Before applying a two-sample t-test to compare the means of a continuous feature between two groups, which assumption about the data distribution should be checked?

Homogeneity of variance across all groups

Normality of the feature within each group

Independence of the two categorical features

Linearity of the relationship between the two features

A data scientist wants to measure the strength and direction of the linear relationship between two continuous features: years of experience and salary. Which statistical method is most appropriate?

Pearson correlation coefficient

A data analyst runs a chi-square test of independence on two categorical features: 'education_level' (high_school, bachelor, master, phd) and 'employment_status' (employed, unemployed). The p-value is 0.06. The analyst wants to draw a conclusion at the 0.05 significance level. What is the most appropriate interpretation?

There is insufficient evidence to conclude an association between education level and employment status.

There is a statistically significant association between education level and employment status.

The test is invalid because the features have different numbers of categories.

The association is strong because the p-value is close to 0.05.

A data scientist is comparing the average response time of three different server configurations (A, B, C). They have 50 response time measurements per configuration. A Shapiro-Wilk test on each group returns p-values of 0.01, 0.03, and 0.02, respectively. What is the most appropriate next step?

Use a t-test for each pair of groups

Transform the data and then use ANOVA

DatabricksCertified Machine Learning Associate

Domain 2Objective 4

Compare Two Categorical or Two Continuous Features Using the Appropriate Method MACHINE-LEARNING-ASSOCIATE Practice Questions (Page 2)

Part of the Section 2: Data Processing domain, which makes up ~27% of our current practice bank. Databricks does not publish an official question count, but from its 90-minute exam (~35–60 total, ~9–16 in this domain), expect 1–2 from this objective — we provide 12 practice questions to prepare you well beyond it. (estimate)

12questions here

3free pages

4concepts

Questions 6–10

6expert · hard
A data scientist is comparing the mean revenue of three marketing campaigns (A, B, C). They have 30 observations per campaign. A Shapiro-Wilk test on each group returns p-values of 0.20, 0.15, and 0.10, respectively. Levene's test returns p = 0.01. What is the most appropriate test?
Select an answer first
7foundation · easy
Before applying a two-sample t-test to compare the means of a continuous feature between two groups, which assumption about the data distribution should be checked?
Select an answer first
8foundation · easy
A data scientist wants to measure the strength and direction of the linear relationship between two continuous features: years of experience and salary. Which statistical method is most appropriate?
Select an answer first
9expert · hard
A data analyst runs a chi-square test of independence on two categorical features: 'education_level' (high_school, bachelor, master, phd) and 'employment_status' (employed, unemployed). The p-value is 0.06. The analyst wants to draw a conclusion at the 0.05 significance level. What is the most appropriate interpretation?
Select an answer first
10application · medium
A data scientist is comparing the average response time of three different server configurations (A, B, C). They have 50 response time measurements per configuration. A Shapiro-Wilk test on each group returns p-values of 0.01, 0.03, and 0.02, respectively. What is the most appropriate next step?
Select an answer first

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Compare Two Categorical or Two Continuous Features Using the Appropriate Method MACHINE-LEARNING-ASSOCIATE Practice Questions (Page 2)

Questions 6–10

A data scientist is comparing the mean revenue of three marketing campaigns (A, B, C). They have 30 observations per campaign. A Shapiro-Wilk test on each group returns p-values of 0.20, 0.15, and 0.10, respectively. Levene's test returns p = 0.01. What is the most appropriate test?

Before applying a two-sample t-test to compare the means of a continuous feature between two groups, which assumption about the data distribution should be checked?

A data scientist wants to measure the strength and direction of the linear relationship between two continuous features: years of experience and salary. Which statistical method is most appropriate?

A data scientist is comparing the average response time of three different server configurations (A, B, C). They have 50 response time measurements per configuration. A Shapiro-Wilk test on each group returns p-values of 0.01, 0.03, and 0.02, respectively. What is the most appropriate next step?

Keep studying — Section 2: Data Processing