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Measuring the success of "WhatsApp Channel" involves assessing various aspects to ensure it aligns with Meta's goals and user expectations. Here's how I would approach it: 1. Possible Purpose: • The primary purpose of WhatsApp Channel is to provide a reliable and private way for people and organiz

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Hypothesis testing is a statistical method used to make informed decisions or draw conclusions about a population based on sample data. It involves several key concepts, including null and alternate hypotheses, significance level, test statistics, p-value, type 1 error, type 2 error, and power. Let'

Margin of error and confidence interval are important concepts in statistics that help us understand how certain we can be about the results of a survey or study. Let's break them down with a simple example. Margin of Error (MOE): The margin of error is like a safety buffer around the results of a

The Central Limit Theorem (CLT) is a fundamental concept in statistics that describes the behavior of the sampling distribution of the sample mean (or other sample statistics) when samples are drawn from a population, regardless of the shape of the population distribution. In simpler terms, it state

In statistics, a population and a sample are two fundamental concepts used to describe the group of individuals or observations under study: 1. Population: • Definition: A population refers to the entire group of individuals, objects, or observations about which you want to make inferences or draw

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Let's break down the steps involved in a structured manner: 1. Clarifying Questions: • What specific change was made to the Google app? • What is the main goal of this change? (e.g., increasing user engagement, improving conversion rates, etc.) • What metrics are relevant to measuring the impact

At Netflix, comparing two users' ranked lists of movie and TV show preferences would involve designing and testing a metric that captures the similarity or dissimilarity between their preferences. The goal would be to create a measure that accurately reflects how closely aligned their tastes are. He

Spotify app. Creating an effective recommendation algorithm for Spotify involves considering a variety of data and metrics to provide personalized and engaging music recommendations to users. Here are some data or metrics that could be used, along with explanations for each: 1. Listening History: A

Support concept on screen. If I am a data scientist working at Uber, to test a new chat product designed for an automated partial refund instead of calling to the support center, I would follow the following process: 1. Clarifying questions: • What is the objective of this new chat product? • W

Young people using social media. As a data scientist at LinkedIn, measuring the success of InMail would involve considering various factors. Here's an overview of how you could approach it: Possible Purpose: The purpose of InMail on LinkedIn is to facilitate communication and networking between pro

Atlassian logo. As a data scientist at Atlassian, measuring the success of Atlassian Confluence would involve considering various aspects. Here's an overview of how you could approach it: Possible Purpose: The purpose of Atlassian Confluence is to provide a collaborative and knowledge-sharing platf

Apple iPhone with Facebook messenger app from app store. As a data scientist at Facebook overseeing Facebook Messenger, here's how I would measure its success: 1) Possible Purpose: The purpose of Facebook Messenger is to provide users with a convenient and seamless platform for messaging, communica

WhatsApp Logo Some of the metrics that could be relevant to WhatsApp's performance and user engagement may include: • Monthly Active Users (MAUs): WhatsApp's MAUs represent the number of unique individuals who use the platform at least once per month. This metric provides insights into the size an

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Let's imagine we're trying to figure out if there are ghosts in a spooky, old house. We use something called "hypothesis testing" to help us decide. 1. Null Hypothesis: This is like our starting guess. We guess that there are no ghosts in the house. So, our null hypothesis is, "There are no ghosts

In simple terms, the standard error is a measure of how much the sample mean (average) is likely to vary from the true population mean. It tells us how uncertain or "noisy" our estimate of the population mean is based on a sample. Formula for the standard error of the mean (SE): SE = (σ / √n) where

In statistics, skewness measures the asymmetry of the probability distribution of a random variable. There are two main types of skewness: right (positive) skewness and left (negative) skewness. 1. Right (Positive) Skewness: • Right skewness occurs when the tail on the right side of the probabilit

Instagram App. Ranking the Instagram Feed is a crucial task that involves balancing user engagement, content relevance, and business objectives. The goal is to create a personalized and engaging user experience while also ensuring that the platform generates revenue and maintains user trust. Here's

A/B Test Illustration. As a data scientist evaluating the outcome of an experiment where 5% of one group clicks more, I would need to consider several factors before determining whether this result is good and whether to proceed with launching based on this outcome. Here's a step-by-step approach I

Facebook app on the Apple iPhone display and desktop version of Facebook on the Apple Macbook. 1) Clarifying Questions: Before proceeding, I would ask a few clarifying questions to understand the scope and context of the project: • What specific aspects of the Instagram UI are you looking to implem

Spotify music. Several factors contribute to the success of a Spotify playlist. Here are some key elements: 1. Curation and Theme: A successful Spotify playlist typically has a clear theme or concept that resonates with a specific target audience. It could be a specific genre, mood, or activity-bas

Close up to a person driving and using navigation app - Google Maps. Clarifying Questions: • When did the drop in daily active users occur? • Was the drop in usage consistent across all regions and demographics? • What was the average time spent on the app before and after the drop in usage? Pro

Linkedin website on a computer screen. As a data scientist at LinkedIn working on the "People You May Know" algorithm, I would consider a variety of data and metrics to create a robust and effective recommendation system. Here are some key factors that could be used, along with detailed explanations

Website of Atlassian Jira on phone screen. As a data scientist at Atlassian, measuring the success of Atlassian JIRA would involve considering several key aspects. Here's a breakdown of how I would approach it: 1) Possible Purpose: The purpose of Atlassian JIRA is to provide a powerful and customiz

Facebook Ads logo on smartphone. As a data scientist at Facebook, measuring the success of Facebook Ads involves considering various factors. Here's an overview of how you could approach it: 1) Possible Purpose: The purpose of Facebook Ads is to provide an effective advertising platform for busines

A person holding smartphone with Whatsapp Business app on an Android Google Play Store. As a data scientist at Facebook overseeing WhatsApp Business Messaging, measuring its success involves several aspects. Here's a breakdown of each element you mentioned: 1) Possible Purpose: The purpose of Whats

Instagram Reels. As a data scientist at Instagram, here's how I would measure the success of Instagram Reels: 1) Possible Purpose: The purpose of Instagram Reels is to provide users with a creative and engaging way to share short-form video content. It aims to capture users' attention, increase the