Trending March 2024 # These Factors Are Causing A Rise In Btc, Eth’s Correlation With The Stock Market # Suggested April 2024 # Top 11 Popular

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Going mainstream is not always the best outcome for assets, and cryptocurrencies have lent proof to the same. While a rise in adoption had definitely brought legitimacy and capital to the market, it has also made it susceptible to macroeconomic changes.

Crypto is stocking up

This has been highlighted in the rising correlation between cryptocurrency and U.S Stock market prices, which has been a worrying trend for analysts for quite a few years. This was accelerated last month when the U.S Federal Reserve’s hawkish stance and inflation reporting sent both markets tumbling down.

Now, as both asset classes enter a period of stability, these fears have been freshly invoked, especially since a number of announcements are expected to be rolled out by the Fed in the coming week.

However concerning the trend may have been earlier, its unparalleled acceleration since August 2023 has sent many into a dizzy. Over the past month, Bitcoin has fallen 12% against the dollar, while the S&P has gone down 10%, indicating that the gap between both is narrowing with each crash.

Martin Green, CEO of Cambrian Asset Management noted the same in a recent Forbes interview, highlighting that while the Bitcoin-Nasdaq correlation was 0.2 over the last three years, “in the last several weeks, it has doubled to around point four.” He added,

“There is a higher correlation today than there was six months ago… I would say that recently along the two axis – up and down – Bitcoin and tech stocks are in tandem because of interest rates and inflation concerns that have affected stocks and crypto.”

Safe haven no more

Crypto and tech stocks moving in tandem could cause many hurdles to global finance, as pointed out by the International Monetary Fund (IMF) recently. Among these include the risk of contagion that could cause investor sentiment to spillover between markets.

A spillover can also be noted between crypto assets, as a similar correlation between the second-largest cryptocurrency Ether, and the S&P 500 has breached record highs.

This has eaten into BTC’s narrative of being a safe haven asset akin to, or better than, Gold. This was behind much of its earlier popularity, argued ChangeNOW spokesperson Mike Ermolaev in the same interview.

He said that while macro trends were a contributing factor towards BTC economic evolution, its mainstream adoption by institutional investors could also have played its part. While outflows from BTC investment products have hit a record high lately, the larger investment cohort has been increasingly bullish on the nascent asset.

Even as this has brought legitimacy to the industry, it could also lead to money managers’ treating the asset similar to traditional tech stocks, thus adding to the correlation.

“There has been a lot of money flowing into crypto from traditional markets these past couple years. During that time, traditional markets and cryptocurrency markets have converged. It’s evident from various indicators that tech stocks and Bitcoin are strongly correlated right now.”

Fortunately, a silver lining prevails amidst the chaos, as Bitcoin and Ether tracking the traditional stock market could mean a surge in these assets’ prices whenever the shares take an upturn.

Moreover, the growth in institutional interest and long-term holders is a signal that the market is maturing and eroding its risk factor. Bitcoin tracking the S&P or the NASDAQ could add to this narrative even further.

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How Young People Are Causing Financial Change With Nubank, Conta Iti, And Lanistar

Today’s young people have been raised alongside the Internet. Digital technology is second nature to them, so it is no surprise that almost every service has gone digital in order to get young people to use their products.

Nubank, Conta Iti, and Lanistar are three financial services that have gone digital. However, unlike some old-school brands, these three companies have been designed to give these people exactly what they need, in a way that is organic and understandable.

But, what exactly are Nubank, Conta Iti, and Lanistar doing that makes them so perfect for the digital age? Keep reading to find out!

Nubank Makes Digital Banking For Everyone

One app that has shown the potential of managing finances digitally is Nubank: one of the first and certainly the most successful neobanking platforms in Latin America. 

Founded in 2013, Nubank has been able to show the potential of digital banking to the world, with an app that is easy to use, convenient, and full of a variety of features that cater to a broad range of financial needs. 

