Students-t test is the most popular statistical test. The test compares two mean values to judge if they are different or not. For small data it is possible to conduct it using manual calculation – however that is not the case. Researchers would need to use statistical software and packages to conduct their analysis. This guide will help the junior researchers to conduct independent- and paired-t test using STATA software.
Multivariate analyses depend on multivariate normality assumption. Although the analyses are available in SPSS, it is not possible to assess the assumption from the basic package. Statistical assessment of the normality is available in a specialized package, SPSS Amos, in form of Mardia's multivariate kurtosis. However, graphical assessment of the normality by chi-square versus Mahalanobis distance plot is not available in both of the packages. The aim of this article is to present the steps to construct the plot in SPSS in a point-and-click manner as expected by most SPSS users.
Over the years, maximum likelihood estimation and Bayesian method became popular statistical tools in which applied to fit finite mixture model. These trends begin with the advent of computer technology during the last decades. Moreover, the asymptotic properties for both statistical methods also act as one of the main reasons that boost the popularity of the methods. The difference between these two approaches is that the parameters for maximum likelihood estimation are fixed, but unknown meanwhile the parameters for Bayesian method act as random variables with known prior distributions. In the present paper, both the maximum likelihood estimation and Bayesian method are applied to investigate the relationship between exchange rate and the rubber price for Malaysia, Thailand, Philippines and Indonesia. In order to identify the most plausible method between Bayesian method and maximum likelihood estimation of time series data, Akaike Information Criterion and Bayesian Information Criterion are adopted in this paper. The result depicts that the Bayesian method performs better than maximum likelihood estimation on financial data.
The statistical characteristics of wind direction that was recorded at maximum wind speed in Peninsular Malaysia for two monsoons from 1999 to 2008 for seven stations were analyzed in this study. Modeled by von Mises distribution, the change in parameters values namely mean direction and concentration parameter was measured. Statistical summary, graphical representations, Watson-William Test and linear-circular correlation are used in the analysis. It is found that there is a significant change in the mean direction of wind over the period of ten years for most stations in Peninsular Malaysia. However, there is a weak relationship between wind direction and wind speed. This study suggested the presence of prominent direction of wind that blows in Peninsular Malaysia by monsoon. This finding may provide useful information on giving a better understanding of the behavior of the wind in Peninsular Malaysia and the potential use of wind as an alternative source of energy.
Otoliths, which can be used for the evaluation of relationships between the environment and organisms, are structures
consisting of calcium carbonate. The aim of this study was to realize the shape analysis. In addition, it is to detect the
characteristics of otolith biometrics in order to determine the relationship between the fish size of Engraulis encrasicolus
L. from the Black and Marmara Seas. The samples were obtained from the Black and Marmara Seas between December
2013 and February 2014. The relationships between the TL (Total length) and OL (Otolith length), TL and OB (Otolith
breadth), and TL and OW (Otolith weight) were determined using the linear regression equation. Form factor, roundness,
circularity and rectangularity were used for shape analyses. According to the data, there was no difference between
localities (p>0.05). Moreover, there was no difference between the left and right otoliths of the individuals sampled from
the same locality (p>0.05). According to the regression coefficient for relationships of TL-OL, TL-OB and TL-OW, otolith
length was identified as the best index for estimating fish length (r
2
>0.70). It showed that index values were statistically
different between two populations (p<0.001).
The practicality of biometrics of seafood cannot be overemphasized, particularly for competent authorities of the shrimp industry. However, there is a paucity of relevant literature on the relationship between biometric and physicochemical indices of freshly harvested shrimp. This work therefore investigated the relationship between biometric (standard length (SL), total weight (TW) and condition factor (CF)) and physicochemical (moisture content, pH, titratable acidity, water activity, water retention index, colour values and fracturability) characteristics of freshly harvested Pacific white shrimp (Litopenaeus vannamei) obtained from three different farms. The relationships between these parameters were determined using correlation and regression analyses.
