Which of the following results in probability theory is about the convergence of the normalized sum of a set of random variables to the Gaussian distribution? O Central limit theorem Law of large numbers Axioms of probability Bayesian estimationFrequency Standard deviations Match the illustration to the concept it is trying to demonstrate Bias Uniform Distribution - discrete and continuous Empirical Rule Central Limit Theorem Law of Large Numbers Complement Type here to searchAs the sample size n increases, the shape of the distribution of the sample means taken with replacement from a population with mean a and standard deviation o, will approach a normal distribution. This distribution will have a mean of u and a standard deviation of - Vn . This is a statement of the O rule of the mean O central limit theorem O law of large numbers O sample error of the meanSuppose we have a distribution that is unimodal, bell-shaped, and roughly symmetric. What is the name of the result that tells us that we should expect approximately 95% of our data to fall within two standard deviations from the mean? O Law of Averages O Empirical Rule Central Limit Theorem O Law of Large Numbers QUESTION 24 Decide whether the random variable is discrete or continuous. The random variable X equals the number of cars that run a red light during a specified amount of time. O Discrete O Continuous O Cannot determine we would need to know the duration of time