Prepare for and practice interview questions from Bausch + Lomb.

Bausch + Lomb Interview Questions

Bausch + Lomb Interview Guides

Machine Learning

How would you build a job recommendation feed?

Job Recommendation

Write a function calculate_rmse to calculate the root mean squared error from y_pred and y_true

RMS Error

Lasso vs Ridge

In which case would you use a bagging algorithm versus a boosting algorithm

Bagging vs Boosting

What are some machine learning methods for building this system

FAQ Matching

Data Structures & Algorithms

Given an integer N, write a function that returns all of the prime numbers up to N

Prime to N

Write a function moving_window to find the moving window average

Moving Window

Given a json string with nested objects, write a function that flattens all the objects to a single key-value dictionary.

Flatten JSON

Write a function str_map to determine if there exists a one-to-one correspondence between characters of string1 and string2

String Mapping

Write a function `sorting` from scratch to sort a list of strings in ascending alphabetical order

Sort Strings

Select the 2nd highest salary in the engineering department

2nd Highest Salary

Write a query that returns all neighborhoods that have 0 users.

Empty Neighborhoods

Last Transaction

Flight Records

Write a SQL query that creates a cumulative distribution of the number of comments per user with bin buckets of one

Cumulative Distribution

Statistics

Explain what a p-value is to someone who is not technical

P-value to a Layman

How many more samples are needed to decrease the margin of error to 0.3

Reducing Error Margin

What are the assumptions of linear regression?

Assumptions of Linear Regression

What is the downside of only using the R-Squared (R^2) value to determine a relationship between two variables

Using R Squared

Explain the difference between covariance and correlation and provide an example

Covariance vs Correlation

Business Case

Friend Requests Down

How would you approach valuing the benefit of keeping this show on Netflix

Licensing Valuation

How would you decide whether Google should build a game feature for Google Home

Game Feature Home

What would be your recommendation on utilizing a customer success manager versus just a free trial to get new or existing customers to use the new product

Customer Success vs. Free Trial

How would you design a system that offers college students with recommendations that maximize the value of their education?

Value of College

<p>We’re given two tables, a <code>users</code> table with demographic information and the neighborhood they live in and a <code>neighborhoods</code> table.</p>

<p>Write a query that returns all neighborhoods that have 0 users. </p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><code>users</code> table</p>

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>neighborhood_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
<p><code>neighborhoods</code> table</p>

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>city_id</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>


<p>Write a SQL query to select the 2nd highest salary in the engineering department.</p>

<p><strong>Note:</strong> If more than one person shares the highest salary, the query should select the next highest salary.</p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><code>employees</code> table</p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>first_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>last_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>salary</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>department_id</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<p><code>departments</code> table</p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>salary</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>


<p>Given the two tables, write a SQL query that creates a cumulative distribution of the number of comments per user. Assume bin buckets class intervals of one.</p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><code>users</code> table</p>

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>neighborhood_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>sex</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>
<p><code>comments</code> table</p>

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>body</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>frequency</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>cum_total</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>


<p>Let’s say that your company is running a standard control and variant AB test on a feature to increase conversion rates on the landing page. The PM checks the results and finds a .04 p-value.</p>

<p>How would you assess the validity of the result?</p>


How would you assess the validity of the result?

Experiment Validity

A/B Testing

<p>Given an integer <code>N</code>, write a function that returns a list of all of the prime numbers up to <code>N</code>.</p>

<p><em>Note: Return an empty list there are no prime numbers less than or equal to <code>N</code>.</em></p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="n">N</span> <span class="o">=</span> <span class="mi">3</span>
</span></span></code></pre>

<p><strong>Output:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="k">def</span> <span class="nf">prime_numbers</span><span class="p">(</span><span class="n">N</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="p">[</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">]</span>
</span></span></code></pre>


<p>Let’s say you work at an advertising firm. You have a table of users’ impressions of ad campaigns over time. Each <code>impression_id</code> consists of values of user engagement specified by <code>Excited</code>, <code>OK</code>, and <code>Bored</code>.</p>

<p>Write a query to find all users who were at some point “Excited” and have never been “Bored” with a campaign.</p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><code>ad_impressions</code> table:</p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>dt</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>campaign_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>impression_id</code></td>
<td>TEXT</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>


Write a query to find all users that were at some point "Excited" and have never been "Bored" with a campaign.

