{{ extends "global/Page.html" }} {{ block title }}Instructions - Part 1{{ endblock }} {{ block content }}
Imagine you are a member of the hiring committee at a mid-sized company that is looking to hire a new Junior Analyst. The company cares a lot about the true underlying quality of the person they hire—things like analytical skills, communication, reliability, and general problem-solving ability.
Historically, it is known that for candidates who apply for this job, the true quality is normally distributed with mean {{ mu }} and standard deviation {{ sigma }}.
{{ if true_quality_distribution_uri }}Imagine you are a member of the hiring committee at a mid-sized company that is looking to hire a new Junior Analyst. The company cares a lot about the true underlying quality of the person they hire—things like analytical skills, communication, reliability, and general problem-solving ability.
Historically, it is known for the candidates who apply for this job, the true quality is normally distributed with mean {{ mu }} and standard deviation {{ sigma }}.
{{ if true_quality_distribution_uri }}Your Goal: Your goal is to hire the candidate with the highest true quality in each round to maximize your bonus payment.
Funnel: You will evaluate {{ num_candidates }} candidates through a 3-gate funnel: {{ num_candidates }} -> {{ gate1_select }} -> {{ gate2_select }} -> {{ final_select }}.
Final decision: You will see {{ gate2_select }} finalists selected by another participant and choose exactly {{ final_select }} candidate to hire.
{% endif %}Scores you will see: Since you do not know each candidate's exact true quality, your company has collected THREE different evaluation scores:
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{{ form.Q_ultimate_mission }}