DA0-002 Data Analysis Practice Test 10 — 15 Questions

Question 1

A dataset contains a feature 'Age' with values ranging from 18 to 95. To prepare data for a k-nearest neighbors algorithm, which transformation should be applied to 'Age'?

Accepted Answer

Min-max normalization. Min-max normalization scales features to a fixed range (e.g., 0-1), which is appropriate for distance-based algorithms like k-NN.

Answer

Z-score standardization

Answer

No transformation needed

Answer

Log transformation

Question 2

A data analyst is testing whether a new website layout increases conversion rate. The p-value from the test is 0.03. Using a significance level of 0.05, what is the correct conclusion?

Accepted Answer

Reject the null hypothesis; the new layout significantly increases conversion rate. Since p-value (0.03) < α (0.05), we reject the null hypothesis and conclude there is a statistically significant difference.

Answer

The test is inconclusive because p-value is greater than 0.01

Answer

Accept the null hypothesis; the new layout has no effect

Answer

Fail to reject the null hypothesis; the new layout does not increase conversion rate

Question 3

In time series analysis, which component represents regular patterns that repeat over fixed periods, such as daily or yearly?

Accepted Answer

Seasonality. Seasonality refers to patterns that repeat at regular intervals.

Answer

Trend

Answer

Cyclical

Answer

Irregular

Question 4

Which data quality dimension ensures that data represents the real-world object or event correctly?

Accepted Answer

Accuracy. Accuracy refers to how well data reflects reality.

Answer

Completeness

Answer

Consistency

Answer

Timeliness

Question 5

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 6

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 7

A data analyst is comparing the means of two independent groups using a t-test. The sample sizes are small and the data is not normally distributed. Which condition is violated for a valid t-test?

Accepted Answer

Normality. The t-test assumes normality of the data, especially with small samples. Violation of normality can affect the validity.

Answer

Equal variances

Answer

Independence of observations

Answer

Sample size larger than 30

Question 8

A data analyst is preparing a dataset for analysis and needs to address data quality issues. Which TWO of the following are common data cleaning tasks?

Accepted Answer

Imputing missing values. Handling missing values and removing duplicates are standard data cleaning tasks.

Answer

Performing hypothesis testing

Answer

Building a regression model

Answer

Calculating correlation coefficients

Question 9

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 10

An analyst is planning an A/B test to compare two website designs. Which TWO factors should be considered when calculating the required sample size?

Accepted Answer

Desired effect size. Statistical power and desired effect size are key inputs for sample size calculations.

Answer

Data type of the outcome variable

Answer

Color scheme of the designs

Answer

Number of missing values

Question 11

A data analyst is summarizing the central tendency of a dataset with extreme outliers. Which measure is most robust to outliers?

Accepted Answer

Median. The median is not affected by extreme values, unlike the mean.

Answer

Standard deviation

Answer

Mean

Answer

Range

Question 12

A data scientist is building a model to predict customer churn (yes/no). After training a logistic regression model, the coefficient for 'monthly charges' is 0.05 with a p-value of 0.03. Which interpretation is correct at α=0.05?

Accepted Answer

For every unit increase in monthly charges, the odds of churn increase by about 5%.. The p-value < 0.05 indicates a statistically significant relationship; the positive coefficient means higher charges increase the log-odds of churn.

Answer

The model's R-squared is 0.05.

Answer

Monthly charges decrease the probability of churn.

Answer

Monthly charges have no significant effect on churn.

Question 13

A dataset contains height measurements in centimeters and inches. An analyst wants to apply k-means clustering. Which data transformation should be applied before clustering?

Accepted Answer

Min-max normalization. Min-max normalization scales features to a range, often [0,1], which is appropriate for distance-based algorithms like k-means.

Answer

Log transformation

Answer

Z-score standardization

Answer

No transformation needed

Question 14

In a simple linear regression model y = 2.5 + 1.2x, what is the predicted value of y when x = 10?

Accepted Answer

14.5. Plug x=10: y = 2.5 + 1.2*10 = 2.5 + 12 = 14.5.

Answer

12.0

Answer

13.7

Answer

10.0

Question 15

A data analyst is performing time series analysis on monthly sales data and notices a consistent pattern of higher sales every December. Which component of time series does this represent?

Accepted Answer

Seasonality. Seasonality refers to regular patterns that repeat at fixed intervals, such as yearly.

Answer

Trend

Answer

Irregular component

Answer

Cyclical