Leptospirosis is an emerging disease, especially in countries with a tropical climate such as Malaysia. A dramatic increase in the number of cases has been reported over the last decade; however, information on the epidemiological trends of this disease is lacking. The objective of this study is to provide an epidemiological description of human leptospirosis cases over a 9-year period (2004-2012) and disease relationship with meteorological, geographical, and demographical information. A retrospective study was undertaken to describe the patterns of human leptospirosis cases and their association with intrinsic (sex, age, and ethnicity) and extrinsic (location, rainfall, and temperature) factors. Data was grouped according to age, sex, ethnicity, seasonality and geographical distribution, and analyzed using statistical tools to understand the influence of all the different factors on disease incidence. A total of 12,325 cases of leptospirosis were reported between 2004 and 2012 with an upward trend in disease incidence, with the highest in 2012. Three hundred thirty-eight deaths were reported with an overall case fatality rate of 2.74%, with higher incidence in males (9696; 78.7%) compared with female patients (2629; 21.3%), and overall male to female ratio of 3.69:1. Patients aged cohorts between 30-39 years old (16.22 per 100,000 population) had the highest disease incidence while the lowest incidence occurred between <1 to 9 years old (3.44 per 100,000 population). The average incidence was highest amongst Malays (10.97 per 100,000 population), followed by Indians (7.95 per 100,000 population). Stratification according to geographical distribution showed that the state of Malacca had the highest average disease incidence (11.12 per 100,000 population) followed by Pahang (10.08 per 100,000 population). The states of Terengganu, Kelantan, and Perak recorded similar rates of incidence (≈8.00 per 100,000 population), while Johor with the least number of reported cases (1.80 per 100,000 population). Positive relationships were recorded between the number of reported cases with the number of raining days per month and monthly average temperature (p-value<0.05). However, no significant association was noted between rainfall volume and number of reported Leptospirosis cases. This collaborative efforts between medical, academic and governmental institutions has enabled the construction of this comprehensive database that is essential to understand the disease trends in Malaysia and add insights into the prevention and control of this disease.
Combined multiple 2D views (proximal, anterior and ventral aspects) of the sagittal otolith are proposed here as a method to capture shape information for fish classification. Classification performance of single view compared with combined 2D views show improved classification accuracy of the latter, for nine species of Sciaenidae. The effects of shape description methods (shape indices, Procrustes analysis and elliptical Fourier analysis) on classification performance were evaluated. Procrustes analysis and elliptical Fourier analysis perform better than shape indices when single view is considered, but all perform equally well with combined views. A generic content-based image retrieval (CBIR) system that ranks dissimilarity (Procrustes distance) of otolith images was built to search query images without the need for detailed information of side (left or right), aspect (proximal or distal) and direction (positive or negative) of the otolith. Methods for the development of this automated classification system are discussed.
To assess the agreement of the Scheimpflug camera system Pentacam with the optical low-coherence reflectometry (OLCR) device LENSTAR LS900 in measuring anterior segment biometry.
The growth of microorganism on substrates, whether toxic or not usually exhibits sigmoidal
pattern. This sigmoidal growth pattern can be modelled using primary models such as Logistic,
modified Gompertz, Richards, Schnute, Baranyi-Roberts, Von Bertalanffy, Buchanan threephase
and Huang. Previously, the modified Gompertz model was chosen to model the growth of
Burkholderia sp. strain Neni-11 on acrylamide, which shows a sigmoidal curve. The modified
Gompertz model relies on the ordinary least squares method, which in turn relies heavily on
several important assumptions, which include that the data does not show autocorrelation. In this
work we perform statistical diagnosis test to test for the presence of autocorrelation using the
Durbin-Watson test and found that the model was adequate and robust as no autocorrelation of
the data was found.
Countless statistical tools are available to extract information from data. Life time modeling is considered as one of
the most prominent fields of statistics, which is evident from the developments made in this field in the last few decades.
Almost every statistic for life time analysis is based on precise life time observations, however, life time is not a precise
measurement but more or less fuzzy. Therefore, in addition to classical statistical tools, fuzzy number approaches to
describe life time data are more suitable. In order to incorporate fuzziness of the observations, fuzzy estimators for the
three parameter lognormal distribution were suggested. The proposed estimators cover stochastic variation as well as
fuzziness of the observations.