Nubank is so appealing, in fact, that it has been able to branch out to reach audiences beyond just young people: in Brazil alone, an estimated 35-50 Million individuals are signed up with Nubank. The digital age is one that everyone alive today is experiencing, and Nubank has capitalised on this.

Conta Iti Gives Young People Tools For Success

Another Brazillian neobank platform that is working hard to get its product to today’s young people is Conta Iti. 

What sets Conta Iti apart from the competition is the age at which users can sign up. From just fourteen years old, teens can get signed up for the Conta Iti app and banking card, giving young people access to a hands-on approach to financial independence and financial education.

Conta Iti trusts teens and young people to use their product and use it in a way that benefits them: this is not something that every traditional institution is willing to do. 

Lanistar Masters Social Media Marketing

In the age of Instagram, the idea of ‘celebrity’ has rapidly changed. Celebrities are no longer mysterious figures gracing red carpets; they are now live streaming to your phone, showing off the latest and greatest products. 

Celebrities are connected far more to their viewers, as opinion leaders and, most importantly, friends.

Fintech startup Lanistar understands this completely, and understands that in order to reach the right people, it is important to speak to them through channels they actually use and believe in. Hence, Lanistars ongoing campaigns of social media marketing with influencers from around the world ranging from David Luiz to Dan Dukorre.

Understanding how to connect with the right people is not Lanistar’s only skill: they also know what this group of people want.

For example, statistics show that Lanistar’s target audience, those aged 18-35, is also the biggest age group of individuals who use cryptocurrency such as Bitcoin. As such, crypto integration is one of the biggest goals of Lanistar, who intend to have an industry-leading cryptocurrency exchange and wallet working in-app in 2023. 

Want to be one of the first to try it? Then follow the links below for more information on Lanistar and how to get involved:

Bitclout 2.0 Announced As Next Stock Market For People

Los Angeles, USA, April 26th, 2023, Chainwire; Today, an exciting announcement was made on decentralized social app Diamond that Bitclout 2.0, the highly-anticipated follow-up to 2023’s viral sensation that took the crypto world by storm, has been revealed by the infamous @diamondhands.

Bitclout 2.0 aims to build upon the success of the original by introducing several new products and features, effectively turning reputation into an asset class on par with what NFTs are today.

BitClout 2.0 is expected to launch with a sophisticated airdrop after the DeSo blockchain’s transition to its new Revolution Proof of Stake consensus mechanism is complete. The white paper for BitClout 2.0 can be accessed at chúng tôi and the password can be obtained by sending a DM to @bitclout on any DeSo app like Diamond or DeSo Chat Protocol.

Bootstrapping A Stock Market for People

One of the most groundbreaking new products BitClout 2.0 introduces is Creator Coins V2, a reimagined version of the original trading product that sparked thousands of celebrities and influencers to join the platform.

Creator Coins are a new type of asset class introduced by BitClout 1.0 that are tied to the reputation of an individual rather than to a company or commodity, and Creator Coins allow creators, celebrities, influencers, and everyday users to monetize their work in ways never before possible in web2.

Since Creator Coins track the reputation of an individual, if Elon Musk successfully lands the first person on Mars or alternatively go bankrupt, it will affect the price of his Creator Coin.

Creator Coins V2 are fully backward compatible with V1, allowing users to transfer over seamlessly, and will be tradeable on DeSo DEX, the world’s fastest on-chain order-book exchange (showcased by Openfund).

Trading activity on BitClout 2.0 will be incentivized with a new $BITCLOUT token, allowing people to accrue fees through Creator Coin V2 trading activity.

Bitclout 2.0 will reward early adopters through a sophisticated and viral airdrop scheme that takes inspiration from both BitClout 1.0 and from NFT marketplace Blur. BitClout 2.0’s airdrop mechanics will not only drive trading liquidity but also “content liquidity” by compensating the most active creators on the platform.

Creators who post regularly and engage the community will also earn $BITCLOUT tokens through airdrops, adding an innovative new incentive structure for creators never seen on other platforms.