Always Excited Users

<p>Tell me about a data project that didn’t go the way you expected. What did you set out to do, what surprised you, and how did you handle it?</p>


Describing a data project and its challenges

Hurdles In Data Projects

Behavioral

<p>Given a table of bank transactions with columns <code>id</code>, <code>transaction_value</code>, and <code>created_at</code> representing the date and time for each transaction, write a query to get the last transaction for each day.</p>

<p>The output should include the id of the transaction, datetime of the transaction, and the transaction amount. Order the transactions by datetime.</p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><code>bank_transactions</code> table</p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>transaction_value</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>transaction_value</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>


<p>How would you explain what a p-value is to someone who is not technical?</p>


<p>What does a p-value in a statistical test represent?</p>

What does a p-value in a statistical test represent?

P-value to a Layman I

<p>In a statistical test, how does a low p-value (less than 0.05) influence our decision about the null hypothesis?</p>

In a statistical test, how does a low p-value (less than 0.05) influence our decision about the null hypothesis?

P-value to a Layman II

<p>The probability that it will rain tomorrow is dependent on whether or not it is raining today and whether or not it rained yesterday.</p>

<p>If it rained yesterday and today, there is a 20% chance it will rain tomorrow. If it rained one of the days, there is a 60% chance it will rain tomorrow. If it rained neither today nor yesterday, there is a 20% chance it will rain tomorrow.</p>

<p>Given that it is raining today and that it rained yesterday, write a function <code>rain_days</code> to calculate the probability that it will rain on the nth day after today.</p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="n">n</span><span class="o">=</span><span class="mi">5</span>
</span></span></code></pre>

<p><strong>Output:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="k">def</span> <span class="nf">rain_days</span><span class="p">(</span><span class="n">n</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="mf">0.39968</span>
</span></span></code></pre>


Given that it is raining today and that it rained yesterday, write a function to calculate the probability that it will rain on the nth day after today.

Rain in N Days

Probability

<p>A team wants to A/B test multiple different changes through a sign-up funnel.</p>

<p>For example, on a page, a button is currently red and at the top of the page. They want to see if changing a button from red to blue and/or from the top of the page to the bottom of the page will increase click-through.</p>

<p>How would you set up this test?</p>


<p>Your team wants to run an AB test on the color (red or blue) and position (top/bottom of the page) of a button that links to a promotion.</p>

<p>How many different variants of the test should you run to see the effect that a red button has on the bottom of the page, if currently the button is blue and on the top of the page.</p>


Your team wants to run an AB test on the color (red or blue) and position (top/bottom of the page) of a button that links to a promotion.

How many different variants of the test should you run to see the effect that a red button has on the bottom of the page, if currently the button is blue and on the top of the page.

A/B Test Variants

Button AB Test

<p>Write a query to create a new table, named flight routes, that displays unique pairs of two locations.</p>

<p><em>Note: Duplicate pairs from the <code>flights</code> table, such as Dallas to Seattle and Seattle to Dallas, should have one entry in the flight routes table.</em></p>

<h3>Schema</h3>

<p><code>flights</code> table</p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>source_location</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>destination_location</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>destination_one</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>destination_two</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>

<h3>Example</h3>

<p><strong>Input:</strong></p>

<p><strong><code>flights</code> table</strong></p>

<table>
<thead>
<tr>
<th>id</th>
<th>source_location</th>
<th>destination_location</th>
</tr>
</thead>

