# Tag Info

• 611
1 vote

### Testing for statistical correlation using textual data

Unfortunately, the assumptions required of simple statistical tests would fail for your premise. The most simple examples (a 2-group binomial test as in prop.test or fisher s exact test fisher.test in ...
• 11
1 vote

### Probability of one horse finishing ahead of another

Let $p_i$, $i=1,2,\dots,n$ denote the probabilities that each horse wins given in the problem statement. A model that leads to simple calculations is to assume that some monotonically decreasing ...
• 9,331
Accepted

### Show the Binomial distribution approaches a Normal distribution (using characteristic function)

Your idea is good. But it's easier to take logarithms and just look at what results. You will eventually want to expand the log characteristic function (aka the cumulant generating function) as a ...
• 303k
1 vote

### Discrete uniform converges weakly to continuous uniform

By the definition of expectation: \begin{align*} & E[f(X_n)] = \sum_{i = 0}^{n - 1}f(i/n)n^{-1} = \sum_{i = 0}^{n - 1}\int_{i/n}^{(i + 1)/n}f(i/n)dx, \\ & E[f(X)] = \int_0^1 f(x)dx = \sum_{i =...
• 7,346

1 vote
Accepted

### Estimating the parameter in a mixed population

If I'm not mistaken, you have categorical outcomes, one of O1, O2, O3, O4, for each individual. Such data could be handled using multiple logistic regression, available as function ...
• 16.1k

### Random forest probability meaning

There are many interpretations of probability. Skimming through them would be a good starting point to understand the concept better. The decision tree makes probabilistic predictions by calculating ...
• 125k

### Definition and Interpretation of Likelihood for non-PhD's

The likelihood does give us what can often be equated with 'plausibility', but it is important to say that it is the relative plausibility according to the statistical model. And it is probably useful ...
• 11.7k

### Definition and Interpretation of Likelihood for non-PhD's

Your interpretations 1 and 2 are both wrong. Bayesians knew all along you have to multiply the likelihood by a prior to get a posterior probability distribution. The problem is there is no ...
• 56.2k

### How Do I Know If A Markov Chain Follows The Markov Property?

You can easily test this by doing multinomial regression. To fit the null hypothesis of a first order Markov chain you would include the previous state as a covariate in the model. You then estimate ...
• 9,331
1 vote

• 1,460