People interested in participating in the $BITCLOUT airdrop can start familiarizing themselves with DeSo apps like Diamond, Openfund, Desofy, or DeSocialWorld, and many more listed on chúng tôi before the launch.

BitClout 2.0 will be built on the Decentralized Social Blockchain. According to the BitClout 2.0 white paper, “DeSo is the only blockchain that can support the storage and indexing requirements needed for a decentralized social platform like BitClout 2.0.” This is thanks to DeSo’s vastly-superior content storage costs, which make it finally feasible for apps to extend beyond DeFi to storage-intensive social applications, and much more.

The History of BitClout

In March of 2023, a mysterious password-protected link began to go viral.

The link allowed users to access a new app called BitClout, created by the pseudonymous founder known as @diamondhands. What started as just a white paper and an associated demo quickly evolved into an addictive worldwide phenomenon, thanks to BitClout’s introduction of a novel new concept known as Creator Coins.

BitClout and its concept of Creator Coins were initially so viral and engaging that the early prototype alone attracted organic signups from hundreds of influencers and celebrities. 

It also spawned numerous articles about its burgeoning “stock market for people,” including a long-form piece in the New Yorker.

The Next Great Decentralized Social Application

With the launch of Bitclout 2.0, the true power and capabilities of the DeSo Blockchain will be on full display for the world to see.

Already one of the fastest and cheapest layer-1 blockchains on the market, DeSo’s move to Proof of Stake is likely to cement DeSo’s status as the industry leader for developers wanting to build storage-intensive infinite-state applications.

Once completed, DeSo will inch closer to its final form, “The Sovereign Internet” featuring a “Decentralized Web,” enabling developers to deploy censorship-resistant storage-intensive applications at scale from anywhere in the world.

Bitclout 2.0 will likely be the first example of what can be built on DeSo post-Proof of Stake, but it won’t be the last. 

Currently, other proposals are circulating, including Bitfair, the first crypto-native sports betting app, and Pseudo, the first decentralized identity marketplace. 

Learn more about the DeSo roadmap and what’s next here.

About Deso

DeSo is a new layer-1 blockchain built from the ground up to decentralize social media and scale storage-heavy applications to billions of users. It raised $200 million and is backed by Sequoia, Andreessen Horowitz, Coinbase Ventures, Social Capital, Polychain Capital, Winklevoss Capital, Pantera, and other blue chip funds.


These Australian Twins Are The Second ‘Semi

When an ultrasound shows that a pregnancy contains two babies within the same placenta, it’s usually a good sign that the twins are identical. But in a case study reported this week in the New England Journal of Medicine, that observation was quickly followed by the realization that one baby was male, and one was female. That’s impossible in identical twins.

The Australian twins, now four years old, are, indeed, not identical. But they’re not fraternal, either. They’re what the medical community calls semi-identical, doctors concluded after a variety of tests—only the second ever case of semi-identical, or sesquizygotic, twins ever reported.

“I think it’s remarkable that the genetic techniques we have today allows us to find these kind of twinings,” says Megan Dennis, who studies human genetics at the University of California, Davis.

In identical twins, one sperm fertilizes a single egg, and the resulting cells split into two groups, forming two genetically identical embryos sharing 100 percent of the same DNA. Fraternal twins occur when two eggs are released, and two different sperm fertilize each. Like different-aged siblings, these twins share 50 percent of of their genetic material.

These semi-identical twins, however, share 100 percent of maternal genetic material and 78 percent of paternal genetic material. During conception, researchers believe that two sperm simultaneously fertilized one egg. The genetic material then split into three groups of cells: one containing chromosomes from both sperm, one containing chromosomes from the first sperm and the egg, and the third containing chromosomes from the second sperm and the egg. The set of cells with chromosomes from both sperm die, as chromosomes from both sperm and egg are needed for survival. The remaining cells combine together again (giving them that weird 78 percent paternal gene similarity) and continue to grow before splitting to form two embryos—the two twins, one male and one female.

