A data scientist is investigating the duration of sessions, SSS, on a new mobile application. The underlying distribution of SSS is heavily skewed towards shorter sessions and is certainly not normal, though it possesses a finite mean μ\muμ and a finite standard deviation σ\sigmaσ. For a large random sample of nnn sessions, the scientist utilizes the Central Limit Theorem to approximate the distribution of the sample mean session duration, Sˉ\bar{S}Sˉ.
Formulate the Central Limit Theorem in this specific context, explicitly stating the parameters of the resulting distribution and all conditions that must be satisfied for this approximation to be valid.
390 exam-style questions on OCR (MEI) A Level Maths 2.4 Probability Distributions, covering 2.4.1 Recognise binomial situations, 2.4.2 Probability of success p, 2.4.3 Calculate binomial probabilities, 2.4.4 Mean of the binomial distribution, 2.4.5 Expected frequencies for binomial, 2.4.6 Probability functions and discrete random variables, 2.4.7 Numerical probabilities for a simple distribution, 2.4.8 Normal distribution as a model (A-level only), 2.4.9 Shape of the Normal curve (A-level only), 2.4.10 Linear transformation and standardising (A-level only), 2.4.11 Symmetry and inflection of Normal curve (A-level only), 2.4.12 Calculate probabilities from a Normal distribution (A-level only), 2.4.13 Model with probability distributions, and 2.4 Probability Distributions. Each one has a worked solution and a mark scheme showing where the marks go.