What is probability | Expected Values, Frequency Distribution, Complement

👉🏻 Sign up for Our Complete Data Science Training with 57% OFF: https://bit.ly/2ZIUrvF Learn how to calculate simple probabilities, compute expected values, find probability frequency distributions, and use complements. ► Consider hitting the SUBSCRIBE button if you LIKE the content: https://www.youtube.com/c/365DataScience?sub_confirmation=1 We ask ourselves questions like “What is the chance of success?” and “What is the probability that we fail?” to determine whether the risk is worth taking. Many CEOs need to make huge decisions when investing in their research and development departments or contemplating buyouts or mergers. By using probability and statistical data, they can predict how likely each outcome is and make the right call for their firm. Some of you might be wondering: “What is this probability we are talking about?”. Essentially, probability is the chance of something happening. A more academic definition for this would be “the likelihood of an event occurring”. The word event has a specific meaning when talking about probabilities. Simply put, an event is a specific outcome or a combination of several outcomes. These outcomes can be pretty much anything - getting Heads when flipping a coin, rolling a 4 on a six-sided die or running a mile in under 6 minutes. ► VISIT our website: https://bit.ly/365ds 🤝 Connect with us LinkedIn: https://www.linkedin.com/company/365datascience/ 365 Data Science is an online educational career website that offers the incredible opportunity to find your way into the data science world no matter your previous knowledge and experience. We have prepared numerous courses that suit the needs of aspiring BI analysts, Data analysts and Data scientists. We at 365 Data Science are committed educators who believe that curiosity should not be hindered by inability to access good learning resources. This is why we focus all our efforts on creating high-quality educational content which anyone can access online.