DA0-001 Analysing Data Practice Test 3 — 15 Questions

Question 1

A data analyst is examining sales data for a retail chain and notices that the mean monthly sales is $50,000 while the median is $35,000. Which of the following best describes the distribution of the sales data?

Accepted Answer

The distribution is right-skewed.. When the mean is greater than the median, the distribution is right-skewed (positively skewed) because the mean is pulled towards the higher values by outliers or a long right tail.

Answer

The distribution is bimodal.

Answer

The distribution is left-skewed.

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The distribution is symmetrical.

Question 2

A data analyst is comparing the average test scores of students who attended a tutoring program versus those who did not. Which statistical test is most appropriate for determining if there is a significant difference between the means of these two independent groups?

Accepted Answer

Two-sample t-test. The independent samples t-test is used to compare the means of two independent groups.

Answer

Paired t-test

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Chi-square test

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ANOVA

Question 3

In a linear regression model predicting house prices, the coefficient for the number of bedrooms is $30,000 and the intercept is $50,000. If a house has 3 bedrooms, what is the predicted price?

Accepted Answer

$140,000. Using y = mx + b, predicted price = 30000 * 3 + 50000 = $140,000.

Answer

$80,000

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$150,000

Answer

$90,000

Question 4

A data analyst wants to segment customers into groups based on their purchasing behavior. The dataset includes numerical features such as annual income and purchase frequency. Which algorithm is most appropriate for this task?

Accepted Answer

K-means clustering. K-means clustering is a common algorithm for customer segmentation based on numerical features.

Answer

Linear regression

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Logistic regression

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Chi-square test

Question 5

A data analyst is preparing data for a k-nearest neighbors algorithm. The features include age (0-100) and income (0-200,000). Which technique should be applied to ensure the distance metric is not dominated by income?

Accepted Answer

Min-max normalization. Min-max normalization scales features to a 0-1 range, ensuring each feature contributes equally to distance calculations.

Answer

Log transformation

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Z-score standardization

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One-hot encoding

Question 6

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

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Ignore the missing values

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Replace with zeros

Question 7

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 8

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 9

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

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Values that are negative

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

Question 10

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.

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The model has a high bias.

Answer

The model has a strong correlation of 0.85.

Question 11

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 12

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

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Square root transformation

Question 13

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

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Velocity

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Variety

Question 14

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 15

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

Answer

Number of features