Random Selection Process Research Articles

Effective Learning of the Students of Private Universities in Bangladesh: Impediments and Way-out

Effective learning is vital for students in the tertiary stage. But it is often seen that students in Bangladesh are not effectively learning and often they are suffering from the lack of motivation and lack of skills, necessary for thriving in the contemporary world. This paper focuses on the importance of effective learning and how to achieve necessary study skills through effective study strategies. Further, this paper attempts to find out the underlying issues of demotivation of private university students in Bangladesh and the obstacles which hinder their effective learning along with examining the study habits of the students. This paper also suggests some recommendations as to how the identified obstacles and issues can be successfully sorted out by various strategies with a view to up-scaling effective learning by the students. Mixed approaches of qualitative and quantitative approaches have been adopted-qualitative for collecting necessary secondary data and quantitative for primary data. Secondary data have been collected from renowned universities and online sources. Primary data have been accumulated from the answers to a structured questionnaire consisting of 28 questions applied to 40 students on ‘Random Selection Process’ from a selected private university as a research sample. Finally, the data have been analyzed and presented through tables and figures.

ANALYSIS OF THE ECONOMIC OF RICE (ORYZA SATIVA L.) FARMING IN NEPAL’S KAPILVASTU DISTRICT

Rice is an annual plant in the Poaceae family. It can be produced across Nepal, from the plains to the mountains, and is the country’s main food crop. A study was conducted to look at the production, economics, and factors affecting the gross return of rice production in 2022 in the Kapilvastu area of Nepal, where a rice super zone was created under the Prime Minister Agriculture Modernization Project. (PM-AMP). A sample of 300 rice growers was selected using a straightforward random selection process. While secondary data was gathered by reading relevant literature, primary data was gathered through an interview technique that has been thoroughly tested. The results showed that smaller farmers’ costs to produce rice were higher per hectare (NRS. 180431) than those of larger farmers (NRS. 127289 per hectare) . Because the overall B: C ratio was larger than 1, the study finds that investing in rice farming was economically viable in the studied area (1.19). The discovery will aid farmers in considering the necessity to replace human and bullock labor with farm machinery. As a result, the cost of cultivation would decrease as rice farming’s productivity and financial returns increased.

ASSESSING INFLUENCE OF MARKETING KNOWLEDGE MANAGEMENT ON BUSINESS PERFORMANCE: A CASE OF CONVENTIONAL BANKS IN PAKISTAN

Purpose of this research is to determine link between marketing knowledge management (MKM) and the conventional banks performance. This study employs quantitative research approach, and it draws its participants from a sample of firms and organizations that have already put MKM and DFI into practice. A total of 304 commercial bank managers and staff were given the questionnaire using a random selection process. The researchers did, however, collect 304 completed surveys, which they put through the reliability test, an EFA, and a simple linear regression analysis. Surveys are used to gather data, which is then examined with the statistical techniques such as correlation and regression analysis. It seems that MKM has favorable and substantial effect on company outcomes. By providing empirical proof of importance of marketing knowledge management (MKM) in enhancing corporate performance, this study adds to the current body of knowledge. It also draws attention to necessity for businesses to effectively manage and utilize their marketing knowledge and to adopt digital financial innovation in order to improve their performance.

A Linear Regression Study of the Effects of Age on Income in the Godawari Municipality, Lalitpur

The study examined the relationship between age and income in Godawari Municipality in Lalitpur, Nepal. The research showed a correlation between age and income is positive, indicating that as people age, their likelihood of having an increasing income increases. The goodness of fit of the regression model, however, is poor, indicating that the yearly income of the respondents may possibly be influenced by other factors. The findings of the study have important ramifications for decision-makers in government, business, and for people who are preparing for their financial future. It emphasizes the value of continued study to comprehend the intricate connections between age, income, and other demographic factors. A straightforward random selection process was used to pick 2954 respondents for the survey from the municipality. In order to test a linear regression model of the effects of age on income, participants were questioned about their age and annual income. According to the model, there was an NPR 1,237 rise in income for every year that people aged, and this link was significant at the 0.05 level. Policymakers, companies, and people preparing for their financial future in the municipality should take these results seriously. The findings might be used by policymakers to guide initiatives like expanding job possibilities and social security services for senior citizens to assist aging populations.