<tbody>
<tr>
<td>1</td>
<td>Seattle, WA</td>
<td>Dallas, TX</td>
</tr>

<tr>
<td>2</td>
<td>Dallas, TX</td>
<td>Seattle, WA</td>
</tr>

<tr>
<td>3</td>
<td>Seattle, WA</td>
<td>San Francisco, CA</td>
</tr>

<tr>
<td>4</td>
<td>San Francisco, CA</td>
<td>Dallas, TX</td>
</tr>

<tr>
<td>5</td>
<td>San Francisco, CA</td>
<td>Portland, OR</td>
</tr>

<tr>
<td>6</td>
<td>Seattle, WA</td>
<td>Dallas, TX</td>
</tr>

<tr>
<td>7</td>
<td>Portland, OR</td>
<td>San Francisco, CA</td>
</tr>

<tr>
<td>8</td>
<td>San Francisco, CA</td>
<td>Los Angeles, CA</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

<table>
<thead>
<tr>
<th>destination_one</th>
<th>destination_two</th>
</tr>
</thead>

<tbody>
<tr>
<td>Dallas, TX</td>
<td>Seattle, WA</td>
</tr>

<tr>
<td>Portland, OR</td>
<td>San Francisco, CA</td>
</tr>

<tr>
<td>San Francisco, CA</td>
<td>Seattle, WA</td>
</tr>

<tr>
<td>Dallas, TX</td>
<td>San Francisco, CA</td>
</tr>

<tr>
<td>Los Angeles, CA</td>
<td>San Francisco, CA</td>
</tr>
</tbody>
</table>


<p>Let’s say you work at Costco. Costco has a database with two tables. The first is <code>users</code> composed of user information, including their registration date, and the second is <code>purchases</code> that has the entire item purchase history (if any) for those users.</p>

<p>Write a query to get the total amount spent on each item in the ‘purchases’ table by users that registered in 2022.</p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><code>users</code> table</p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>user_name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>registration_date</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
<p><code>purchases</code> table</p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>order_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>item</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>price</code></td>
<td>FLOAT</td>
</tr>

<tr>
<td><code>purchase_date</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>item</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>total_amount_spent</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>


Total Spent on Products

<p>Let’s say we’re comparing two machine learning algorithms. In which case would you use a bagging algorithm versus a boosting algorithm? </p>

<p>Give an example of the tradeoffs between the two.</p>


<p>In machine learning, when would you use a bagging algorithm over a boosting algorithm?</p>


In machine learning, when would you use a bagging algorithm over a boosting algorithm?

Bagging vs. Boosting

<p>Let’s say that you’re working on a job recommendation engine. You have access to all user Linkedin profiles, a list of jobs each user applied to, and answers to questions that the user filled in about their job search.</p>

<p>Using this information, how would you build a job recommendation feed?</p>


<p>What problem can arise in job recommendation systems with regard to initial recommendations?</p>

What problem can arise in job recommendation systems with regard to initial recommendations?

<p>Given a <code>users</code> table, write a query to get the cumulative number of new users added by the day, with the total reset every month. </p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<p><code>users</code> table</p>

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

<table>
<thead>
<tr>
<th>DATE</th>
<th>INTEGER</th>
</tr>
</thead>

<tbody>
<tr>
<td>2020-01-01</td>
<td>5</td>
</tr>

<tr>
<td>2020-01-02</td>
<td>12</td>
</tr>

<tr>
<td>…</td>
<td>…</td>
</tr>

<tr>
<td>2020-02-01</td>
<td>8</td>
</tr>

<tr>
<td>2020-02-02</td>
<td>17</td>
</tr>

<tr>
<td>2020-02-03</td>
<td>23</td>
</tr>
</tbody>
</table>


Given a users table, write a query to get the cumulative number of new users added by the day, with the total reset every month. 

