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MMMU-Pro / test_Computer_Science_77 / You have a 1-D dataset large {x^{(1)}, ... , x^{(m)} } and you want to…

Problem

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Plots and Charts

options

$\large \mu_1= -8, \large \sigma_1^2= 2$
$\large \mu_1= -6, \large \sigma_1^2= 2$
$\large \mu_1= -3, \large \sigma_1^2= 2$
$\large \mu_1= -1, \large \sigma_1^2= 6$
$\large \mathbf{\mu_1=} -3, \large \mathbf{\sigma_1^2=} 4$
$\large \mu_1= -6, \large \sigma_1^2= 4$
$\large \mu_1= -5, \large \sigma_1^2= 3$
$\large \mu_1= -4, \large \sigma_1^2= 3$
$\large \mu_1= -7, \large \sigma_1^2= 1$
$\large \mu_1= -2, \large \sigma_1^2= 5$

question

You have a 1-D dataset $\large \{x^{(1)}, ... , x^{(m)} \}$ and you want to detect outliers in the dataset. You first plot the dataset and it looks like this:<image 1>Suppose you fit the gaussian distribution parameters $\large \mu_1$ and $\large \sigma_1^2$ to this dataset.Which of the following values for $\large \mu_1$ and $\large \sigma_1^2$ might you get?

Plain-text mathematical notation (without MathML)

You have a 1-D dataset $\large \{x^{(1)}, ... , x^{(m)} \}$ and you want to detect outliers in the dataset. You first plot the dataset and it looks like this:<image 1>Suppose you fit the gaussian distribution parameters $\large \mu_1$ and $\large \sigma_1^2$ to this dataset.Which of the following values for $\large \mu_1$ and $\large \sigma_1^2$ might you get?

Original LaTeX notation

You have a 1-D dataset $\large \{x^{(1)}, ... , x^{(m)} \}$ and you want to detect outliers in the dataset. You first plot the dataset and it looks like this:<image 1>Suppose you fit the gaussian distribution parameters $\large \mu_1$ and $\large \sigma_1^2$ to this dataset.Which of the following values for $\large \mu_1$ and $\large \sigma_1^2$ might you get?

subject

Computer_Science

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Source and history

upstream_id / Original problem ID: test_Computer_Science_77
task_id: 11b69d50-87a7-57ca-a3dc-b33bcaa37e3b
task_key: standard~20~2810~20options~29--test--test~5fComputer~5fScience~5f77
task_revision_id: 1
config / split: standard (10 options) / test

Official source

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