I have a dataset with n = 30, does every point have a 1/30 chance of being selected during a resample? I.e. Does the bootstrap assume a uniform distribution of this sample data? If this is the case, isn't it a bad that an extreme value has the same probability of occurring as what otherwise might be a more "normal" value? Or I am misunderstanding.
2. With a Monte Carlo Simulation, the more iterations the better (in terms of converging to a more reliable output statistic) - can the same be said with bootstrapping (i.e. the more resamples, the better)?

Thanks

The cool thing about having an entrepreneurial-related podcast is that I get to speak with very knowledgeable people inside the startup and bootstrapping world.

Arvid Kahl is a multi-talented business professional working as an expert software engineer, a successful entrepreneur, and an energetic writer. And here are the 9 lessons I got from our interview:

1- Go for an Audience First Approach

The audience-first approach is a much more effective way of gaining success in your venture.

It involves finding a niche or a problem prevalent in an existing target market and creating a product for it.

It is imperative that you understand whom you are creating products for, what their critical problems are, and how your product can solve those problems.

2- Listen To People Rather than Assuming

Every bootstrap founder needs to research the market before starting the project.

You should carefully listen to what the people say rather than making assumptions about their needs and preferences on your own.

3- Look Around your Circle for Ideas

In our chat, Arvid shared a great exercise to find potential products you want to build:

Start by looking at your own expertise and skills:

What is your background? Do you have any hobbies? What is unique about you?

Then look around in your family and social circle:

Is there any problem in their lives that you could fix with a product/service?

Write down everything you discover and rate them based on your interest for the topic and the potential of the idea.

This practice can also help you to identify an audience and a potential market opportunity.

4- Serve People You can Relate To

Choose a target market or a community of potential clients that you understand and can relate to. A new, unexplored set of people are hard to cater to as a company.

5- Become an Adaptive Generalist

Becoming a generalist means having knowledge of multiple disciplines rather than sticking to one specific expertise.

Use the diversity of skills to intersect and face the challenges that come your way.

6- Understand the Downsides and Upsides

In a bootstrap venture, you must understand that there are no guarantees of success. You may lose everything you have. There are several risks and stresses that you will be exposed to.

On the upside, you will have all the control of the company. You can hire whomever you want, do whatever you want, and sell the comp

Hey, I'm in the beta stage of my startup https://www.gainknowhow.com/. I'm trying to get feedback from my contacts and strangers on what they think of the idea and the app. Basically, it's the documentation tool I've been desperately wanting in previous tech roles. Now I just need to convince others of its benefits. What do you think?

It’s been almost 365 days since we launched the first version of Postpace and today we have reached nearly a quarter of a million dollar revenue.

6 months ago, I wrote our first open building report and shared our whole process of ideation, building and launching a SaaS minimum viable version (MVP) and growing it to $146k revenue without any funding.

Today, I am excited to publish our second open building report and share everything about what we are doing to find product-market fit for our SaaS startup.

To introduce myself, I’m Muntasir. Along with my co-founder Moin and colleague Mohiuddin, I’m building a productivity platform for content writers, marketers and teams with end-to-end workflow automation.

My motivation to write this and all future articles is to share our journey of building a global SaaS company (both wins and failures) in a very transparent manner. So, without further ado, let’s start 🤩

TL;DR

1. Validating a business idea is just the start, it doesn’t necessarily mean the business is sustainable and repeatable. The next step is, finding product-market fit which ensures the business creates recurring value for its customers.
2. Customers’ needs are diverse and will often lead you to build the wrong overall product. Identify the persona who needs your product most and focus on solving their problem first. Building for all is a recipe for disaster.
3. Product management is an underrated skill for founders. Customer feedback and suggestions should not be literally translated into product features. Using customer suggestions to identify their pain point and then designing a viable solution is the right way to do it.
4. Celebrating a feature launch is a great way to build community and traffic. Break the cycle of boring feature announcements and actually treat every feature launch as a product launch. Trust me, when it comes to SaaS, you can’t launch enough times. We have launched more than 80 times so far 😎
5. Raising prices gradually doesn’t hurt conversion rates. Lower price is never a competitive advantage, frictionless user experience is a competitive advantage for SaaS.
6. SaaS is easy to launch, hard to grow. Keeping the process simple and giving the idea enough time to

My elderly dad just got me with this one.

