Statistics

This paper introduces a new improved ratio estimator for population mean in stratified random sampling using calibration estimation theory. Following the results of an empirical study, it is deduced that the proposed estimator is substantially more efficient than existing estimators of its class.

This paper provides a unified framework for chain ratio-product estimation and proposes a generalized chain ratio-product estimator for estimating population mean in stratified sampling. The bias and variance expressions of the proposed estimator have been derived under large sample approximation. Asymptotic optimum estimator (AOE) and its approximate variance estimator are derived with conditions for allowable departure identified. Some existing estimators in theory are obtained and shown to be particular members of the proposed estimator under certain restrictions. Analytical comparisons of the AOE with other existing estimators showed that the AOE is substantially more efficient under certain realistic conditions.

The present study is an attempt to find out appropriate ARIMA model by using Box-Jenkins methodology to forecast the export/import of wood based panel in India on time series data for a period of 16 years from 1996-97 to 2011-12. Test criterion like lowest Bayesian Information Criterion (BIC), R2 value and lowest of mean absolute percentage error (MAPE) are applied to predict the accuracy of the model. This study found ARIMA (0,1,0) with R2: 0.83 for the export and ARIMA (0,1,1) with R2: 0.87 for the import to forecast of export/import of wood based panel. The estimated export and import of wood based panels in the year 2020 would be increased by 170% and 127% in respect to 2012.

Uniformity trials are needed to determine suitable shape and size of the plot for fertility variation in land. The suggested model is more adequate model over well known Fairfield Smith variance law and also removes all the objections by Cochran (1977) for Fairfield Smith variance law model. The adequacy of suggested model has been examined by the given data in Haque et al. (1988). Key words: Fairfield Smith’s Variance Law, nonlinear model, uniformity trial experiments.

This Article introduces the basic concepts, terminology, goals and procedures underlying the proper statistical design of experiment. This section describes in detail the process of choosing an experimental design. The choice of design in agricultural field experiments depends on the objectives of the experiment and the number of factors to be investigated.

This paper presents exponential dual to ratio and dual to product-type estimators for estimating finite population mean using auxiliary information in double sampling. The expressions for bias and mean square error of the proposed estimators have been derived for two different cases up to the first order approximation. Comparisons have been made with other estimators viz. simple mean per unit estimator, usual ratio estimator Cochran and product estimator Murthy , dual to ratio estimator Kumar and Bahl and dual to product estimator Singh and Choudhury estimator, exponential ratio and product estimators Singh and Vishwakarma in double sampling. Empirical studies have also been carried out to show the merits of the proposed estimators over the existing estimators. It is concluded that the use of proposed estimators should be preferred in practice.

This paper was taken the loss and risk concepts, the objective of this paper is to estimate the loss and the risk in the Bayes method, as illustrated in the related case Where the prior distribution of the random variable is discrete and continuous, it applied on crop sales data in the continuous case, while it applied by two examples in the discrete case. Then the estimator of the loss function is the mean posterior distribution of the random variable, so it’s the same with median posterior distribution, hence is also the Bayes estimator with respect to a loss function equal to absolute deviation. The Bayes risk is a real value is the average of the loss function, so the smallest estimator who is the best estimator of the Bayes risk.

In this paper, we propose a new optional randomized response model based on Gupta and Shabbir (2007) two-stage randomized response model which unbound the assumption that the mean of the scrambling variable S is ‘unity’ [i.e. ]. We derive the estimator of the sensitive variable, mean, and show that our method is more efficient than other randomized response models suggested by Eichhorn and Hayre (1983) and Gupta and shabbir (2007) estimators. A numerical illustration is given in support of the present study.

Anaemia is a common health problem among women throughout the world. The present study with the objective to assess the nutritional status of rural village women and to study the knowledge of village women regarding Anaemia. In addition to this, the effect of various socio-economic and demographic factors on Anaemia related knowledge of village women are assessed. The cross sectional study was carried out in Punavasal village of Tiruvarur District in Cauvery delta region, Tamil Nadu. A total of 1000 respondents were selected randomly. Their knowledge was tested and socio-demographic and nutritional profile was recorded. Conclusion was that knowledge of rural women was found to be very poor in regard of Anaemia, nutritional status was unsatisfactory. To eradicate the problem of Anaemia a more intense awareness campaign is required in the region. Keywords: Anaemia, Heamoglobin, Blood, RBC, WBC.

Child mortality refers to the death of infants and children under the age of five or between the age of one month to four years depending on the definition. Child mortality is a core indicator of child health and well-being. In this paper we propose a probability model for child mortality among women with fixed parity under certain assumption and techniques. The suitability of the model is tested through observed data. NFHS-3 data has been used to carry out this study.