Data Science FREE Data Science Analysis Question and Answers 2 — Questions and Answers
Question 1: Which technique is most appropriate for reducing the dimensionality of a dataset while preserving the maximum variance?
- Principal Component Analysis (PCA) (Correct answer)
- K-Means Clustering
- Linear Regression
- Decision Trees
Correct answer: Principal Component Analysis (PCA)
PCA projects data onto orthogonal components that capture the most variance, making it the standard technique for dimensionality reduction.
Question 2: In exploratory data analysis, what does a right-skewed distribution indicate about the data?
- The tail extends toward higher values with most data concentrated on the left (Correct answer)
- The data is uniformly distributed
- The mean is less than the median
- The distribution has no outliers
Correct answer: The tail extends toward higher values with most data concentrated on the left
A right-skewed distribution has a longer tail on the right side, meaning most observations cluster at lower values while fewer extreme high values pull the tail rightward.
Question 3: When performing A/B testing, what is the primary purpose of calculating statistical power before running the experiment?
- To determine the minimum sample size needed to detect a meaningful effect (Correct answer)
- To calculate the p-value threshold
- To choose between parametric and non-parametric tests
- To measure the effect size after the experiment
Correct answer: To determine the minimum sample size needed to detect a meaningful effect
Statistical power analysis before an experiment determines the sample size required to reliably detect an effect of a given size at a specified significance level.
Question 4: Which metric is most appropriate for evaluating a classification model when the dataset has a severe class imbalance (e.g., 95% negative, 5% positive)?
- Area Under the Precision-Recall Curve (AUPRC) (Correct answer)
- Accuracy
- R-squared
- Mean Absolute Error
Correct answer: Area Under the Precision-Recall Curve (AUPRC)
AUPRC focuses on the performance of the minority class and is more informative than accuracy when class distribution is highly imbalanced.
Question 5: What is the main risk of using too many features relative to the number of observations in a regression model?
- Overfitting, where the model captures noise rather than the true signal (Correct answer)
- Underfitting, where the model is too simple
- Increased bias in parameter estimates
- Slower convergence of gradient descent
Correct answer: Overfitting, where the model captures noise rather than the true signal
When features outnumber observations, the model can perfectly fit training data including its noise, leading to poor generalization on new data.
Question 6: In time series analysis, what does the Augmented Dickey-Fuller (ADF) test assess?
- Whether the series is stationary or contains a unit root (Correct answer)
- Whether the series follows a normal distribution
- Whether two time series are cointegrated
- Whether seasonal patterns are present
Correct answer: Whether the series is stationary or contains a unit root
The ADF test checks for the presence of a unit root in a time series, where rejecting the null hypothesis indicates the series is stationary.
Data Science FREE Data Science Analysis Question and Answers 2
Which technique is most appropriate for reducing the dimensionality of a dataset while preserving the maximum variance?