DA0-002 Data Analysis Practice Test 9 — 15 Questions

Question 1

A data analyst is cleaning a dataset and finds that the 'age' column has several missing values. Which of the following is a valid method for handling missing numerical data?

Accepted Answer

Impute with the mean. Mean imputation is a common method for handling missing numerical data, though median or mode can also be used.

Answer

Delete the entire column

Answer

Ignore the missing values

Answer

Replace with zeros

Question 2

An analyst is conducting an A/B test to compare two website designs. The null hypothesis is that there is no difference in conversion rates. The p-value obtained is 0.03, and the significance threshold is 0.05. What should the analyst conclude?

Accepted Answer

Reject the null hypothesis; there is a significant difference.. Since p-value (0.03) < α (0.05), we reject the null hypothesis, indicating a statistically significant difference.

Answer

Accept the alternative hypothesis that the new design is better.

Answer

The test is inconclusive; need a larger sample size.

Answer

Fail to reject the null hypothesis; there is no significant difference.

Question 3

In time series decomposition, a data analyst separates a retail sales series into trend, seasonal, and residual components. After decomposition, the residual component shows no pattern and is random. Which of the following best describes the seasonal component?

Accepted Answer

Regular patterns that repeat at fixed intervals.. Seasonality refers to regular, periodic patterns that repeat at fixed intervals (e.g., monthly, quarterly).

Answer

Cyclical variations lasting more than a year.

Answer

Irregular fluctuations that cannot be predicted.

Answer

A long-term increase or decrease in sales.

Question 4

A data analyst needs to identify outliers in a dataset. Which of the following is a common method based on the interquartile range (IQR)?

Accepted Answer

Values below Q1 - 1.5*IQR or above Q3 + 1.5*IQR. A common rule is to consider any data point below Q1 - 1.5*IQR or above Q3 + 1.5*IQR as an outlier.

Answer

Values more than 2 standard deviations from the mean

Answer

Values that are negative

Answer

Values below the 5th percentile or above the 95th percentile

Question 5

A data analyst is evaluating a multiple regression model with three predictors. The R² value is 0.85. Which of the following is the best interpretation of R²?

Accepted Answer

85% of the variance in the outcome is explained by the predictors.. R² represents the proportion of variance in the dependent variable explained by the independent variables. 0.85 means 85% of the variance is explained.

Answer

85% of the predicted values are correct.

Answer

The model has a high bias.

Answer

The model has a strong correlation of 0.85.

Question 6

A data analyst is performing a chi-square test of independence on a contingency table of customer satisfaction (satisfied vs. dissatisfied) and product type (A, B, C). The test yields a p-value of 0.04 with α = 0.05. What is the correct conclusion?

Accepted Answer

There is a significant association between satisfaction and product type.. Since p-value < α, we reject the null hypothesis of independence, meaning there is a significant association between satisfaction and product type.

Answer

There is no evidence of an association between satisfaction and product type.

Answer

The test is invalid because the expected counts are too low.

Answer

Satisfaction and product type are independent.

Question 7

A data analyst is working with a dataset that includes a column 'income' with values ranging from 20,000 to 150,000. To standardize this variable for a linear regression that assumes normally distributed residuals, which method should be used?

Accepted Answer

Z-score standardization. Z-score standardization transforms data to have mean 0 and standard deviation 1, which is suitable for algorithms that assume normality (like linear regression).

Answer

Log transformation

Answer

Min-max normalization

Answer

Square root transformation

Question 8

A data analyst is preparing a dataset for analysis and needs to ensure data quality. Which TWO of the following are dimensions of data quality?

Accepted Answer

Consistency. Accuracy and consistency are recognized dimensions of data quality in CompTIA Data+.

Answer

Volume

Answer

Velocity

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Variety

Question 9

A data analyst is performing K-means clustering on customer data. Which THREE of the following are steps in the K-means algorithm?

Accepted Answer

Initialize k centroids randomly.. K-means involves initializing centroids, assigning points to nearest centroid, and updating centroids as the mean of assigned points.

Answer

Perform eigenvalue decomposition.

Answer

Calculate the correlation matrix.

Question 10

An analyst is preparing data for an A/B test and wants to ensure valid results. Which TWO of the following should be considered when calculating the required sample size?

Accepted Answer

Desired effect size. Sample size calculation depends on desired effect size and statistical power, among other factors like significance level.

Answer

Data dimensionality

Answer

Skewness of data

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Number of features

Question 11

A data analyst is analyzing customer purchase amounts. The dataset contains several extreme high values due to luxury purchases. Which measure of central tendency is most robust to these outliers?

Accepted Answer

Median. The median is not affected by extreme values, making it robust to outliers.

Answer

Range

Answer

Mean

Answer

Mode

Question 12

In A/B testing, the null hypothesis typically states that:

Accepted Answer

There is no difference between the control and treatment groups. The null hypothesis (H0) is a statement of no effect or no difference between groups.

Answer

The treatment group will perform better than the control group

Answer

The sample size is sufficient for the test

Answer

There is a significant difference between the control and treatment groups

Question 13

A data scientist is performing K-means clustering on customer data. She plots the within-cluster sum of squares (WCSS) for different values of k and observes an 'elbow' at k=4. What does this indicate?

Accepted Answer

The optimal number of clusters is 4. The elbow method suggests that adding more clusters beyond k=4 yields diminishing returns, so k=4 is a suitable number of clusters.

Answer

The algorithm should be run with k=3 to avoid overfitting

Answer

The data contains exactly 4 outliers

Answer

The WCSS is minimized at k=4, indicating perfect clustering

Question 14

A data analyst is asked to compare the average sales across three different store locations. The data is normally distributed and variances are approximately equal. Which statistical test is most appropriate?

Accepted Answer

ANOVA. ANOVA is used to compare means of three or more groups when assumptions of normality and equal variance are met.

Answer

Pearson correlation

Answer

Chi-square test

Answer

Two-sample t-test

Question 15

In simple linear regression, the coefficient of determination R² measures:

Accepted Answer

The proportion of variance in the dependent variable explained by the independent variable. R² indicates the proportion of variance in the dependent variable explained by the independent variable.

Answer

The probability that the slope is zero

Answer

The slope of the regression line

Answer

The strength and direction of the linear relationship