“For the most part, one paternal set of cells went to one, and one to the other,” Dennis says. “But there was a little mixture.” So, the twins are also chimeric—they have cells with different genes. Scientists are starting to think that chimerism in humans is more common than previously realized, but this is a particularly rare way for that to arise, Dennis says.

The research team who identified the twins, questioning if semi-identical pairs are more common than was previously thought, also screened almost 1,000 fraternal twins—and found no other cases. The only other known set of semi-identical twins were born in the United States in 2007.

Although eggs have controls in place to prevent fertilization from more than one sperm, it’s not uncommon for a single egg to be fertilized by multiple sperm, either during natural conception or during in-vitro fertilization. However, those embryos are usually not viable, lead to early pregnancy loss, or lead to the development of a non-viable pregnancy, wrote Amanda Kallen, an assistant professor in the Division of Reproductive Endocrinology & Infertility at Yale Medicine, in an email. “This unusual case clearly expands our understanding of ‘what’s possible’ and will allow us further insight into the intricacies of fertilization and early embryo development,” she said.

Cases like these, UC Davis’ Dennis says, help demonstrate the complexity of genetics—and how the simple principles of gene inheritance might not apply in all cases. “Generally, the rules stand, and we should be confident in Mendelian genetics,” she says. “But the genome and development are complicated.”

These Are The Best Carplay Apps For Ev Owners

As the adoption of electric vehicles has grown, so has the availability of EV-specific apps for CarPlay. There are a number of excellent CarPlay apps that help take your EV experience to the next level, including planning trips, finding chargers, and more. Read on for the growing list of CarPlay apps that every EV owner should check out.

EVs that support CarPlay

Most every EV on the market offers support for Apple’s CarPlay platform, including the Ford Mustang Mach-E, The Volkswagen ID.4, the Kia EV6, the Chevy Bolt, and plenty of others. Two of the major exceptions here are Tesla and Rivian, neither of which support CarPlay and neither of which have shown any indication they plan to add CarPlay support.

CarPlay, for those unfamiliar, is Apple’s platform that basically mirrors your iPhone to your car’s infotainment system. You can access specific apps designed for CarPlay, including first-party apps from Apple, third-party apps in a handful of different categories, and interact with Siri.

For a breakdown of the best CarPlay apps across all App Store categories, be sure to check out our in-depth roundup right here.

Apple is also planning a major revamp for CarPlay that will start hitting the first supported cars sometime in late 2023. This “next generation of CarPlay” provides content for all of the driver’s screens in a car, including the instrument cluster. It will also add support for vehicle-specific features like climate controls and drive modes.

The best EV apps for CarPlay Apple Maps

Edit: EV routing in Apple Maps is currently only supported on the Ford Mustang Mach-E. I did not know this, and I hope Apple is working swiftly to expand the feature to other cars.

If you’re an Apple Maps user who wants to stick with Apple’s platform for navigation, the company has done an excellent job of adopting some EV-specific features over the last several years. As you’d expect, these EV-specific features are also supported via CarPlay. This also includes support for multi-stop navigation routes, which is a feature added in iOS 16 this year at long last.

The headlining feature here is support for electric vehicle routing, which means the Maps app can help you plan trips that include support for charging stops for your EV. Apple Maps, when your iPhone is connected to CarPlay, can track your car’s charge level. In some cases, you might also need to download your car manufacturer’s app from the App Store.

Apple Maps takes into account a number of different factors to determine when and how often you need to charge. This includes the availability of chargers, the speed of those chargers, elevation levels, your driving speed, and more. It will then automatically insert charging stops along your route. Additionally, if you drive until your charge gets too low, Apple Maps will present an alternative route to the nearest charging station.

To make sure you’re using all of the available EV features in Apple Maps, update your iPhone to iOS 16, which is available as a free download.

Google Maps

Google Maps offers a handful of features for EV drivers, but not to the level of Apple Maps or some of the other apps on the market. For instance, Google Maps on CarPlay doesn’t offer support for electric vehicle routing. The app doesn’t have access to your car’s battery data and won’t route you to EV chargers on a long drive.