The complete mol-ecule of the title compound, [Sn(C4H9)2(C5H10NOS2)2], is generated by a crystallographic mirror plane, with the SnIV atom and the two inner methyl-ene C atoms of the butyl ligands lying on the mirror plane; statistical disorder is noted in the two terminal ethyl groups, which deviate from mirror symmetry. The di-thio-carbamate ligand coordinates to the metal atom in an asymmetric mode with the resulting C2S4 donor set defining a skew trapezoidal bipyramidal geometry; the n-butyl groups are disposed to lie over the longer Sn-S bonds. Supra-molecular chains aligned along the a-axis direction and sustained by methyl-ene-C-H⋯S(weakly coordinating) inter-actions feature in the mol-ecular packing. A Hirshfeld surface analysis reveals the dominance of H⋯H contacts in the crystal.
This study enhanced the production of thermostable organic solvent-tolerant (TS-OST) lipase by locally isolated thermotolerant Rhizopus sp. strain using solid-state fermentation (SSF) of palm kernel cake (PKC). The optimum conditions were achieved using a series of statistical approaches. The cultivation parameters, which include fermentation time, moisture content, temperature, pH, inoculum size, various carbon and nitrogen sources, as well as other supplements, were initially screened by the definitive screening design, and one-factor-at-a-time using PKC as the basal medium. Three significant factors (olive oil concentration, pH, and inoculum size) were further optimized using face-centred central composite design. The results indicated a successful and significant improvement of lipase activity by almost two-fold compared to the initial screening production. The findings showed that the optimal conditions were 2% (v/w) inoculum size, 2% (v/w) olive oil, 0.6% (w/w) peptone, 2% (v/w) ethanol, 70% moisture content at initial pH 10.0 and 45 °C within 72 h of fermentation. Process optimization resulted in maximum lipase activity of 58.63 U/gram dry solids (gds). The analysis of variance showed that the statistical model was significant (p value <0.0001) and reliable with a high value of R2 (0.98) and adjusted R2 (0.96). This indicates a better correlation between the actual and predicted responses of lipase production. By considering this study, the low-cost PKC through SSF appears to be promising in the utilization of agro-industrial waste for TS-OST lipase production. This is because satisfactory enzyme activity could be attained that promises industrial applications.
Individual patient data (IPD) meta-analyses are increasingly common in the literature. In the context of estimating the diagnostic accuracy of ordinal or semi-continuous scale tests, sensitivity and specificity are often reported for a given threshold or a small set of thresholds, and a meta-analysis is conducted via a bivariate approach to account for their correlation. When IPD are available, sensitivity and specificity can be pooled for every possible threshold. Our objective was to compare the bivariate approach, which can be applied separately at every threshold, to two multivariate methods: the ordinal multivariate random-effects model and the Poisson correlated gamma-frailty model. Our comparison was empirical, using IPD from 13 studies that evaluated the diagnostic accuracy of the 9-item Patient Health Questionnaire depression screening tool, and included simulations. The empirical comparison showed that the implementation of the two multivariate methods is more laborious in terms of computational time and sensitivity to user-supplied values compared to the bivariate approach. Simulations showed that ignoring the within-study correlation of sensitivity and specificity across thresholds did not worsen inferences with the bivariate approach compared to the Poisson model. The ordinal approach was not suitable for simulations because the model was highly sensitive to user-supplied starting values. We tentatively recommend the bivariate approach rather than more complex multivariate methods for IPD diagnostic accuracy meta-analyses of ordinal scale tests, although the limited type of diagnostic data considered in the simulation study restricts the generalization of our findings.
The problem in analysing qualitative study is regularly highlighted when it comes to data analysis process. Unlike quantitative data that deals with numerical and statistical issues, analysing qualitative data requires the researcher to deal with understanding human experiences and interpreting the data. Therefore, validity and reliability of the analysis are often questioned and becomes a challenge in analysing data from qualitative research. The objective of this writing is to highlight some of the challenges and strengths in the qualitative research process. Validity, reliability, and credibility are among the challenges in analysing qualitative study. Rigor in conducting data collection helps in overcoming the problem in validity, reliability and credibility. In addition, in-depth understanding and triangulation techniques such as interview, document analysis and observation used in qualitative researches are among the strengths for qualitative study.