Rural-Urban Labor Migration, Remittances, and Its Effect on Migrant-Sending Farm Households: Northwest Ethiopia

The purpose of this research is to examine the impact of rural-urban labor migration and remittances on rural agricultural productivity. A rigorous random selection process was used to pick 480 households from cross-sectional data. For this investigation, both primary and secondary data were used. Stata version 16 was used to examine both qualitative and quantitative data using descriptive (mean, standard deviation, and percentages) and econometric (three-stage least square technique) analyses. According to the descriptive data, the majority of respondents used their remittances for consumption, to acquire agricultural inputs, and to pay back their debts and tax payments. According to econometric studies, rural-urban migration has little influence on agricultural productivity. Remittances, cultivated land, livestock ownership, and extension services, on the other hand, have a positive and significant effect on agricultural productivity. In a nutshell, the link between migration, remittances, and agricultural output in agrarian and rural families is remarkable. Agriculture is the major source of income and mostly handles the liquidity issue. Agriculture production in the study region is labor intensive, and it is influenced by the amount of effort utilized in production as well as the socioeconomic characteristics of the household. As a result, it must address the major conundrum of agricultural productivity, particularly rural-urban migration and remittances. Address a knowledge gap, begin activities, and develop and implement multiple initiatives by various responsible stakeholders that are essential for the research topic. Furthermore, agricultural extension service delivery should be improved by timely recruiting, frequent agent training, and appropriate logistics.

On comparing design-based estimation versus model-based prediction to assess the abundance of biological populations

Assessing the abundance of biological populations is a central technical challenge in ecology, whether fundamental or applied. Although the question faced is simple, it is actually a complicated topic that has produced a vast array of methods. The first step is always sampling the geographical space, ideally by means of a randomized selection process. In that case, with a frequentist interpretation of probability, abundance can be estimated by taking into account randomization, or predicted conditionally on the sample at hand, by specifying a statistical model. This leads to a choice between so-called design-based estimation and model-based prediction. The goal of this methodological article is to contribute to the understanding of fundamental notions regarding these two statistical frameworks by the targeted audience, mainly quantitative ecologists. For this purpose, we illustrate the comparison between design-based estimation in the case of simple random sampling without replacement (SRSWOR) and model-based prediction. As an example, we model count data with a delta-lognormal distribution and rely on uniformly minimum-variance unbiased estimators (UMVUEs) for the prediction of abundance. We investigate the robustness of the predictor by contaminating the delta-lognormal distribution using actual count data. Data from a survey concerning wintering populations in France of two wader species, namely, northern lapwing (Vanellus vanellus) and European golden plover (Pluvialis apricaria) serve as illustrative examples. By means of Monte Carlo simulations, we highlight the lack of robustness of the predictor based on the delta-lognormal distributional model, in terms of both actual bias and precision. We organize the discussion around the illustrative examples in the context of the sampling design, the model and the data.

Impact of stockbrokers’ services on the trust and confidence of retail equity investors: an ordinal approach

PurposeThe purpose of this study was to assess equity investors satisfaction with stockbroker services. Four components emerged from a factor analysis of 14 variables of retail equity investors’ satisfaction with stockbroker services. According to the findings, these elements have a substantial impact on investors’ trust and confidence in stockbrokers.Design/methodology/approachBy physically visiting stockbrokers’ offices in Punjab, including Amritsar, Jalandhar, Ludhiana and Mohali, 1,000 questionnaires were distributed to retail equities investors. Stockbrokers were chosen using a simple random selection process due to their large number. Questionnaires were filled out by personally visiting stockbrokers’ offices and handing over surveys, instructing them to fill them out with information from their clients and personally visiting stockbrokers’ offices and instructing their clients to complete the questionnaires. The respondents completed 373 surveys. A total of 45 surveys were determined to be incomplete and were removed from the study. The remaining 328 surveys were used to conduct the analysis. The study uses ordinal regression to assess investors’ trust and confidence in stockbrokers’ services.FindingsThe findings of the study highlighted the importance of variables evaluated by respondents when seeking stockbroker services. These criteria included the accuracy of stockbrokers’ information, the speed with which accounts are settled and the brokers’ willingness to give valuable service to investors. These 14 variables, which measure investor satisfaction with stockbroker services, were subjected to factor analysis. With the use of component analysis, four factors were identified: satisfaction with stockbroker services, stockbroker regulations, stockbroker transactional services and stockbrokers’ image in the eyes of investors, which explained 72.55% of the variation in the data. With the use of ordinal regression analysis, it was discovered that these four criteria have a considerable impact on investors’ trust and confidence in stockbrokers.Research limitations/implicationsThe current study, which is being conducted at the state level, might be expanded to include the entire country. It might be possible to look into the impact of retail capital market investment on rural investors. The research might be expanded to include a look at how reforms affect the functioning of stock markets. A study on the awareness of retail investment trends among women investors could be conducted. It is possible to investigate the ramifications of internet stock trading in India. It is possible to investigate the impact of technical innovation on capital markets. In this study, a survey has been conducted, in the future, the behavior of the investors can be observed to analyze whether they are satisfied with the services of stockbrokers or not.Practical implicationsThis research would be extremely beneficial to investors who make investment decisions and employ stockbrokers to help them make those selections. Because with the aid of the factors revealed investors can match the service quality of their own intermediary and only if they will be satisfied they will trust their intermediary.Social implicationsThis research will aid stockbrokers in providing investors with efficient and effective services. As they will have knowledge about the needs and aspirations of their clients, they will try to render their services as per their expectations. This will ultimately lead to the satisfaction of the retail equity investors, and they will have trust and confidence in the services provided by the stockbrokers. The present study helps the stockbrokers in understanding the fact that the qualitative aspects of their services are crucial for building investors’ trust and confidence otherwise investors will not be satisfied with their services. This study is extremely important for government as well. They can also take cues from witnessed the positive impact of their regulations on the quality of the stockbrokers’ services. This improvement in the quality of stockbroker services has further enhanced the trust and confidence of investors. Regulations are essential for improving the quality of stockbrokers’ services.Originality/valueThis paper reveals that a variety of factors, i.e. satisfaction with stockbroker services, stockbroker regulations, stockbroker transactional services and stockbrokers’ image in the eyes of investors influence retail equities investors’ trust and faith in brokerage services.