Google Maps does offer a feature that picks the most efficient routes for EVs. The app will ask you to select your car’s “engine type,” and you can choose “electric” from the list of options. Google Maps will then pick routes that are the most energy-efficient, while also still factoring in traffic and other data points.

Google Maps also includes support for manually finding EV charging stations. It will show a few helpful details for these chargers, as well, including connector types and charging speeds. Some stations in Google Maps will also show whether a charger is available or if all of the spots are full.

App Store: Google Maps


Like Google Maps, Waze has a pretty lackluster selection of features for electric cars and this is true for the Waze app via CarPlay as well. The only thing Waze offers for EV owners is the ability to find nearby charging locations and chargers along your current route.

My belief is that Waze is best used alongside another navigation app. But as Apple Maps has continued to add Waze-style features, I’ve found myself relying on it less and less. The lackluster support for EV features doesn’t help the situation, either.

A Better Route Planner

If you’re an EV driver and haven’t tried out A Better Route Planner, commonly referred to as ABRP, you’re missing out. It’s a powerful routing app and service for EV owners that offers more granularity and control over your route than any other option on the market. I’ve yet to find any app that creates plans as accurately as ABRP, nor one that offers the level of control as ABRP.

ABRP allows you to select your vehicle model, enter a destination, and get a full trip plan, including charging stops, total charging time, total trip time, and much more. You can use the app as your main navigation interface via CarPlay, allowing you to see your plan in real-time. This can factor in changes, traffic, and other things that might affect your route and charging plan.

If you don’t want to use ABRP for navigation, you can create your plan in ABRP, then use a different app for navigation to each of the ABRP stops, like Google Maps, Apple Maps, or Waze. Having all of this information accessible via CarPlay is a huge help while driving. You can also view a report after your trip that breaks down the drive time, charging time, and how they compare to the planned estimates.

ABRP is a free download with a $4.99 per month subscription ($49.99 per year) to unlock full functionality. If you’re an EV driver, this is the easiest $5 a month you can spend, in my opinion.

Interestingly, Rivian just recently announced that it has acquired A Better Route Planner. It remains to be seen what this means for the future of the app.

App Store: A Better Route Planner

Electrify America

Electrify America is the largest alternative to Tesla’s Supercharger network, offering nearly 800 charging stations across the United States. The company offers a CarPlay app that makes it easy to find Electrify America charging stations nearby; the app can also route you directly to those charging stations.

In addition to helping you locate charging stations, the Electrify America app also presents some information about those stations. This includes things like the number of chargers available, charging speeds, the available connector types, pricing, idle fees, and more. There are also filtering options available for most of these things as well. For instance, you can filter nearby charging stations to show only chargers that have charging speeds of a certain threshold.

Additionally, you can use the Electrify America app via CarPlay to pick a specific stall at the charging location and initiate charging. This unlocks more of a “plug-and-play” style charging experience and means you don’t have to use your iPhone to do it.

Unfortunately, as of now, the Electrify America app for CarPlay doesn’t show any information while your car is charging. You’ll have to jump to your car’s native charging interface to do this or use the Electrify America app on your iPhone. The CarPlay app will, however, tell you when your car is done charging.

App Store: Electrify America


ChargePoint is similar to Electrify America in that its app is focused on its own network of chargers. Therefore, many of the same features that are available in Electrify America app for its chargers are also available in ChargePoint for its network: finding nearby chargers, filtering those locations, favoriting chargers, and more.

ChargePoint also offers a similar “Start Charging” button for its network of chargers via CarPlay. The app will contact the charger, start the session, then prompt you to plug in your car. Charging will then start without any further interaction from you.

App Store: ChargePoint


PlugShare s a popular third-party service that aggregates electric vehicle charging stations across all networks and types. It’s by far the most powerful platform for locating charging stations of all types, ranging from 120V outlets in random locations to Electrify America and Tesla Supercharger information.

