Background: Epidemic of anemia is considered to be a significant threat to pregnant women or women in child bearing age. Anemia is one of the major nutritional health disorders affecting significant proportion of population not only in developing countries but also in developed countries. This threat is more alarming in developing countries where poverty, illiteracy may contribute to high risk for causes of anemia. Objective: The purpose of the current study was to investigate the main causes of anemia in pregnant women in the State of Azad Kashmir, Muzaffarabad and to investigate the relationship between education and anemia. Methods: A descriptive cross sectional study was conducted over a sample of 433 pregnant women. The Chi- square test has been used to assess the statistical significance of different risk factors with Hb% (Heamoglobin) of the respondent. The multiple logistic regression model was used to get the most significant risk factors of anemia. Results: The study shows that the most dominant risk factors of the anemia were age at the time of marriage at different age categories that are 16 - 20 (OR = 3.945) (OR Odds ratios) with 95% C-I (confidence interval) (0.294 to 52.985), 21 - 25 (OR = 2.316) with 95% C-I (0.192 to 27.932) and 26 - 30 (OR = 4.179) with 95% C-I (0.347 to 50.320). Education at different education levels that is illiterate (OR = 1.191) with 95% C-I (0.005 to 87.279) and primary (OR = 1.179) with 95% C-I (0.009 to 156.200). Hb% at different levels 3 - 4 g/dl (OR = 1.220) with 95% C-I (0.299 to 4.984), 5 - 6 g/dl (OR = 2.221) with 95% C-I (0.679 to7.263) and 7 - 10 g/dl (OR = 1.384) with 95% C-I (0.408 to

4.689). Monthly income < 10,000 (OR = 2.296) 95% C-I (0.385 to 13.677), 11,000 - 15,000 (OR = 3.623) 95% C-I (0.678 to 19.31) and 16,000 to 20,000 (OR = 2.158) 95% C-I (0.441 to 10.563). Age of last child born 1 year (OR = 1.711) 95% C-I (0.399 to 7.341), 2 year (OR = 1.284) 95% C-I (0.304 to 5.421) and <1 year (OR = 2.224) 95% C-I (0.552 to 8.952). Daily eating habits, just like previous (OR = 2.415) 95% C-I (0.652 to 8.948), less than previous (OR = 3.671) 95% C-I (0.868 to 15.522). Previous history of miscarriage (OR = 1.258) 95% C-I (0.103 to 0.647), suffered in any hemorrhagic disease (OR = 1.529) 95% C-I (0.592 to 3.949). Nature of the work Exhaustive (OR = 1.961) 95% C-I (0.805 to 4.779).

The paper deals with the analysis of market sentiments in exchange rates
which are of great interest to trading individuals and institutional investors.
For example, an institutional investor or a trading individual makes better investments and
minimizes losses when equipped with an understanding of market sentiments in
weekly or monthly exchange returns. In the approach suggested here, a typical
market sentiment is defined on the basis of the certain function of the mean
and the standard error of the logarithm of the ratio of successive daily
exchange rates. Based on this surmise, the market sentiments are classified
into various states, whereby states are defined according to the perceptions of
the market player. A multinomial probability model is built to capture the uncertainties in market
sentiments. Two asymptotically distribution-free tests, namely the chi-square and the likelihood ratio test of
goodness of fit for the hypothesis of the symmetry in market sentiments are
suggested. Two different measures of market sentiments are proposed. The
approach advocated here will be of interest to researchers, exchange rate
traders and financial analysts. As an application of the proposed line of
approach, we analyze weekly market sentiments that govern exchange rates of the
major global currencies—EUR, GBP, SDR, YEN,
ZAR, USD, data from 2001-2012. Some interesting conclusions are revealed based
on the data analysis.

Abstract:
some basic elements on the use and misuse of independence and homogeneity chi-square tests in the final reports of theses are shown, as well as the importance of the confounding bias control, the need to take this into account in the analytic research and some methods to achieve it.