EFFECT OF PRANAYAMA (SPECIFIED BREATHING EXERCISE) ON STRESS & ANXIETY AMONG THE STUDENTS IN TRINCOMALEE CAMPUS, EASTERN UNIVERSITY SRI LANKA

Introduction: Due to the competitiveness among the society which increases with the current lifestyle and education system, most of the students, especially the University students are under Stress & Anxiety1. Pranayama meant an Alternative nostril breathing exercise and it is a cost-free, amazing therapy. Objective: This study was conducted to evaluate the effect of Pranayama on Stress and Anxiety and the Pulse rate among the selected students from the Faculty of Applied Science, Trincomalee Campus, Eastern University Sri Lanka. Methodology: This is a randomized control experimental study. Screening was done by using the tool of the Hamilton Rating Scale for Anxiety (HMA-A or HARS- 1959)2. Among the 460 hostel students, 120 participants were selected based on the inclusive, exclusive & diagnostic criteria. They were divided into two groups by a random selection process; 60 participants from the study group were only performed Pranayama daily for 15 minutes in the morning and the evening for 48 days. The remaining 60 in the control group were not engaged with any breathing exercise or any type of physical exercise. The data was analyzed using SPSS. Results: A reduction in Stress & Anxiety level scores from 16 ± 4.7 to 8 ± 3.3 after practicing Pranayama. An extremely significant ‘p’ value of less than 0.001 was obtained. And also it showed a mild reduction in pulse rate from 74.9 ± 6.4 to 73.2 ± 2.7 bpm too. Conclusion: Regular practice of Pranayama for a certain period is beneficial to reduce the Stress and Anxiety level and regulating the pulse rate.

Factors Junior High School Teachers Consider When Assigning Grades to Student’s Performance

The purpose of the study was to discover the academic and non-academic aspects that teachers in the Jomoro District evaluate when grading their students' performance. Descriptive survey design in conjunction with the quantitative method was used. Participants included 160 teachers who were chosen from 40 public Junior High Schools in the Jomoro District using stratified proportionate and simple random selection processes. The study's instrument was a questionnaire with 26 items and a reliability value of .70. Means and standard deviations, frequency distribution, and percentages, as well as One-Way Multivariate Analysis of Variances (MANOVA) were used to analyze the data. The Teachers at the Jomoro District's Junior High Schools take into account students' project, class test, homework, and group work results, according to the findings. Teachers at the Jomoro District's Junior High Schools use the scores of students' project, class test, homework, group work, and the end of term examination as academic factors when grading the students' performance at the end of the term, according to the findings. In addition, when it came to grading processes, there was no statistically significant difference in teacher qualification.

Stochastic Variational Approach to Small Atoms and Molecules Coupled to Quantum Field Modes in Cavity QED.

