23 - Analysis of Variance
... meaningful differences between groups. However it does not tell us which groups are significantly different from which other groups. To narrow down the source of differences, we may perform post hoc analysis, which essentially compares each group mean with every other group mean, looking for a signi ...
... meaningful differences between groups. However it does not tell us which groups are significantly different from which other groups. To narrow down the source of differences, we may perform post hoc analysis, which essentially compares each group mean with every other group mean, looking for a signi ...
1 The Gradient Statistic
... We ask, can we predict the sex of a jackal from the mandible length of a skull? We will use the linear logistic model α + β xi – x where x is the mandible length. The null hypothesis will assert that length is irrelevant, so β = 0. We will take care of the nuisance parameter a by conditioning on its ...
... We ask, can we predict the sex of a jackal from the mandible length of a skull? We will use the linear logistic model α + β xi – x where x is the mandible length. The null hypothesis will assert that length is irrelevant, so β = 0. We will take care of the nuisance parameter a by conditioning on its ...
chapter 8—sampling distributions
... 1. The first result is important since we note that if we sample from a Normal population, then the sample average is exactly normally distributed, regardless of the sample size. As a follow-up, we also know that: If the population is approx Normal, then X ≈ Normal regardless of sample size. 2. In t ...
... 1. The first result is important since we note that if we sample from a Normal population, then the sample average is exactly normally distributed, regardless of the sample size. As a follow-up, we also know that: If the population is approx Normal, then X ≈ Normal regardless of sample size. 2. In t ...
uncertainty
... underlying pdf. We can only estimate from our sample data. (There’s a lot more than 100 boxes of screws coming off the assembly line.) We denote that estimate as x . Our expectation is that x is close to . In fact, we’ll even be able to calculate how close it’s likely to be. Now the second questi ...
... underlying pdf. We can only estimate from our sample data. (There’s a lot more than 100 boxes of screws coming off the assembly line.) We denote that estimate as x . Our expectation is that x is close to . In fact, we’ll even be able to calculate how close it’s likely to be. Now the second questi ...
Gov 2000 - 4. Multiple Random Variables
... joint and conditional distributions • Remember when we defined probability we talked a lot about joint probabilities of events—what was the probability of A and B occurring: P(A ∩ B). We also talked about the conditional probability of A given that B occurred. • It turns out that a very important pa ...
... joint and conditional distributions • Remember when we defined probability we talked a lot about joint probabilities of events—what was the probability of A and B occurring: P(A ∩ B). We also talked about the conditional probability of A given that B occurred. • It turns out that a very important pa ...
Introduction to Probablity - Sys
... There is a 20% chance that Saskatoon will be amongst the final 5. There is a 35% chance that Moncton will be amongst the final 5 and an 8% chance that both Saskatoon and Moncton will be amongst the final 5. What is the probability that Saskatoon or Moncton will be amongst the final 5. ...
... There is a 20% chance that Saskatoon will be amongst the final 5. There is a 35% chance that Moncton will be amongst the final 5 and an 8% chance that both Saskatoon and Moncton will be amongst the final 5. What is the probability that Saskatoon or Moncton will be amongst the final 5. ...
Statistics, 1e
... bell-shaped and characterized by its mean µ and standard deviation σ. The probability of falling within any particular number of standard deviations of µ is the same for all normal distributions. ...
... bell-shaped and characterized by its mean µ and standard deviation σ. The probability of falling within any particular number of standard deviations of µ is the same for all normal distributions. ...
