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Evaluating University Height Estimation Methods
Which researcher's method is more likely to produce an estimate that is close to the true average height of all 20,000 students? Justify your choice by explaining the critical difference in their data collection strategies and how it affects the resulting single-value estimate.
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General Formula for Prediction via Maximum Probability
Evaluating University Height Estimation Methods
A data scientist is trying to estimate the typical number of daily active users for a new mobile app. They collect data for the first five days: [100, 150, 120, 180, 1000]. The last day was a special promotional event. They consider two different functions to produce a single-value estimate from this data:
- Function A: Calculates the arithmetic average of the five data points.
- Function B: Identifies the middle value after sorting the data points.
Which of the following statements best analyzes the difference between the estimates produced by these two functions in this specific context?
Consider a function designed to produce a single-number estimate of a population's central value from a sample of data. The function works by taking only the minimum and maximum values from the sample and calculating their average. This function is a robust choice for this task, particularly in situations where the sample might contain extreme outliers.