Cumulative Reset

<p>Say you are tasked with designing a data mart or data warehouse for a new online retailer.</p>

<p>How would you design the system?</p>

<p><em>Note: Sketch a star schema to explain your design.</em></p>


Design a data warehouse for a new online retailer

Retailer Data Warehouse

Data Modeling

<p>Let’s say you’re interning at a fintech startup that’s building a platform for online games of chance. During testing, one of your simulations flips a coin 10 times and gets 8 tails and 2 heads.</p>

<p>How would you determine if the coin is fair, and what statistical approach would you use to support your conclusion?</p>


How would you assess if a coin is fair after observing 8 tails in 10 flips?

Fair Coin

<p>Write a function <code>calculate_rmse</code> to calculate the root mean squared error of a regression model. The function should take in two lists, one that represents the predictions <code>y_pred</code> and another with the target values <code>y_true</code>.</p>

<p><strong>Input:</strong></p>

<p><strong>Example 1: </strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="n">y_pred</span> <span class="o">=</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">5</span><span class="p">]</span>
</span></span><span class="line"><span class="cl"><span class="n">y_true</span> <span class="o">=</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">5</span><span class="p">]</span>
</span></span><span class="line"><span class="cl">
</span></span><span class="line"><span class="cl"><span class="k">def</span> <span class="nf">calculate_rmse</span><span class="p">(</span><span class="n">y_pred</span><span class="p">,</span><span class="n">y_true</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="mi">0</span>
</span></span></code></pre>

<p><strong>Example 2:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="n">y_pred</span> <span class="o">=</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">5</span><span class="p">]</span>
</span></span><span class="line"><span class="cl"><span class="n">y_true</span> <span class="o">=</span> <span class="p">[</span><span class="mi">5</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">3</span><span class="p">]</span>
</span></span><span class="line"><span class="cl">
</span></span><span class="line"><span class="cl"><span class="k">def</span> <span class="nf">calculate_rmse</span><span class="p">(</span><span class="n">y_pred</span><span class="p">,</span><span class="n">y_true</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="mf">1.63</span>
</span></span></code></pre>


<p>Let’s say you’re a Product Data Scientist at Instagram. How would you measure the success of the Instagram TV product?</p>


<p>What is the primary goal of Instagram TV as a product feature?</p>

What is the primary goal of Instagram TV as a product feature?

Instagram TV Success

How would you measure the success of the Instagram TV product

Product Sense & Metrics

<p>Let’s say we have a sample size of $n$. The margin of error for our sample size is 3.</p>

<p>How many more samples would we need to decrease the margin of error to 0.3?</p>


<p>Let's say we have a sample size of N. The margin of error for our sample size is 3.</p>

How many more samples would we need to decrease the margin of error to 0.3?

Let's say we have a sample size of N. The margin of error for our sample size is 3.

How many more samples would we need to decrease the margin of error to 0.3?

<p>Let’s say that you work for an E-commerce store. A new marketing manager joins the company and redesigns the existing new-user email journey to try and boost customer conversion rates. A few weeks after launching the new email journey, the new-user to customer conversion rate goes up from 40% to 43%.</p>

<p>Before you can celebrate, the company’s CMO points out a troubling fact. Just a few months prior to the new manager starting the conversion rate already stood at 45%, before slowly dropping down to the “starting” 40%.</p>

<p>How would you investigate if the redesigned email campaign actually led to the increase in the conversion rate, and that the increase wasn’t instead the result of other factors?</p>


<p>What would be an appropriate method to investigate whether the redesigned email campaign led to an increase in the conversion rate of an E-commerce store, in the absence of infrastructure for an AB test?</p>

What would be an appropriate method to investigate whether the redesigned email campaign led to an increase in the conversion rate of an E-commerce store, in the absence of infrastructure for an AB test?

Causal Email Journey

How would you find out if an increase in user conversion rates after a new email journey is casual or just part of a wider trend?

