Statistics interview questions
Inference, uncertainty and the ideas that people most often get subtly wrong in interviews.
38 questions in this category.
- What is the generalization of the median?
- The Quantile.
- What is the difference between "long" and "wide" format data?
- Wide: categorical data is grouped in a single row, long: each row is an observation belonging to a particular category.
- Technique used to sample based on a probability where each sample unit is a collection of a cluster element.
- Cluster sampling.
- What is a Type I and a Type II error?
- Basically Type I errors are the False Positive and Type II error are the False Negative.
- What two parameters defined a normal distribution?
- Its mean and its standard deviation.
- In a normal distribution which parameter indicates how wide is the bell?
- The standard deviation.
- What is the difference of and nominal and ordinal feature?
- Nominal data assigns names to each data point without placing it in some sort of order, ex: pass, fail. And ordinal data groups data according to some sort of ranking system: it orders the data, ex: grades A, B, C, D, E and F.
- What does high and low cardinality mean?
- High cardinality refers to columns with values that are very uncommon or unique, example: email addresses, or user names. And low cardinality: refers to columns with few unique values, example: status flags, boolean values.
- What is R-squared?
- R-squared is a statistical measure of how close the data are to the fitted regression line. It is also known as the coefficient of determination.
- What is a residual?
- Is the difference between the observed value and the estimated value of the quantity of interest.
- What is dimensionality reduction?
- It is the process of reducing the number of variables under consideration by obtaining a set of principal variables.
- What is a false negative?
- An example in which the model mistakenly predicted the negative class.
- What is a false positive?
- An example in which the model mistakenly predicted the positive class.
- Precision is the rate between?
- True Positives / (True Positives + False Positives)
- What does stationarity in a dataset means?
- A property of data in a dataset, in which the data distribution stays constant across one or more dimensions. Most commonly, that dimension is time.
- The normal distribution derives its importance from which famous theorem?
- Central Limit Theorem.
- What does MSE mean?
- Mean Square Error.
- What does RMSE mean?
- Root Mean Square Error.
- Name three techniques of dimensionality reduction.
- Singular Value Decomposition (SVD), Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Autoencoders, Fourier and Wavelet Transforms.
- What values could you infer from a boxplot?
- Min, 1 quantile, mean, 3 quantile, max and outliers.
- Is rotation necessary in PCA?
- Yes, rotation is necessary because it maximizes the difference between variance captured by the component.
- What is the difference between covariance and correlation?
- Correlation is the standardized form of covariance.
- Is it possible capture the correlation between continuous and categorical variable?
- Yes, we can use ANCOVA (analysis of covariance) technique to capture association between continuous and categorical variables.
- If pearson correlation is 0 between two variables can we assume that there isn't any relation between them?
- No. Pearson correlation coefficient between 2 variables might be zero even when they have a relationship between them. Example: x and x^2
- Give 3 techniques for handling missing values.
- Delete rows with missing data, Imputation, Predicting the missing values.
- What is the Law of Large Numbers?
- Is a theory that states that as the number of trials increases, the average of the result will become closer to the expected value.
- What is Survivorship bias?
- Is the logical error of concentrating on the people or things that made it past some selection process and overlooking those that did not.
- What is a confounding variable?
- Is a variable that influences both the dependent variable and the independent variable, causing a spurious association.
- What is autocorrelation?
- Is the correlation of a signal with a delayed copy of itself as a function of delay.
- What is MSE?
- MSE stands for Mean Squared Error. And is a measure of how close a fitted line is to data points by measuring the average squared of the errors.
- What is RMSE?
- RMSE stands for Root Mean Squared Error. Is the squared root of MSE.
- How can we select K for K-means?
- Domain knowledge, Elbow method or Average silhouette method.
- What is precision and recall at k?
- Precision at k and recall at k are evaluation metrics for ranking algorithms.