1
← Back to quizzesFree quiz
Fundamentals of Statistical Learning
10 questions · Informatik. Review key concepts before taking the quiz
0 / 10
Score: 0%
2
Given a discrete random variable X with pmf f_X(x), which expression correctly relates its CDF to the pmf?
3
In a Bernoulli experiment with unknown success probability θ, the method-of-moments estimator for θ is:
4
For a random vector X = (X1,…,Xk)ᵀ, which statement correctly describes the marginal pdf of Xi when the joint pdf is f_X(x)?
5
Which of the following is the variance decomposition known as the law of total variance?
6
A test statistic T_n = Σ_{j=1}^k (N_j - n p_{0j})^2 / (n p_{0j}) converges in distribution to which of the following under H0?
7
In linear regression, assuming XᵀX is invertible, the least squares estimator β̂ satisfies which equation?
8
For a random variable X with finite mean μ and variance σ², Chebyshev’s inequality provides a bound for P(|X-μ| ≥ t). Which of the following is that bound?
9
When testing H₀: θ = θ₀ versus H₁: θ ≠ θ₀ with an asymptotically normal estimator θ̂, the Wald test rejects H₀ if:
10
In logistic regression, the log‑likelihood gradient can be expressed as Xᵀ (Y - μ(β)). What does μ_i(β) represent?
