DA0-002 Practice Test 26 — 15 Questions

Question 1

A marketing team runs an A/B test on email subject lines. The p-value is 0.03 with α = 0.05. Which of the following is the correct interpretation?

Accepted Answer

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

Answer

The result is not statistically significant at the 95% confidence level.

Answer

The probability that the null hypothesis is true is 3%.

Answer

Fail to reject the null hypothesis; no significant difference.

Question 2

A time series of monthly sales data exhibits a clear upward trend over several years, with consistent peaks each December. Which components are present in this series?

Accepted Answer

Trend and seasonality. The upward trend is a trend component, and the consistent December peaks indicate seasonality.

Answer

Cyclical and irregular components only

Answer

Seasonality and cyclical components only

Answer

Trend and irregular components only

Question 3

Which data cleaning method involves replacing a missing value with the average of the available values in that column?

Accepted Answer

Mean imputation. Mean imputation replaces missing values with the column mean.

Answer

Interpolation

Answer

Listwise deletion

Answer

Forward-fill

Question 4

A logistic regression model is used to predict the probability of customer churn. The model's coefficient for the feature 'customer support calls' is 0.8 with a p-value of 0.001. Which interpretation is correct?

Accepted Answer

For each additional support call, the log-odds of churn increase by 0.8, and this effect is statistically significant.. In logistic regression, a positive coefficient indicates that as the predictor increases, the log-odds of the outcome increase. The p-value being less than 0.05 indicates the effect is statistically significant.

Answer

The odds of churn are multiplied by 0.8 for each additional call.

Answer

Support calls have no significant effect on churn.

Answer

For each additional support call, the probability of churn increases by 80%.

Question 5

In a regression analysis, the coefficient of determination (R²) is 0.85. How should this value be interpreted?

Accepted Answer

85% of the variance in the dependent variable is explained by the model. R² represents the proportion of variance in the dependent variable that is explained by the independent variable(s). An R² of 0.85 means the model explains 85% of the variability.

Answer

85% of the data points lie on the regression line

Answer

The slope of the regression line is 0.85

Answer

85% of the independent variables are significant

Question 6

A data analyst is examining the distribution of customer ages in a dataset. The ages are: 22, 25, 29, 30, 31, 34, 35, 37, 40, 42, 45, 50, 55, 60, 65. Which measure of central tendency would be least affected by an outlier if a value of 120 is incorrectly recorded as age 120?

Accepted Answer

Median. The median is resistant to outliers because it is the middle value when data are sorted. The mean is sensitive to extreme values, and the mode may not change but is not a robust measure of central tendency. The range is a measure of spread, not central tendency.

Answer

Mode

Answer

Mean

Answer

Range

Question 7

A data scientist is building a K-means clustering model for customer segmentation. After plotting the within-cluster sum of squares (WCSS) against the number of clusters (k), she observes that the WCSS decreases sharply until k=5 and then levels off. Which value of k should she choose based on the elbow method?

Accepted Answer

k=5. The elbow method suggests selecting the number of clusters at the point where the WCSS starts to diminish less rapidly, forming an 'elbow'. Here, the elbow is at k=5, where adding more clusters yields diminishing returns.

Answer

k=6

Answer

k=4

Answer

k=3

Question 8

A data analyst wants to test if the proportion of customers who prefer Product A over Product B is different from 50%. She surveys 200 customers and finds that 120 prefer Product A. Which statistical test should she use?

Accepted Answer

One-sample z-test for proportions. A one-sample z-test for proportions compares a sample proportion to a hypothesized population proportion. Here, the null is p=0.5. A chi-square test for goodness-of-fit could also be used, but the z-test is standard for a single proportion.

Answer

Chi-square test of independence

Answer

ANOVA

Answer

Two-sample t-test

Question 9

A data analyst is performing data cleaning on a dataset and identifies several outliers in the 'age' column. Which TWO methods are appropriate for handling these outliers? (Select two.)

Accepted Answer

Capping. Capping limits extreme values to a threshold, and removal deletes outlier records. Transformation (e.g., log) can reduce impact but is more for skewness. Imputation and binning are for missing data or discretization, not directly for outliers.

Answer

Mean imputation

Answer

Transformation

Answer

Binning

Question 10

Which TWO of the following are measures of central tendency?

Accepted Answer

Median. Mean, median, and mode are measures of central tendency. Range and standard deviation measure dispersion.

Answer

Range

Answer

Variance

Answer

Standard deviation

Question 11

Which TWO of the following data quality dimensions are most directly affected by duplicate records?

Accepted Answer

Uniqueness. Duplicates harm accuracy (incorrect counts) and uniqueness (duplicate entries). Completeness, consistency, timeliness are less directly affected.

Answer

Timeliness

Answer

Consistency

Answer

Completeness

Question 12

An analyst is performing K-means clustering on customer data. The elbow method shows a clear bend at k=4. Which THREE of the following are true about K-means clustering with k=4?

Accepted Answer

The number of clusters is determined to be 4.. K-means initialises centroids randomly, so results can vary. The elbow method suggests 4 clusters. The algorithm minimises within-cluster sum of squares. K-means works best with numeric data and assumes spherical clusters.

Answer

The algorithm will always produce the same clusters regardless of initial centroids.

Answer

Categorical variables should be standardised before clustering.

Question 13

Which TWO of the following are appropriate uses of min-max normalisation?

Accepted Answer

Scaling features to a range of 0 to 1. Min-max normalisation scales data to a fixed range (often 0-1), useful for distance-based algorithms like k-NN and neural networks. Standardisation (Z-score) is better for algorithms assuming Gaussian distribution.

Answer

Transforming data to have mean 0 and standard deviation 1

Answer

Preparing data for linear regression with normally distributed residuals

Answer

Handling missing values

Question 14

The exhibit shows a JSON schema for a dataset. Which statement correctly describes the data types represented?

Accepted Answer

All fields are qualitative. All fields in the dataset are qualitative (categorical or nominal). customer_id is a unique identifier (nominal), education is a categorical variable, age is often grouped into categories (ordinal), and income is typically treated as ordinal when bucketed into ranges. Despite being stored as numbers, age and income are not used for arithmetic in typical data analysis, making them qualitative.

Answer

age and income are continuous; customer_id and education are discrete

Answer

customer_id and age are discrete quantitative; income is continuous quantitative; education is qualitative

Answer

All fields are quantitative

Question 15

During a data presentation, an audience member questions the accuracy of the data shown. Which of the following is the best way for the analyst to respond?

Accepted Answer

Provide documentation of data sources and transformation steps. Providing documentation of data sources and transformation steps directly addresses the audience member's concern about accuracy by demonstrating transparency and traceability. This approach aligns with best practices in data governance, as it allows the audience to verify the data lineage and any ETL processes that may have introduced errors. It also builds trust by showing the analyst has a clear understanding of the data pipeline.

Answer

Change the topic

Answer

Offer to send the raw data later

Answer

Dismiss the question and continue