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The solvency ratio of an insurance company is the size of its capital relative to all risks it has taken. The solvency ratio is most often defined as: The solvency ratio is most often defined as: n e t . a s s e t s ÷ n e t . p r e m i u m . w r i t t e n {\displaystyle net.assets\div net.premium.written}
The Brown–Forsythe test uses the median instead of the mean in computing the spread within each group (¯ vs. ~, above).Although the optimal choice depends on the underlying distribution, the definition based on the median is recommended as the choice that provides good robustness against many types of non-normal data while retaining good statistical power. [3]
Thus the likelihood-ratio test tests whether this ratio is significantly different from one, or equivalently whether its natural logarithm is significantly different from zero. The likelihood-ratio test, also known as Wilks test , [ 2 ] is the oldest of the three classical approaches to hypothesis testing, together with the Lagrange multiplier ...
The incremental cost-effectiveness ratio (ICER) is the ratio between the difference in costs and the difference in benefits of two interventions. The ICER may be stated as (C1 – C0)/(E1 – E0) in a simple example where C0 and E0 represent the cost and gain, respectively, from taking no health intervention action.
We can derive the value of the G-test from the log-likelihood ratio test where the underlying model is a multinomial model. Suppose we had a sample x = ( x 1 , … , x m ) {\textstyle x=(x_{1},\ldots ,x_{m})} where each x i {\textstyle x_{i}} is the number of times that an object of type i {\textstyle i} was observed.
In statistics, an F-test of equality of variances is a test for the null hypothesis that two normal populations have the same variance.Notionally, any F-test can be regarded as a comparison of two variances, but the specific case being discussed in this article is that of two populations, where the test statistic used is the ratio of two sample variances. [1]
In practice the odds ratio is commonly used for case-control studies, as the relative risk cannot be estimated. [1] In fact, the odds ratio has much more common use in statistics, since logistic regression, often associated with clinical trials, works with the log of the odds ratio, not relative risk. Because the (natural log of the) odds of a ...
In this example, the ratio of adjacent terms in the blue sequence converges to L=1/2. We choose r = (L+1)/2 = 3/4. Then the blue sequence is dominated by the red sequence r k for all n ≥ 2. The red sequence converges, so the blue sequence does as well. Below is a proof of the validity of the generalized ratio test.