Hypothesis testing book

Question

I am looking for a book that is focused on hypothesis testing. I read "Hypothesis Testing: An Intuitive Guide for Making Data Driven" by Jim Frost and I'm looking for similar book which is focused on practical applications of diferent tests (and exaplains how they works and when to use it)

Answer 1

I dug up this book: Svetlozar Rachev, Markus Höchstötter, Frank Fabozzi, Sergio Focardi. Probability and Statistics for Finance. Wiley (2011). Chapter 19 is "Hypothesis Testing". It does not go as deep into the theory as Lehman. Starting on page 496, it lists several concrete and practical examples pertinent to finance and markets, worked out in lots of detail.

1 (simple test for parameter $\lambda$ of Poisson distribution) Consider a portfolio of risky bonds, where the number of defaulting bonds within one year is modeled as a Poisson random variable with parameter $\lambda$. The null hypothesis $H_0$ is that $\lambda=\lambda_0$, while the alternative hypothesis $H_1$ is that $\lambda=\lambda_1$, for some values $\lambda_0$ and $\lambda_1$.

2 (1-tailed test for parameter $\lambda$ of exponential distribution) Same risky bond portfolio, and the time between two successive defaults is given by an exponential random variable with parameter $\lambda$. The null hypothesis $H_0$ is that $\lambda \ge 1$, e.g. 1, while the alternative hypothesis $H_1$ is that $0 < \lambda <1$.

3 (1-tailed test for the mean $\mu$ of a normal distribution where the variance is known.) $\mu$ is the mean of the daily returns of a stock index. The null hypothesis $H_0$ is that $\mu \le y$, while the alternative hypothesis $H_1$ is that $\mu > y$ for some value $y$.

4 (1-tailed test for the variance of a normal distribution where the mean is known.) Same stock index, the null hypothesis $H_0$ is that $\sigma^2 >v$, while the alternative hypothesis $H_1$ is that $0 < \sigma^2 <v$ for some value $v$.

5 (2-tailed test for the mean $\mu$ of a normal distribution where the variance is known.) Same stock index, the null hypothesis $H_0$ is that $\mu = y$, while the alternative hypothesis $H_1$ is that $\mu \ne y$ for some value $y$.

6 (Equal tails test for the variance of a normal distribution where the mean is known.) Same stock index, the null hypothesis $H_0$ is that $\sigma^2 = v$, while the alternative hypothesis $H_1$ is that $\sigma^2 \ne v$ for some value $v$.

7 Test for equality of means: given two stocks, are their mean returns the same...

8 2-tailed Kolmogorov-Smirnov test for equality of distribution...

9 Likelihood ratio test...