highly recommend that you check it out i know they've been working really hard to rebrand and build out the new platform so i'm also really really excited to check it out when their new website goes live all right back to the video number two is uncertainty so there's this joke that data scientists are usually the ones with the most like filler words and the most kind of like qualifying words for example we always say stuff like perhaps maybe it is a possibility it is likely it seems it appears i think and my favorite yes but you never know these days okay so let me give you an example this is not a real example but say that your job as a data scientist is to improve a e-commerce store so you're like okay i have all this data so let me try to figure out what variables are correlated with people who click more things on the ecommerce store and eventually buy stuff so you do your correlational analysis and you find that okay so these are the variables that are correlated with people purchasing things but you know the golden rule that correlation is not causation so you're like okay in order to actually establish a causal effect i have to conduct an experiment so in your analysis maybe you found that people who got more notification are those that go on to purchase more things so you decide to run an experiment to have a control group and have a test group where you send people more notifications so you do that and you find that there actually is a statistically significant difference between your control group and your test group at NUMBER_TOKEN confidence interval wait pop quiz time pause this video and answer in the comments below what does it actually mean to have a NUMBER_TOKEN confidence interval in layman terms so hopefully you know the answer to your question where you figured it out and you left the comment and then you present to your stakeholders okay it seems that sending these notifications is actually quite good and it seems that it increases the metric that we care about which is dollar spent for example but you never know these days because you know even when you do experiment like this you really can never be NUMBER_TOKEN sure about anything first of all you need to be okay living with that uncertainty make peace with that uncertainty because as a data scientist you are just very uncertain about everything the trick is to really know your statistics so that you're able to quantify your uncertainty and communicate that with other people with your stakeholders in a language that they understand so definitely don't just be like yep it's that sick and NUMBER_TOKEN confidence interval because like what does that even mean the third thing that i wish i knew about being a data scientist is the amount of ambiguity there is this is kind of related to the first thing i talked about in which you know they hire you based upon your baseline skill but you're kind of expected to just figure things out and then learn the things that you need to learn and then implement them so that you're able to do your job some anonymized examples of things that people have asked me what should we do for holiday season how would i know what's the sales projections how do we make the ranking better how do we decrease harm you you get them basically people often ask you very very vague things or they sometimes don't even know what it is that they want so the first part of your job is to actually figure out what it is that they actually want for example make the ranking better like what what ranking but it's your job to figure it out let's take the first example of what should we do this holiday season an example approach that you
START_SPONSOR_TOKEN highly recommend that you check it out i know they've been working really hard to rebrand and build out the new platform so i'm also really really excited to check it out when their new website goes live all right back to the video number two is END_SPONSOR_TOKEN