Disjoint/Addition Rule
... You roll a die twice. What is the probability that on the first roll you get a 5 and on the second roll you will get an even number? – Event 1: You roll a 5 on the first roll. – Event 2: You roll an even number on the second roll. – Even though 5 and even appear to be disjoint events, in this case, ...
... You roll a die twice. What is the probability that on the first roll you get a 5 and on the second roll you will get an even number? – Event 1: You roll a 5 on the first roll. – Event 2: You roll an even number on the second roll. – Even though 5 and even appear to be disjoint events, in this case, ...
Section 8.2
... constructing a probability distribution for how many shots it takes for him to make his first free throw (let’s go to n = 10). • What would the graph of a geometric probability distribution look like? ...
... constructing a probability distribution for how many shots it takes for him to make his first free throw (let’s go to n = 10). • What would the graph of a geometric probability distribution look like? ...
Lecture 1: Probability theory
... - Hand in questions at the workshop, or ask your tutor when they want it for next week (hand in at the maths school office in Pevensey II). ...
... - Hand in questions at the workshop, or ask your tutor when they want it for next week (hand in at the maths school office in Pevensey II). ...
3. Lecture Notes 3_ppt
... Suppose we toss a coin and observe the resulting face at the top. • Experiment: tossing the coin. • Sample points: Head (H) and Tail (T). • Sample space: S = {H, T}. • Events: {H}, {T}, {H,T} and Φ (the empty set). Suppose we throw a die and observe the resulting face at the top. • Experiment: throw ...
... Suppose we toss a coin and observe the resulting face at the top. • Experiment: tossing the coin. • Sample points: Head (H) and Tail (T). • Sample space: S = {H, T}. • Events: {H}, {T}, {H,T} and Φ (the empty set). Suppose we throw a die and observe the resulting face at the top. • Experiment: throw ...
Expected Value and Variance
... • This class we will, finally, discuss expectation and variance. • Often used concepts to summarize probability distributions: what to expect and how much does it vary around the expectation. • As usual we first look at the discrete case, then at the continuous. For the discrete case we only look at ...
... • This class we will, finally, discuss expectation and variance. • Often used concepts to summarize probability distributions: what to expect and how much does it vary around the expectation. • As usual we first look at the discrete case, then at the continuous. For the discrete case we only look at ...
Solutions of second practice midterm
... Practice midterm 2: solutions The midterm will be closed-book and closed-notes. It covers the following sections from the textbook: ...
... Practice midterm 2: solutions The midterm will be closed-book and closed-notes. It covers the following sections from the textbook: ...
December 2013 - John Abbott Home Page
... Part III (6 marks each) 1. The cholesterol of a sample of 10 men is measured and a hypothesis test is performed at the 0.05 level of significance to test if the mean cholesterol level in men is greater than 225. It is known that cholesterol is normally distributed with standard deviation 30. If the ...
... Part III (6 marks each) 1. The cholesterol of a sample of 10 men is measured and a hypothesis test is performed at the 0.05 level of significance to test if the mean cholesterol level in men is greater than 225. It is known that cholesterol is normally distributed with standard deviation 30. If the ...
Yanyuan Ma A Semiparametric Approach to Dimension Reduction COLLOQUIUM
... We provide a novel and completely different approach to dimension-reduction problems from the existing literature. We cast the dimensionreduction problem in a semiparametric estimation framework and derive estimating equations. Viewing this problem from the new angle allows us to derive a rich class ...
... We provide a novel and completely different approach to dimension-reduction problems from the existing literature. We cast the dimensionreduction problem in a semiparametric estimation framework and derive estimating equations. Viewing this problem from the new angle allows us to derive a rich class ...