Causal Email Journey 

Analytics

<p>How would you measure the success of Facebook Groups?</p>


<p>Considering the purpose of Facebook Groups as a platform for connecting users through shared interests or real-life relationships, which metrics would be appropriate to measure the success of these groups?</p>


Considering the purpose of Facebook Groups as a platform for connecting users through shared interests or real-life relationships, which metrics would be appropriate to measure the success of these groups?

Group Success

How would you measure the success of Facebook Groups

<p>A digital health startup is analyzing ECG sensor data captured from wearable heart monitors. Each row in the dataset represents one heartbeat, including its timestamp and calculated heart rate at that moment.</p>

<p>The clinical team wants to detect tachycardia runs, periods where a patient’s heart rate stays above 100 bpm continuously for at least 10 seconds .</p>

<p>Write a SQL query to identify every valid tachycardia run and return:</p>

<ol>
<li><code>patient_id</code></li>
<li><code>run_start</code>: timestamp of the first beat in the run</li>
<li><code>run_end</code>: timestamp of the last beat in the run</li>
<li><code>duration_seconds</code>: difference in seconds between start and end (rounded to 2 decimals)</li>
</ol>

<p>Sort results by <code>patient_id</code>, then <code>run_start</code>.</p>

<p><strong>Definition of a Tachycardia Run</strong></p>

<ul>
<li>All consecutive heartbeats must have <code>heart_rate &gt; 100</code></li>
<li>Total duration ≥ 10 seconds</li>
<li>Any gap ≥ 3 seconds between consecutive beats breaks the run</li>
</ul>

<p><strong><em>Note:</em></strong> <em>A patient may have multiple separate runs.</em></p>

<p><strong>Schema</strong></p>

<p><strong>Input</strong></p>

<p><strong><code>ecg_readings</code> table</strong></p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td>patient_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>timestamp</td>
<td>DATETIME</td>
</tr>

<tr>
<td>heart_rate</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<p><strong>Output</strong></p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td>patient_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>run_start</td>
<td>DATETIME</td>
</tr>

<tr>
<td>run_end</td>
<td>DATETIME</td>
</tr>

<tr>
<td>duration_seconds</td>
<td>DECIMAL</td>
</tr>
</tbody>
</table>
<p><strong>Example</strong></p>

<p><strong>Input</strong></p>

<p><strong><code>ecg_readings</code> table</strong></p>

<table>
<thead>
<tr>
<th>patient_id</th>
<th>timestamp</th>
<th>heart_rate</th>
</tr>
</thead>

<tbody>
<tr>
<td>1</td>
<td>2025-03-01 10:00:00</td>
<td>98</td>
</tr>

<tr>
<td>1</td>
<td>2025-03-01 10:00:02</td>
<td>105</td>
</tr>

<tr>
<td>1</td>
<td>2025-03-01 10:00:04</td>
<td>110</td>
</tr>

<tr>
<td>1</td>
<td>2025-03-01 10:00:07</td>
<td>108</td>
</tr>

<tr>
<td>1</td>
<td>2025-03-01 10:00:12</td>
<td>107</td>
</tr>

<tr>
<td>1</td>
<td>2025-03-01 10:00:15</td>
<td>85</td>
</tr>

<tr>
<td>1</td>
<td>2025-03-01 10:00:20</td>
<td>120</td>
</tr>

<tr>
<td>1</td>
<td>2025-03-01 10:00:28</td>
<td>122</td>
</tr>
</tbody>
</table>
<p><strong>Output</strong></p>

<table>
<thead>
<tr>
<th>patient_id</th>
<th>run_start</th>
<th>run_end</th>
<th>duration_seconds</th>
</tr>
</thead>

<tbody>
<tr>
<td>1</td>
<td>2025-03-01 10:00:02</td>
<td>2025-03-01 10:00:12</td>
<td>10.00</td>
</tr>
</tbody>
</table>

