DA0-002 Practice Exam 56 — 20 Questions

Question 1

A data scientist is conducting an A/B test with a significance level of 0.05. Which three factors should be considered when calculating the required sample size? (Choose THREE)

Accepted Answer

Statistical power (e.g., 0.80). Sample size calculation depends on desired power, effect size, and significance level.

Answer

Seasonality of the data

Answer

Number of clusters in k-means

Question 2

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 3

In a multiple regression model with three predictors, the coefficient for one predictor is 5.2 with a p-value of 0.001. Which of the following is the best interpretation?

Accepted Answer

The predictor has a statistically significant effect on the dependent variable, controlling for other variables.. The coefficient indicates the change in the dependent variable for a one-unit increase in the predictor, holding other predictors constant.

Answer

The predictor explains 5.2% of the variance in the dependent variable.

Answer

A one-unit increase in the predictor decreases the dependent variable by 5.2 units, on average.

Answer

The model is not a good fit because one predictor is significant.

Question 4

A company wants to determine if there is a significant difference in the average sales revenue between two different store layouts. They collect sales data from 30 stores with Layout A and 30 stores with Layout B. Which statistical test is most appropriate for comparing the means of these two independent groups?

Accepted Answer

Two-sample t-test. The two-sample t-test (independent t-test) compares the means of two independent groups. A paired t-test would be for dependent samples, ANOVA for three or more groups, and chi-square for categorical variables.

Answer

ANOVA

Answer

Chi-square test

Answer

Paired t-test

Question 5

An analyst uses K-means clustering on customer purchase data. After plotting the within-cluster sum of squares for different values of k, they observe an elbow at k=4. What is the most appropriate number of clusters?

Accepted Answer

4. The elbow method suggests choosing k where the WSS starts to diminish slowly; that point is the elbow.

Answer

6

Answer

5

Answer

3

Question 6

A data scientist is performing a hypothesis test with a significance level α=0.05. The p-value obtained is 0.03. What should the scientist conclude?

Accepted Answer

Reject the null hypothesis because the p-value is less than the significance level.. Since 0.03 < 0.05, we reject the null hypothesis, indicating statistically significant evidence against it.

Answer

Fail to reject the null hypothesis because the p-value is greater than 0.01.

Answer

The test is inconclusive, need a larger sample size.

Answer

Accept the null hypothesis because the p-value is small.

Question 7

A data analyst notices that a dataset of customer ages has several missing values. Which method for handling missing data is most appropriate if the data is missing completely at random and the analyst wants to preserve sample size?

Accepted Answer

Impute with the mean age. Mean imputation replaces missing values with the mean, preserving sample size, but can bias estimates. However, for MCAR, it is a common simple approach.

Answer

Forward-fill using the previous value

Answer

Replace missing values with zero

Answer

Delete all rows with missing data

Question 8

A data analyst is building a logistic regression model to predict whether a customer will churn (yes/no). Which TWO statements about logistic regression are correct?

Accepted Answer

The output is a probability between 0 and 1.. Logistic regression outputs probabilities between 0 and 1, and can use a sigmoid function. It is a classification algorithm, and coefficients represent log-odds changes.

Answer

It is used only for time series forecasting.

Answer

The dependent variable is continuous.

Answer

It requires normally distributed errors.

Question 9

A marketing analyst wants to predict whether a customer will churn (yes/no) based on account age and monthly charges. Which regression technique is most appropriate?

Accepted Answer

Logistic regression. Logistic regression is used for binary classification problems, outputting probabilities.

Answer

Simple linear regression

Answer

Multiple linear regression

Answer

K-means clustering

Question 10

A data scientist is analyzing a dataset with multiple features and wants to apply k-means clustering to segment customers. She chooses k = 4 based on the elbow method. During the iteration process, which of the following correctly describes a step in the k-means algorithm?

Accepted Answer

Assign each point to the nearest centroid based on Euclidean distance, then update centroids as the mean of points in each cluster.. K-means iteratively assigns each point to the nearest centroid, then recalculates centroids as the mean of points in the cluster.

Answer

Compute the covariance matrix and use principal components to initialize centroids.

Answer

Use hierarchical clustering to determine initial centroids.

Answer

Randomly assign centroids and then compute distances to the cluster medians.

Question 11

A dataset contains a variable 'Income' with many missing values. The analyst decides to impute missing values with the median income of the non-missing values. Which type of imputation is this?

Accepted Answer

Median imputation. Replacing missing values with the median is a form of mean/median/mode imputation.

Answer

Interpolation

Answer

Deletion

Answer

Forward-fill imputation

Question 12

A data team is preparing data for a clustering analysis. Which THREE of the following steps are commonly part of data cleaning?

Accepted Answer

Removing duplicate records. Data cleaning includes handling missing values, outlier treatment, and deduplication.

Answer

Calculating the mean

Answer

Training a regression model

Question 13

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 14

A data analyst is performing a chi-square test for independence between two categorical variables. Which THREE of the following are necessary conditions for the test to be valid?

Accepted Answer

Sample is randomly selected. The chi-square test requires expected frequencies ≥5, random sampling, and independence of observations.

Answer

Variances are equal across groups

Answer

Data is normally distributed

Question 15

A retail company wants to analyze monthly sales data over the past three years to identify long-term trends. Which component of time series analysis is most relevant for this goal?

Accepted Answer

Trend. The trend component represents the long-term direction of the data, which is exactly what the company wants to identify.

Answer

Irregular component

Answer

Cyclical component

Answer

Seasonality

Question 16

A data analyst is cleaning a customer dataset. Which two actions are appropriate for handling duplicate records? (Choose TWO)

Accepted Answer

Remove all rows with identical values in every field. Removing exact duplicates and standardizing identifiers help resolve duplicates.

Answer

Impute missing values with mean

Answer

Delete any row with a duplicate email address

Answer

Apply Z-score standardization

Question 17

A data scientist builds a simple linear regression model to predict house prices based on square footage. The model yields an R-squared value of 0.85. Which statement accurately interprets this result?

Accepted Answer

The model explains 85% of the variability in house prices. R-squared of 0.85 means 85% of the variance in house prices is explained by square footage.

Answer

The slope of the regression line is 0.85

Answer

85% of the data points lie exactly on the regression line

Answer

There is a 85% chance that square footage causes higher prices

Question 18

A data analyst is performing a chi-square test of independence on a contingency table of customer satisfaction (satisfied, neutral, dissatisfied) by region (North, South, East, West). Which THREE of the following are necessary assumptions for the test?

Accepted Answer

The two variables are categorical. Chi-square test requires categorical variables, expected frequencies >=5 in at least 80% of cells, and independence of observations.

Answer

The sample size is greater than 30

Answer

The data must be normally distributed

Question 19

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 20

An analyst wants to compare the mean sales revenue across three different store regions. The data is normally distributed and variances are equal. Which statistical test is most appropriate?

Accepted Answer

ANOVA. ANOVA (Analysis of Variance) is used to compare means of three or more groups.

Answer

Two-sample t-test

Answer

Paired t-test

Answer

Chi-square test