The CarPlay app for PlugShare offers many of the same features as the PlugShare app for iPhone. You can view nearby chargers with in-depth details on things like the number of stalls, plug types, and more. PlugShare will also show the average review score from other PlugShare users for a charging location, which can help you weed out locations that aren’t currently working.

App Store: PlugShare


If you’re an EV driver, you’re likely familiar with the process of trying to find a parking spot at your final destination that offers EV charging. This is especially useful if you know you have a long drive after you finish doing whatever you’re doing at that location, as you can return to a car that’s fully charged.

SpotHero is a CarPlay app that include the ability to filter parking locations based on the availability of EV chargers. Using this, you can ensure that your parking garage or parking location will have EV chargers available.

App Store: SpotHero

And more

These are just a handful of the EV apps that are available via Apple’s CarPlay platform. Here are some of the others:

FTC: We use income earning auto affiliate links. More.

What’s The Difference Between Causality And Correlation?


Causation and Correlation are loosely used words in analytics. People tend to use these words interchangeably without knowing the fundamental logic behind them. Apparently, people get trapped in the phonetics of these words and end up using them at incorrect places. But, let me warn you that apart from the similar sounding names, there isn’t a lot common in the two phenomena. Their fundamental implications are very different.

Let’s understand the difference between Causation and Correlation using a few examples below. Analyze the following scenarios and tell us whether there is a causal relation between the two events (X and Y). Answers are provided below.

Hypothesis – Students going to premium B-schools get higher salaries on an average. Are these B-school a cause of getting better jobs?

Hypothesis – People who smoke are found to have higher level of stress. Is smoking the reason of stress?

Hypothesis – People get more matured after having kids? Is having kids a cause of attaining higher maturity levels?

Hypothesis – We witness lower temperature at high altitudes. Which means, the higher you go, the colder it would become. Is higher altitude a cause of lower temperature?

I hope the examples described above would have triggered your learning appetite and have got excited you to learn more on this. Though, this is not a newly discovered topic, but people still haven’t got firm grip on using these terms. Hence, I have tried to explain the aspects of causation and correlation in the simplest possible manner.

Here are the Answers:

Example 1 : Causal relation does not exist. For instance, only ambitious and intelligent people are selected from elite B-schools who further get much higher salary than the average. Hence, even if these students did not study in Tier 1 B-School, he/she still might get more than the average salaries. Hence, we have alternate reasoning issue in this case.

Example 2 : Causal relation does not exist. We can reject hypothesis based on inverse causality. For instance, higher mental stress can actually influence a person to smoke.

Example 4 : Causal relation does exist. We definitely know that inverse causality is not possible. Also alternate reasoning or mutual independence can be rejected.

Result: If you were able to answer all the 4 scenarios correctly, you are ready for the next concept. In case you got any of the scenario wrong, you probably need more practice on finding cause-effect pairs.

What are the keypoints in establishing causation?

3. Mutual independence : Sometimes X and Y might just be correlated and nothing else. In such cases we reject hypothesis based on mutual independence.

How can we conclusively derive cause-effect relationship?

In fields like pharma, it is very important to establish cause-effect pairs. And that’s why, there are enough researches done to find cause-effect pairs. Let’s understand the following definitions before we get down to mathematics :

1. Randomized Experimental data : An experiment is often defined as random assignment of observational units to different conditions, and conditions differ by the treatment of observational units. Treatment is a generic term, which translates most easily in medical applications (e.g. patients are treated differently under different conditions), but it applies to other areas as well.

2. Observational data : If we do not have the luxury to do a randomized experiment, we are forced to work on existing data sources. These events have already happened without any control. Hence, the selection is not random.

Deriving out causality from Observational data is very difficult and non-conclusive. For a conclusive result on causality, we need to do randomized experiments.

Why are observational data not conclusive?

1. Observational Data not conclusive because the selection in observational data are not randomized. We can never conclude individual cause-effect pair.

2. For instance, if the number of students graduating from Tier 1 B-school get higher salary; this will not conclude causality relationship because the selection was based on initial performance.

3. However, if we randomly select students for Tier 1 B-schools, this analysis will become more conclusive to establish causality.