<h3><strong>Explanation</strong></h3>

<p>The high-rate streak from 10:00:02 to 10:00:12 forms one continuous sequence because each gap between timestamps (2 to 4, 4 to 7, and 7 to 12) is less than three seconds. This creates a valid 10-second run. The later high values at seconds 20 and 28 are separated by an eight-second gap, so they form a different sequence that is shorter than 10 seconds and is therefore ignored.</p>


Identify tachycardia runs where heart rate stays above 100 bpm for at least 10 seconds and return run start, end, and duration

Detecting ECG Tachycardia Runs

<p>Let’s say you work at Allstate. Allstate is running <code>N</code>  online ads right now. The table <code>ads</code> contains all those ads, ranked by popularity via the <code>id</code> column (e.g., the entry with <code>id = 1</code> is the most popular, etc.).</p>

<p>Create a subquery or common table expression named <code>top_ads</code> containing the top 3 ads (by popularity) and return the number of rows that would result from the following operations</p>

<ol>
<li><code>ads INNER JOIN top_ads</code></li>
<li><code>ads LEFT JOIN top_ads</code></li>
<li><code>ads RIGHT JOIN top_ads</code></li>
<li><code>ads CROSS JOIN top_ads</code></li>
</ol>

<p><em>Note: Please make the <code>join_type</code> column in your output have the values <code>inner_join</code>, <code>left_join</code>, etc. for each of their respective join types</em></p>

<p><em>Note: Please return only one query with each number in a different row</em></p>

<p><strong>Example:</strong></p>

<p><strong>Input:</strong></p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>
<p><strong>Output:</strong></p>

<table>
<thead>
<tr>
<th>Column</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>join_type</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>number_of_rows</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>


Create top_ads with the top 3 ads and return the row counts for inner, left, right, and cross joins with ads

Size of Joins

<p>You’re given a string that may contain the characters <strong><code>{</code></strong>, <strong><code>}</code></strong>, <strong><code>[</code></strong>, <strong><code>]</code></strong>, <strong><code>(</code></strong>, and <strong><code>)</code></strong>.</p>

<p><strong>Task:</strong> Verify that the string is balanced. A balanced string is one where every opening character, <strong><code>{</code></strong>, <strong><code>[</code></strong>, or <strong><code>(</code></strong>, has a corresponding closing character, <strong><code>}</code></strong>, <strong><code>]</code></strong>, or <strong><code>)</code></strong>.</p>

<p>Write a function called <strong><code>is_balanced(string: str) -&gt; bool</code></strong> which verifies the balance of a string.</p>

<p><strong>Example:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="n">is_balanced</span><span class="p">(</span><span class="s1">&#39;(())[]</span><span class="si">{}</span><span class="s1">&#39;</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">True</span>
</span></span></code></pre>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="n">is_balanced</span><span class="p">(</span><span class="s1">&#39;{([()</span><span class="si">{}</span><span class="s1">])()}&#39;</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">True</span>
</span></span></code></pre>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="n">is_balanced</span><span class="p">(</span><span class="s1">&#39;</span><span class="si">{}</span><span class="s1">[]())&#39;</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">False</span>
</span></span></code></pre>

<hr/>


Write a function that tests whether a string of brackets is balanced.

The Brackets Problem

<p>A biomedical research lab is studying treatment effectiveness across different brain cancer categories. Each patient is associated with one cancer type and may undergo zero or more treatments. Write a query to perform an aggregated analysis across all cancer categories.</p>

<p>For each cancer type, compute:</p>

<ol>
<li>Total number of patients</li>
<li>Percentage of patients who survived ≥ 12 months

<ul>
<li>Round to 2 decimal places</li>
<li>A “1-year survivor” is defined as <code>survival_months &gt;= 12</code></li>
</ul></li>
<li>Average number of treatments per patient

<ul>
<li>Round to 2 decimal places</li>
<li>Include patients with zero treatments</li>
</ul></li>
</ol>

