Hypothesis Tests for a Population Mean

Multistage Hypothesis Tests for the Mean of a Normal Distribution ∗

In this paper, we have developed new multistage tests which guarantee prescribed level of power and are more efficient than previous tests in terms of average sampling number and the number of sampling operations. Without truncation, the maximum sampling numbers of our testing plans are absolutely bounded. Based on geometrical arguments, we have derived extremely tight bounds for the operating ...

Robust tests for testing the parameters of a normal population

This article aims to provide a simple robust method to test the parameters of a normal population by using the new diagnostic tool called the “Forward Search” (FS) method. The most commonly used procedures to test the mean and variance of a normal distribution are Student’s t test and Chi-square test, respectively. These tests suffer from the presence of outliers. We introduce the FS version of...

Nonparametric Tests for the mean of a Non-negative Population

We construct level-α tests for testing the null hypothesis that the mean of a non-negative population falls below a prespecified nominal value. These tests make no assumption about the distribution function other than that it be supported on [0,∞). Simple tests are derived based on either the sample mean or the sample product. The nonparametric likelihood ratio test is also discussed in this co...

Hypothesis tests for hydrologic alteration

Modified Sampling Strategies Using Correlation Coefficient for Estimating Population Mean

This paper proposes two sampling strategies based on the modified ratio estimator using the population mean of auxiliary variable and population correlation coefficient between the study variable and the auxiliary variable by Singh and Tailor (2003) for estimating the population mean (total) of the study variable in a finite population. A comparative study is made with usual sampling strategies...