In this work, we present a stochastic variational calculation (SVM) of energies and wave functions of few particle systems coupled to quantum fields in cavity QED. The spatial wave function and the photon spaces are optimized by a random selection process. Using correlated basis functions, the SVM approach solves the problem accurately and opens the way to the same precision that is reached the nonlight coupled quantum systems. Examples for a two-dimensional trion and confined electrons as well as for the He atom and the H_{2} molecule are presented showing that the light-matter coupling drastically changes the electronic states.

Metagenomic evidence for co-occurrence of antibiotic, biocide and metal resistance genes in pigs

Antibiotic-resistant pathogens constitute an escalating public health concern. Hence a better understanding of the underlying processes responsible for this expansion is urgently needed. Co-selection of heavy metal/biocide and antibiotic resistance genes (ARGs) has been suggested as one potential mechanism promoting the proliferation of antimicrobial resistance (AMR). This paper aims to elucidate this interplay and exploit differences in antibiotic usage to infer patterns of co-selection by the non-antibiotic factors metals and biocides in the context of pig farming. We examined 278 gut metagenomes from pigs with continuous antibiotic exposure, only at weaning and at no exposure. Metals as growth promoters and biocides as disinfectants are currently used with little restrictions in stock farming. The pigs under continuous antibiotic exposure displayed the highest co-occurrence of ARGs and other genetic elements while the pigs under limited use of antibiotics still showed abundant co-occurrences. Pathogens belonging to Enterobacteriaceae displayed increased co-occurrence phenomena, suggesting that this maintenance is not a random selection process from a mobilized pool but pertains to specific phylogenetic clades. These results suggest that metals and biocides displayed strong selective pressures on ARGs exerted by intensive farming, regardless of the current use of antibiotics.

The use of functional stylistics in analyzing a portion of “The Wedding Dance”

This paper aims to analyze the transitivity patterns used in one of the most prominent short stories in Philippine Contemporary Literature “The Wedding Dance” which was written by a renowned writer Amador T. Daguio. This study is based on Halliday’s framework of transitivity analysis to delve on the meaning of the story in the literary discourse. This paper used the simple random sampling among the short stories in the Grade 7 English Learning Material from the Department of Education. In addition, the story is divided into three parts according to the number of sentences. Subsequently, part of the story has been identified and selected as basis for the analysis through random selection process. Furthermore, the paper used all 15 sentences from the first portion of the short story to be analyzed and interpreted using the functional stylistics. Analyzing and interpreting a portion of the short story in the context of functional stylistics played an integral part for it provided a portion of in depth understanding and interpretation of how each process type works and functions. It is also evident that the distribution of process type varies in different yet meaningful ways. Thus, by examining the transitivity process in the text is indeed indispensable for it explained how the field of the situation is being constructed, and have clear idea how transitivity patterns reflected the nature of the text.

Struggling With Business Corporate Cynical Impression? Powerful Methods of CSR to Enhance Corporate Image and Consumer Purchase Intention.

This study focuses on the perception of Chinese students about the image of the company and their purchase intention if the organization has a business cynical impression in the minds of its targeted customers. The study proposed three different types of corporate social responsibility (CSR) to cope up with the organizational cynical impression. These types are Economic and Legal CSR, Philanthropic CSR, and Ethical CSR. The main objective of this study is to determine which CSR type is better to reduce the corporate cynical impression on corporate image and the purchase intentions of consumers. In the study design, the bootstrap approach and AMOS 24 were employed to deal with mediation. The researchers recruited 500 individuals from different educational institutions in China using a simple random selection process. The outcomes of this study indicated that all three types of CSR are successful in mitigating the detrimental effects of corporate cynicism on the image of a firm and the purchase intentions of consumers. A more effective technique of boosting the corporate image of a company and purchase intention of a consumer is via charitable CSR, which may help restore the image of a company and the purchase intention of a consumer that has been affected by corporate cynicism among its target customers.

Compressive sensing based routing and data reconstruction scheme for IoT based WSNs

Data acquisition problem on large distributed wireless sensor networks (WSNs) is considered as a challenge in the growth of Internet of Things (IoT). Recently, the combination of compressive sensing (CS) and routing techniques has attracted much attention of researchers. An open question of this combination is how to integrate these techniques effectively for specific tasks. On the other hand, CS data reconstruction process is considered as one of the CS challenges because it requires to recover N data from only M measurement where M< <N. Through this paper, we propose a new scheme for data gathering in IoT based heterogeneous WSN that includes a new effective Deterministic Clustering using CS technique (DCCS) to handle the data acquisition problem. DCCS reduces the total overhead computational cost needed to self-organize WSN using a simple approach and then uses CS at each sensor node to decrease the overall energy consumption and increase the network lifetime. The proposed scheme includes also an effective CS reconstruction algorithm called Random Selection Matching Pursuit (RSMP) to improve the recovery process at the base station (BS). RSMP adds a random selection process during the forward step to give the opportunity for more columns to be selected as an estimated solution in each iteration. The simulation results show that the proposed scheme succeeds to minimize the overall network power consumption and prolong the network lifetime beside provide better performance in CS data reconstruction.