<p>Sort the results in descending order by survival rate.</p>

<h3><strong>Example 1</strong></h3>

<p><strong>Input :</strong></p>

<p><strong>Table <code>patients</code></strong></p>

<table>
<thead>
<tr>
<th><strong>Column</strong></th>
<th><strong>Type</strong></th>
</tr>
</thead>

<tbody>
<tr>
<td>patient_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>cancer_type</td>
<td>VARCHAR</td>
</tr>

<tr>
<td>survival_months</td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
<p><strong>Table <code>treatments</code></strong></p>

<table>
<thead>
<tr>
<th><strong>Column</strong></th>
<th><strong>Type</strong></th>
</tr>
</thead>

<tbody>
<tr>
<td>treatment_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>patient_id</td>
<td>INTEGER</td>
</tr>

<tr>
<td>treatment_name</td>
<td>VARCHAR</td>
</tr>

<tr>
<td>treatment_date</td>
<td>DATE</td>
</tr>
</tbody>
</table>
<p><strong>Output :</strong></p>

<table>
<thead>
<tr>
<th><strong>Column</strong></th>
<th><strong>Type</strong></th>
</tr>
</thead>

<tbody>
<tr>
<td>cancer_type</td>
<td>VARCHAR</td>
</tr>

<tr>
<td>total_patients</td>
<td>INTEGER</td>
</tr>

<tr>
<td>pct_one_year_survivors</td>
<td>DECIMAL</td>
</tr>

<tr>
<td>avg_treatments_per_patient</td>
<td>DECIMAL</td>
</tr>
</tbody>
</table>

<h3><strong>Example 2</strong></h3>

<p><strong>Input:</strong></p>

<p><strong><code>patients</code> table</strong></p>

<table>
<thead>
<tr>
<th>patient_id</th>
<th>cancer_type</th>
<th>survival_months</th>
</tr>
</thead>

<tbody>
<tr>
<td>1</td>
<td>Glioblastoma</td>
<td>10</td>
</tr>

<tr>
<td>2</td>
<td>Meningioma</td>
<td>24</td>
</tr>

<tr>
<td>3</td>
<td>Astrocytoma</td>
<td>15</td>
</tr>

<tr>
<td>4</td>
<td>Glioblastoma</td>
<td>14</td>
</tr>

<tr>
<td>5</td>
<td>Meningioma</td>
<td>7</td>
</tr>
</tbody>
</table>
<p><strong><code>treatments</code> table</strong></p>

<table>
<thead>
<tr>
<th>treatment_id</th>
<th>patient_id</th>
<th>treatment_name</th>
<th>treatment_date</th>
</tr>
</thead>

<tbody>
<tr>
<td>201</td>
<td>1</td>
<td>Radiation</td>
<td>2024-03-01</td>
</tr>

<tr>
<td>202</td>
<td>1</td>
<td>Chemotherapy</td>
<td>2024-06-01</td>
</tr>

<tr>
<td>203</td>
<td>2</td>
<td>Surgery</td>
<td>2024-02-01</td>
</tr>

<tr>
<td>204</td>
<td>4</td>
<td>Chemotherapy</td>
<td>2024-08-01</td>
</tr>
</tbody>
</table>

<h3><strong>Output:</strong></h3>

<table>
<thead>
<tr>
<th>cancer_type</th>
<th>total_patients</th>
<th>pct_one_year_survivors</th>
<th>avg_treatments_per_patient</th>
</tr>
</thead>

<tbody>
<tr>
<td>Astrocytoma</td>
<td>1</td>
<td>100.00</td>
<td>0.00</td>
</tr>

<tr>
<td>Meningioma</td>
<td>2</td>
<td>50.00</td>
<td>0.50</td>
</tr>

<tr>
<td>Glioblastoma</td>
<td>2</td>
<td>50.00</td>
<td>1.00</td>
</tr>
</tbody>
</table>

