DA0-001 Analysing Data Practice Test 9 — 15 Questions

Question 1

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 2

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 3

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 4

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 5

A stock analyst is analyzing monthly sales data for a retail company and observes a consistent pattern of high sales every December. This pattern is most likely an example of which time series component?

Accepted Answer

Seasonality. Seasonality refers to regular, predictable patterns that repeat at fixed intervals (e.g., yearly, monthly). The consistent December peak indicates a seasonal pattern.

Answer

Irregular

Answer

Cyclical

Answer

Trend

Question 6

In an A/B test, the null hypothesis states that there is no difference between the conversion rates of the control and treatment groups. After collecting data, the p-value is 0.03. Using a significance level α = 0.05, what should the analyst conclude?

Accepted Answer

Reject the null hypothesis; there is a significant difference. Since the p-value (0.03) is less than α (0.05), the null hypothesis is rejected, indicating a statistically significant difference between the groups.

Answer

Accept the alternative hypothesis; the treatment is better

Answer

The test is inconclusive

Answer

Fail to reject the null hypothesis; no significant difference

Question 7

A data analyst is preparing features for a machine learning model that uses distance-based algorithms (e.g., K-means, KNN). The dataset contains numerical features with different scales: age (0-100), income (20,000-200,000), and credit score (300-850). Which data transformation technique is most appropriate to ensure all features contribute equally to the distance calculations?

Accepted Answer

Min-max normalization. Min-max normalization rescales features to a fixed range (e.g., 0 to 1), making distances computed equally weighted. Standardization is better for algorithms assuming Gaussian distributions.

Answer

Z-score standardization

Answer

One-hot encoding

Answer

Log transformation

Question 8

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 9

A dataset contains customer records with a column for 'Phone Number' that should be unique. However, the analyst finds several duplicate phone numbers. Which data quality dimension is primarily affected?

Accepted Answer

Uniqueness. Uniqueness refers to the expectation that each record or attribute value should be unique. Duplicate phone numbers violate uniqueness.

Answer

Completeness

Answer

Accuracy

Answer

Consistency

Question 10

A data analyst is examining the relationship between advertising spend (in thousands) and sales (in thousands). The Pearson correlation coefficient is computed as r = -0.85. Which of the following interpretations is correct?

Accepted Answer

There is a strong negative linear relationship.. Pearson r measures linear correlation: -0.85 indicates a strong negative linear relationship (as one increases, the other decreases). The magnitude |0.85| is close to 1, so strong.

Answer

There is no linear relationship.

Answer

There is a strong positive linear relationship between advertising spend and sales.

Answer

There is a weak negative linear relationship.

Question 11

A data analyst is cleaning a dataset with missing values in a time series of daily temperatures. The missing values occur sporadically. Which imputation method is most appropriate to maintain the temporal trend?

Accepted Answer

Interpolation. Interpolation estimates missing values by using surrounding data points and is suitable for time series with a trend. Forward-fill carries the last observation forward, which may not capture trend well. Mean imputation ignores order.

Answer

Forward-fill

Answer

Mean imputation

Answer

Median imputation

Question 12

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 13

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 14

A company is planning an A/B test to compare two website designs. Which THREE of the following must be determined before the test begins to ensure valid results? (Select three.)

Accepted Answer

The desired effect size. Sample size (based on power and effect size), significance level (α), and desired effect size are all pre-specified to design the test. The p-value is an outcome, not a pre-test parameter. The hypothesis is defined beforehand, but which one is false? Actually null and alternative hypotheses should be pre-specified, but the phrasing 'which one is true' is not determined before; the test determines that. So correct are: determine minimum sample size, determine significance level, and determine desired effect size.

Answer

The p-value of the test

Answer

Which hypothesis is true

Question 15

A data analyst wants to segment customers based on purchasing behavior such as frequency, monetary value, and recency. Which TWO clustering evaluation methods can help determine the optimal number of clusters? (Select two.)

Accepted Answer

Silhouette score. The elbow method uses within-cluster sum of squares, and the silhouette score measures cohesion and separation. Both help choose k. Correlation coefficient is for association, not clustering. ANOVA and t-test are for hypothesis testing.

Answer

Correlation coefficient

Answer

ANOVA

Answer

t-test