Hey fellas,

I've copied the Bootstrapping section of Packer docs verbatim, appending the -u option to the command to run only the packer portion of my config, minimizing errors from config of plugins not yet installed:

nvim --headless -c 'autocmd User PackerComplete quitall' -c 'PackerSync' -u ~/.config/nvim/lua/config.lua

However running this still produces errors that require Press ENTER or type command to continue — which apparently halts it if ENTER is pressed. CTRL-C and re-running several times does not break the cycle.

If desired, this is a pastebin of the cycle I get stuck in.

How do you guys manage the bootstrapping of your Neovim automatically?

Hi,

Run a B2B saas. Have potential few Customers willing to pay few hundereds a month for my SaaS usage.

Found them since they believe in the SaaS I built, it brings them vaule (yes, on my own, with some parttime help. My skills are maxed out - 40 years old. Tech also moves so fast). Service is not perfect, but does its job. Customers now require perfectness and low price. Lol.

Few questions:

1)how to bootstrap successfuly, meaning.... All those other SaaSes with tons of resources (VC capital) will have easier game winning Customers. Yea, they will not be local, understanding localities, without smb feeling etc... But for some it is not a concern. Fair enough.

What could be my advantages?

2)Related question... Is an option to use eastern european, asian, middle east... you name it, outsourcing services the only way to go? How can I bootstrap a startup, hire employees with such a small revenue?

Or do I have to be a backend, frontend, design etc magician doing the stuff on my own??? Subcontacting etc Is it even possible? Lol.

3)anybody pulled this off? Show your thing (DMs are welcome). What is your setup? Did you do coding, design, idea or run the business? Do you subcontracting and put pieces together?

To me it seems like if you are a tech magcian with business acumen and skills or using outsourcing companies (if there are cheap and reasomable Quality ones) you can pull it off. For every other person, VC capital to hire employees, pay the bills needs to be there.

Having VC capital and in the end less company, responsibilities toward VC desires, does it all make sense vs good old job with decent payment? Or should VC funded Founder have 200-300% average salary for IT/Business roles. What I am trying to ask is, why people do it? It it only for young, unexperienced, that could not get a good job, ppl from areas where there are less possibilities and cheap labour?

Some info about me. 40, currently in leadership at a smb company. Successful and experienced in IT. Many job options availbe in my area.

I know many questions, tried to group them in clusters.

Looking forward to your advices/comments.

Thanks,

Hey there, my name is Tiago and I am the host of Wannabe Entrepreneur, a podcast about what is really like to bootstrap a company.
My journey started 6 months ago in this subreddit when I pitched you the idea of starting a podcast about my journey trying to work 100% in my side projects. The post got more than 140 upvotes which gave me the motivation to start.

Six months have passed and I have published 160 episodes. I have definitely learned a lot and today I want to share my top 5 learnings with you...

1- Build a Website
This is something that I regret not having done sooner. Just by publishing your episodes descriptions, you are already feeding google with delicious SEO content that will bring you, new free users. Besides is much better to share a link with your users that you can control. At first, I was using Anchor as my host and once I changed to Redcircle I had to update that link in too many spots...

2- Record under a blanket
If you don't have a great mic or if you are in a very echoe room recording under a blanket will do wonders to the quality of your sound

3- Use Zencastr for interviews
I can not believe that this is a free tool. You can record with multiple people and the tool will record each voice separately with amazing sound quality!

4- Start Monetizing from the start
This applies especially if you want to have members supporting you and want to share a link. The later you start the bigger the pain of going back to your old episode's show notes updating the description.

5- Start marketing from day one
Unfortunately, like in any entrepreneurial project, marketing is crucial to get new users and the sooner you start it the better. Find out what channels work best for you and go for it! For me I found Twitter to be really successful!

I hope this was useful and let me know in the comments if you have any questions! Cheers!