<h3><strong>Explanation:</strong></h3>

<p><strong>Astrocytoma</strong></p>

<ul>
<li>Total patients: 1</li>
<li>Survivors: <sup>1</sup>⁄<sub>1</sub> → 100.00%</li>
<li>Treatments: 0 total → 0.00 per patient</li>
</ul>

<p><strong>Meningioma</strong></p>

<ul>
<li>Total patients: 2</li>
<li>Survivors: patient 2 (24 months) → 50.00%</li>
<li>Treatments: 1 total (patient 2) → 0.50 per patient</li>
</ul>

<p><strong>Glioblastoma</strong></p>

<ul>
<li>Total patients: 2</li>
<li>Survivors: patient 4 (14 months) → 50.00%</li>
<li>Treatments: 3 total (2 for patient 1, 1 for patient 4) → 1.00 per patient</li>
</ul>


For each cancer type, compute total patients, percentage surviving at least 12 months, and average treatments per patient

Brain Cancer Treatment Outcomes

<p>Given two strings, write a function to return <code>True</code> if the strings are anagrams of each other and <code>False</code> if they are not.</p>

<p><em>Note: A word is not an anagram of itself.</em></p>

<p><strong>Example 1:</strong></p>

<p><strong>Input:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="n">string_1</span> <span class="o">=</span> <span class="s2">&#34;listen&#34;</span>
</span></span><span class="line"><span class="cl"><span class="n">string_2</span> <span class="o">=</span> <span class="s2">&#34;silent&#34;</span>
</span></span></code></pre>

<p><strong>Output:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="kc">True</span>
</span></span></code></pre>

<p><strong>Example 2:</strong></p>

<p><strong>Input:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="n">string_1</span> <span class="o">=</span> <span class="s2">&#34;banana&#34;</span>
</span></span><span class="line"><span class="cl"><span class="n">string_2</span> <span class="o">=</span> <span class="s2">&#34;bandana&#34;</span>
</span></span></code></pre>

<p><strong>Output:</strong></p>

<pre tabindex="0" class="chroma"><code><span class="line"><span class="cl"><span class="kc">False</span>
</span></span></code></pre>


Write a function to return True if two strings are anagrams of each other and False if they are not

Valid Anagram

<p>How does random forest generate the forest? Additionally, why would we use it over other algorithms such as logistic regression?</p>


<p>What happens when you average the output on multiple decision trees?</p>


What happens when you average the output on multiple decision trees?

Average Trees

How does random forest generate the forest and why use it over logistic regression

Random Forest Explanation

<p>Given that $X$ and $Y$ are independent random variables with normal distributions, what is the mean and variance of the distribution of $2X - Y$ when the corresponding distributions are $X\sim \mathcal{N}(3, 4)$ and $Y \sim \mathcal{N}(1, 4)$?</p>


<p>Given that $X$ and $Y$ are independent random variables with normal distributions, and the corresponding distributions are $X\sim \mathcal{N}(3, 4)$ and $Y \sim \mathcal{N}(1, 4)$, what is the mean of the distribution of $2X - Y$?</p>

Given that $X$ and $Y$ are independent random variables with normal distributions, and the corresponding distributions are $X\sim \mathcal{N}(3, 4)$ and $Y \sim \mathcal{N}(1, 4)$, what is the mean of the distribution of $2X - Y$?

Distribution of 2X - Y I

<p>Given that $X$ and $Y$ are independent random variables with normal distributions, and the corresponding distributions are $X\sim \mathcal{N}(3, 4)$ and $Y \sim \mathcal{N}(1, 4)$, what is the variance of the distribution of $2X - Y$?</p>

Given that $X$ and $Y$ are independent random variables with normal distributions, and the corresponding distributions are $X\sim \mathcal{N}(3, 4)$ and $Y \sim \mathcal{N}(1, 4)$, what is the variance of the distribution of $2X - Y$?

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