A data analyst computes a Pearson correlation coefficient of -0.8 between study time and error rate. Which interpretation is most appropriate?

There is a strong negative linear relationship: more study time is associated with fewer errors.

There is a weak negative relationship: study time has little effect on errors.

There is a positive relationship: more study time leads to more errors.

Increasing study time causes a decrease in errors.

A machine learning engineer is evaluating a new feature that is expected to improve model accuracy. They run a hypothesis test with a null hypothesis of no improvement and obtain a p-value of 0.06. The business team wants to deploy the feature. Which decision is most appropriate?

Do not deploy based solely on the p-value; consider the cost of a false positive and the effect size.

Deploy the feature because the p-value is not below 0.05, so the null is true.

Do not deploy because the p-value is not below 0.05, regardless of other factors.

Deploy the feature because the p-value is close to 0.05.

A data analyst builds a multiple regression model to predict customer lifetime value (LTV) using age, income, and number of purchases. The model has an R-squared of 0.85, but the coefficient for age is not statistically significant (p=0.20). Which conclusion is most appropriate?

Age may still be useful in the model, but its effect is not statistically significant after controlling for other variables.

The model is invalid because R-squared is too high.

The model is overfitted because age is not significant.

Age should be removed because it is not significant, regardless of R-squared.

GIAC Machine Learning Engineer

Domain 1Objective 4

Statistics Fundamentals GMLE Practice Questions (Page 7)

Part of the Foundational Data Science and Statistics domain, which makes up ~41% of our current practice bank. GIAC (SANS) does not publish an official question count, but from its 180-minute exam (~70–120 total, ~29–49 in this domain), expect 7–12 from this objective — we provide 49 practice questions to prepare you well beyond it. (estimate)

49questions here

10free pages

10concepts

Questions 31–35

31application · medium
A data analyst computes a Pearson correlation coefficient of -0.8 between study time and error rate. Which interpretation is most appropriate?
Select an answer first
32expert · hard
A machine learning engineer is evaluating a new feature that is expected to improve model accuracy. They run a hypothesis test with a null hypothesis of no improvement and obtain a p-value of 0.06. The business team wants to deploy the feature. Which decision is most appropriate?
Select an answer first
33application · medium
A market research firm wants to estimate the average income of residents in a city. They obtain a list of all city blocks and randomly select 20 blocks, then survey every household on those blocks. Which sampling method is being used?
Select an answer first
34expert · hard
A data analyst builds a multiple regression model to predict customer lifetime value (LTV) using age, income, and number of purchases. The model has an R-squared of 0.85, but the coefficient for age is not statistically significant (p=0.20). Which conclusion is most appropriate?
Select an answer first
35foundation · easy
Which probability distribution is most appropriate for modeling the number of customers arriving at a service desk in a fixed time period, assuming arrivals occur independently at a constant average rate?
Select an answer first

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Statistics Fundamentals GMLE Practice Questions (Page 7)

Questions 31–35

A data analyst computes a Pearson correlation coefficient of -0.8 between study time and error rate. Which interpretation is most appropriate?

A machine learning engineer is evaluating a new feature that is expected to improve model accuracy. They run a hypothesis test with a null hypothesis of no improvement and obtain a p-value of 0.06. The business team wants to deploy the feature. Which decision is most appropriate?

A market research firm wants to estimate the average income of residents in a city. They obtain a list of all city blocks and randomly select 20 blocks, then survey every household on those blocks. Which sampling method is being used?

A data analyst builds a multiple regression model to predict customer lifetime value (LTV) using age, income, and number of purchases. The model has an R-squared of 0.85, but the coefficient for age is not statistically significant (p=0.20). Which conclusion is most appropriate?

Which probability distribution is most appropriate for modeling the number of customers arriving at a service desk in a fixed time period, assuming arrivals occur independently at a constant average rate?

Keep studying — Foundational Data Science and Statistics