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Large Sample Problems

Author

Listed:
  • Jai Won Choi
  • Balgobin Nandram

Abstract

Variance is very important in test statistics as it measures the degree of reliability of estimates. It depends not only on the sample size but also on other factors such as population size, type of data and its distribution, and method of sampling or experiments. But here, we assume that these other fasctors are fixed, and that the test statistic depends only on the sample size. When the sample size is larger, the variance will be smaller. Smaller variance makes test statistics larger or gives more significant results in testing a hypothesis. Whatever the hypothesis is, it does not matter. Thus, the test result is often misleading because much of it reflects the sample size. Therefore, we discuss the large sample problem in performing traditional tests and show how to fix this problem.

Suggested Citation

  • Jai Won Choi & Balgobin Nandram, 2021. "Large Sample Problems," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 10(2), pages 1-81, March.
    • Handle: RePEc:ibn:ijspjl:v:10:y:2021:i:2:p:81
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    References listed on IDEAS

    as
    1. Nandram, Balgobin & Choi, Jai Won, 2010. "A Bayesian Analysis of Body Mass Index Data From Small Domains Under Nonignorable Nonresponse and Selection," Journal of the American Statistical Association, American Statistical Association, vol. 105(489), pages 120-135.
    2. Dilli Bhatta & Balgobin Nandram & Joseph Sedransk, 2018. "Bayesian testing for independence of two categorical variables under two-stage cluster sampling with covariates," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(13), pages 2365-2393, October.
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    Citations

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    Cited by:

    1. Jai Won Choi & Balgobin Nandram & Boseung Choi, 2022. "Combining Correlated P-values From Primary Data Analyses," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 11(6), pages 1-12, November.

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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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