Abstract:
This paper presents a graphical way of interpreting effect sizes when more than two groups are involved in a statistical analysis. This method uses noncentral distributions to specify the alternative hypothesis, and the statistical power can thus be directly computed. This principle is illustrated using the chi-squared distribution and the F distribution. Examples of chi-squared and ANOVA statistical tests are provided to further illustrate the point. It is concluded that power analyses are an essential part of statistical analysis, and that using noncentral distributions provides an argument in favour of using a factorial ANOVA over multiple t tests.

Background: Current research focuses primarily on women’s autonomy in decision making while little attention is paid to their freedom of expression. Socioeconomic& socio demographic factors affect women’s autonomy in decision making. In the developing countries, particularly in Pakistan, although women are making significant financial contributions but they are still under collective decisions of husband and other family members while sometimes they are blindly relying on husband’s decision. Objective of study was to find out association of women’s autonomy in decision making & socioeconomic factors.Method:Cross sectional survey was conducted in Muzaffarabad Azad Kashmir on married working women (N=500). The data consist of women’s three decisions: birth control decision, financial decision and freedom of expression. A number of socio-demographic variables were used in chi-square analysis to examine the association of these variables with the said decisions.Results: Age, residence, education, professional differences, job nature, monthly income of married women are positively associated with autonomy in decision making.59% women of above 30 years age exercise independence in birth control decisions(p value0.02). Urban women

Abstract:
According to the actual measurement data, probability models of horizontal wind load were obtained based on wind velocity statistic and power spectral density function of fluctuating wind velocity through stochastic sampling and using spectrum analysis method. Through the comparison of two models, probability models of horizontal wind load based on probability models of fluctuating wind velocity were obtained by revising the mean and variance of fluctuating wind velocity. Results show that the variance takes lower value when the power spectral density function of fluctuating wind velocity is used to obtain the probability model of horizontal wind load. The quadratic term of fluctuating wind velocity takes a small contribution value in total wind load with almost no contribution to the model of horizontal wind load. It is convenient for practical engineering to obtain the models of horizontal wind load by using probability models of fluctuating wind velocity.

Abstract:
In large sample studies where distributions may be skewed and not readily transformed to symmetry, it may be of greater interest to compare different distributions in terms of percentiles rather than means. For example, it may be more informative to compare two or more populations with respect to their within population distributions by testing the hypothesis that their corresponding respective 10th, 50th, and 90th percentiles are equal. As a generalization of the median test, the proposed test statistic is asymptotically distributed as Chi-square with degrees of freedom dependent upon the number of percentiles tested and constraints of the null hypothesis. Results from simulation studies are used to validate the nominal 0.05 significance level under the null hypothesis, and asymptotic power properties that are suitable for testing equality of percentile profiles against selected profile discrepancies for a variety of underlying distributions. A pragmatic example is provided to illustrate the comparison of the percentile profiles for four body mass index distributions.

In this paper, we generalize the proof of the Cochran statistic in the case of an ANOVA two ways structure that asymptotically follows a Chi-2. While construction of homogeneity statistics test usually resorts to the determination of the covariance matrix and its inverse, the Moore-Penrose matrix, our approach, avoids this step. We also show that the Cochran statistic in ANOVA two ways is equivalent to conventional homogeneity statistics test. In particular, we show that it satisfies the invariance property. Finally, we conduct empirical verification from a meta-analysis that confirms our theoretical results.

Abstract:
Quadratic distance methods
based on a special distance which make use of survival functions are developed
for inferences for bivariate continuous models using selected points on the nonnegative quadrant.A related version which can be viewed as a simulated
version is also developed and appears to be suitable for bivariate
distributions with no closed form expressions and numerically not tractable but
it is easy to simulate from these distributions.The notion of an adaptive basis is introduced and
the estimators can be viewed as quasilikelihood estimators using the projected
score functions on an adaptive basis and they are closely related to minimum
chi-square estimators with random cells which can also be viewed as
quasilikeliood estimators using a projected score functions on a special
adaptive basis but the elements of such a basis were linearly dependent.A rule for selecting points on the nonnegative
quadrant which make use of quasi Monte Carlo (QMC) numbers and two sample
quantiles of the two marginal distributions is proposed if complete data is
available and like minimum chi-square methods; the quadratic distance methods also offer
chi-square statistics which appear to be useful in practice for model testing.