Iris recognition has become a widely popular biometric system. The stable textures and features of the human iris have made such biometric systems efficient and accurate for purposes of verification and identification. The term non-ideal iris refers to a situation in which the iris is occluded by noise, including reflections, eyelashes, eyelids and so on. Most current iris recognition algorithms assume that the iris is not occluded, which is less accurate. A method using only some parts of the iris may be suitable to deal with a non-ideal iris. The current application of iris recognition systems are plagued by weaknesses such as slow processing times, especially when dealing with many irises. In this study, a sub-iris recognition technique is proposed to deal with the non-ideal iris, while reducing execution time via an embedded system using a graphical processing unit (GPU). The experiment revealed that the proposed method was accurate and fast.
Cable joint insulation breakdown may cause a huge loss to power companies. Therefore, it is vital to diagnose the insulation quality to detect early signs of insulation failure. It is well known that there is a correlation between Partial discharge (PD) and the insulation quality. Although many works have been done on PD pattern recognition, it is usually performed in a noise free environment. Also, works on PD pattern recognition in actual cable joint are less likely to be found in literature. Therefore, in this work, classifications of actual cable joint defect types from partial discharge data contaminated by noise were performed. Five cross-linked polyethylene (XLPE) cable joints with artificially created defects were prepared based on the defects commonly encountered on site. Three different types of input feature were extracted from the PD pattern under artificially created noisy environment. These include statistical features, fractal features and principal component analysis (PCA) features. These input features were used to train the classifiers to classify each PD defect types. Classifications were performed using three different artificial intelligence classifiers, which include Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Support Vector Machine (SVM). It was found that the classification accuracy decreases with higher noise level but PCA features used in SVM and ANN showed the strongest tolerance against noise contamination.
Meta-analysis is a subset of systematic review; a technique for systematically combining pertinent qualitative
and quantitative study data from numerous selected studies to broaden a single conclusion that has more
statistical power. This inference is statistically stronger than the analysis of any single study, due to increase
numbers of topics, greater variety amongst subjects, or collected effects and outcomes. The aim of this review
article is to highlight the definition, history, purpose, characteristics, use, advantage, disadvantage, validity,
and steps in conducting meta-analysis.
Recovering drug addict is affected by two main factors, namely internal factors (such as resilience and self-confidence) and external (support from families, employers, friends, and community). One of the internal factors that appear to influence the level of recovery of former drug addict is selfconfidence. Therefore this study aims to measure the level of self-confidence among former drug addicts, also known as Orang Kena Pengawasan (OKP) who underwent rehabilitation in 6-11 months and 12-24 months. The study was conducted using cross-sectional surveys. A total of 386 former drug addicts in Peninsular Malaysia were involved in this study with 198 respondents undergoing 6-11 months rehabilitation programme and 197 were respondents who were released within 12-24 months. The data obtained were analyzed using descriptive statistics. This analysis was used to measure the level of self-confidence between respondents who underwent the 6-11 months rehabilitation programme (Group 1) and 12-24 months (Group 2). The study found that the majority of both groups showed no signiticant difference in the level of recovery from the aspect of self-confidence. The study also found the majority of respondents of both groups showed a moderate level of confidence of 58.5 percent. However, Group 1 showed a higher percentage of self-confidence (63.5%) compared to Group 2 of (53.8%). The findings have implications for the development of strategies towards a strong self-confidence among the inmates to reduce recidivism rates in Malaysia.
The data presented in this article were the basis for the study reported in the research articles entitled "Statistical assessment of experimental observation on the slug body length and slug translational velocity in a horizontal pipe" (Al-Kayiem et al., 2017) [1] which presents an experimental investigation of the slug velocity and slug body length for air-water tow phase flow in horizontal pipe. Here, in this article, the experimental set-up and the major instruments used for obtaining the computed data were explained in details. This data will be presented in the form of tables and videos.