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Derive Coefficient and Covariance in Regression Analysis

Last updated: Mar 29, 2026

Quick Overview

This question evaluates competency in probabilistic reasoning and regression analysis, including correlation constraints, relationships between regression slopes, covariance of order statistics, and change-of-variables for transformed random variables.

  • medium
  • Citadel
  • Statistics & Math
  • Data Scientist

Derive Coefficient and Covariance in Regression Analysis

Company: Citadel

Role: Data Scientist

Category: Statistics & Math

Difficulty: medium

Interview Round: Technical Screen

##### Scenario Assessing knowledge of correlation structure, regression relationships and covariance calculations. ##### Question 1) For three random variables X, Y, Z with identical pairwise correlations ρ, what is the smallest possible value of ρ? 2) In simple linear regression of Y on X, you know R² and the slope coefficient β(y|x). Derive the slope β(x|y) from regressing X on Y. 3) Let X and Y be i.i.d. Uniform(0, 1). Compute Cov(max(X, Y), min(X, Y)). 4) Given a monotone function Y = g(X), derive the pdf of X from the pdf of Y (inverse-function distribution). ##### Hints Use positive-definite covariance matrices, β relations with R², Cov identities, and change-of-variables theorem.

Quick Answer: This question evaluates competency in probabilistic reasoning and regression analysis, including correlation constraints, relationships between regression slopes, covariance of order statistics, and change-of-variables for transformed random variables.

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Citadel
Jul 12, 2025, 6:59 PM
Data Scientist
Technical Screen
Statistics & Math
93
0

Correlation Structure, Regression Slopes, Covariance of Order Statistics, and Change-of-Variables

You are given standard random variables and asked to assess correlation constraints, regression relationships, a covariance involving order statistics, and a change-of-variables result. Assume variables have finite second moments and differentiability where needed.

Answer all parts:

  1. Three random variables X, Y, Z have identical pairwise correlations ρ. What is the smallest possible value of ρ?
  2. In simple linear regression of Y on X, you know R² and the slope coefficient from regressing Y on X. Derive the slope coefficient from regressing X on Y.
  3. Let X and Y be i.i.d. Uniform(0, 1). Compute the covariance between the maximum and minimum of X and Y.
  4. Suppose Y = g(X), where g is monotone (strictly increasing or decreasing) and differentiable. Given the pdf of Y, derive the pdf of X (the inverse-function distribution result).

Solution

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