Why don’t we do random experiment every time to establish causality?

There are multiple reason you might be asked to work on observational data instead of experiment data to establish causality.

First is, the cost involved to do these experiments. For instance, if your hypothesis is giving free I-phone to customers, this activity will have an incremental gain on sales of Mac. Doing this experiment without knowing anything on causality can be an expensive proposal.

Second is, not all experiments are allowed ethically. For instance, if you want to know whether smoking contributes to stress, you need to make normal people smoke, which is ethically not possible.

In that case, how do we establish causality using observational data?

There has been good amount of research done on this particular issue. The entire objective of these methodologies is to eliminate the effect of any unobserved variable. In this section, I will introduce you to some of these well known techniques :

Let’s try this methodology.

1. Following is the equation of regressing y (salary) against both Premium college (subscript T) and unobserved dimensions (subscript U)

2. But, because the unobserved dimension is invariant over time, we can simplify the equation as follows :

3. We can now eliminate the unobserved factor by differencing over time

Now, it becomes to find the actual coefficient of causality relationship between college and salary.

2. Simulated Control : Biggest concern with observation data is that we do not get treatment and non-treatment data for the same data point. For instance, referring to the smoking example above, a person can’t be a smoker and non-smoker at the same time.

But, what if, we can find out a look alike for all treated in the non-treated group. And then compare the response of this treatment among look alikes. This is the most common method implemented currently in the industry.

The look alike can be found using nearest neighbor algorithm, k-d tree or any other algorithm. Let’s take an instance, we have two people with same age group, gender, income etc. One of them starts smoking and another does not. Now the stress level can be compared over a period of time given no other condition changes among them.

While this might sound a very exciting approach theoretically, it is usually difficult to carve out pure simulated / virtual control and this can some time lead to conclusions, which may not be correct. This is actually a topic for a different article in future.

3. Instrumental Variable (IV) : This is probably the hardest one which I find to implement. Following are the steps to implement this technique :

Find the cause – effect pair.

Find an attribute which is related to cause but is independent of the error which we get by regressing cause-effect pair. This variable is known as Instrumental Variable.

Now estimate the cause variables using IV.

Try regressing estimated cause – effect to find the actual coefficient of causality.

What have we done here?

In observational data, any regression technique applied between cause-effect pair gives a biased coefficient. Using this methodology, we come out with an unbiased estimation. For example (in cigarette – mental stress  pair), we might think it could be influenced by reverse causality.

Now, if we can find any information which is connected to cigarette consumption but not mental stress, we might be able to find the actual relationship. Generally IV are regulatory based variables. For example, here we found a tax regulation which increased only cigarette price and lead to lesser consumption of cigarettes across board.  We can now try finding out the mental stress using the 4-step method discussed above.

4. Regression discontinuity design : This is amongst one of my favourite choices. It this makes the observational data really close to experimental design.

In the graph shown below, we are finding a dimension which has a spike on treatment  and non-treatment population ratio. Suppose, we want to test the effect of scholarship in college on the grades by the end of course for students. Note that, scholarship is offered to students scoring more than 80% in their pre-college examinations. Here’s the twist. Because these students are already bright, they might continue being on top in future as well. Hence, this is a very difficult cause-effect relation to crack!

But, what if, we compare students who scored just below 80% (say 79.9%) with those who scored just above 80% (say 80.1%) on grades by end of the college. The assumption being that 79.9% student won’t be much different from 80.1% student. And the only thing which can change is the effect of scholarship. This is known as Quasi Randomized Selection.

Hence, the results are very close to perfect conclusions on causality. The only challenge with this methodology is that getting such a dimension is very difficult which can give a pure break up between treated and non-treated population.

End Notes

Establishing causality is probably the most difficult task in the field of analytics. The probability of getting it wrong is exceptionally high. Key concepts discussed in this article will help you address the question of causality to a good extent.

Just to end the article with some humor on the topic, here are a few images to drive the difference in correlation and causality.

A spurious correlation:

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