On the Mistaken Use of the Chi-Square Test in Benford’s Law

Benford’s Law predicts that the first significant digit on the leftmost side of numbers in real-life data is distributed between all possible 1 to 9 digits approximately as in LOG(1 + 1/digit), so that low digits occur much more frequently than high digits in the first place. Typically researchers, data analysts, and statisticians, rush to apply the chi-square test in order to verify compliance or deviation from this statistical law. In almost all cases of real-life data this approach is mistaken and without mathematical-statistics basis, yet it had become a dogma or rather an impulsive ritual in the field of Benford’s Law to apply the chi-square test for whatever data set the researcher is considering, regardless of its true applicability. The mistaken use of the chi-square test has led to much confusion and many errors, and has done a lot in general to undermine trust and confidence in the whole discipline of Benford’s Law. This article is an attempt to correct course and bring rationality and order to a field which had demonstrated harmony and consistency in all of its results, manifestations, and explanations. The first research question of this article demonstrates that real-life data sets typically do not arise from random and independent selections of data points from some larger universe of parental data as the chi-square approach supposes, and this conclusion is arrived at by examining how several real-life data sets are formed and obtained. The second research question demonstrates that the chi-square approach is actually all about the reasonableness of the random selection process and the Benford status of that parental universe of data and not solely about the Benford status of the data set under consideration, since the focus of the chi-square test is exclusively on whether the entire process of data selection was probable or too rare. In addition, a comparison of the chi-square statistic with the Sum of Squared Deviations (SSD) measure of distance from Benford is explored in this article, pitting one measure against the other, and concluding with a strong preference for the SSD measure.

Tree marking versus tree selection by harvester operator: are there any differences in the development of thinned Norway spruce forests?

ABSTRACT In Europe, Norway spruce forests are facing challenges due to climate change. One possible adaptive option is to enhance the resilience of forests by thinning. Usually, thinning requires two working steps: (i) tree marking by a forest manager and (ii) the harvesting operation. Since the typical tree selection procedure by forest managers is expensive and time consuming, the integration of the tree selection process in the harvesting operation is of high interest. In this paper, we examined four tree selection methods on 21 experimental plots located within eight Norway spruce stands and assessed their impact on the future stand development. The future stand development by tree selection methods was examined by means of a simulation study using the tree growth model MOSES (MOdeling Stand rESponse). The selection methods were (i) tree selection by forest managers, (ii) tree selection by the harvester operator as part of a fully mechanized harvesting system. Since we used the tree growth model MOSES, we additionally employed (iii) a random tree selection process implemented in MOSES, and (iv) a control simulation assuming no thinning. The Norway spruce stands are located in Lower Austria. The results show that 70% of the trees selected by the forest managers were identical to those chosen by the harvester operator and thus no significant differences in the key stand parameters after a 50-year simulation is detectable. Our study suggests that the tree selection for thinning by a trained harvester operator is a cost-efficient and fast method.

Deterministic clustering based compressive sensing scheme for fog-supported heterogeneous wireless sensor networks.

Data acquisition problem in large-scale distributed Wireless Sensor Networks (WSNs) is one of the main issues that hinder the evolution of Internet of Things (IoT) technology. Recently, combination of Compressive Sensing (CS) and routing protocols has attracted much attention. An open question in this approach is how to integrate these techniques effectively for specific tasks. In this paper, we introduce an effective deterministic clustering based CS scheme (DCCS) for fog-supported heterogeneous WSNs to handle the data acquisition problem. DCCS employs the concept of fog computing, reduces total overhead and computational cost needed to self-organize sensor network by using a simple approach, and then uses CS at each sensor node to minimize the overall energy expenditure and prolong the IoT network lifetime. Additionally, the proposed scheme includes an effective algorithm for CS reconstruction called Random Selection Matching Pursuit (RSMP) to enhance the recovery process at the base station (BS) side with a complete scenario using CS. RSMP adds random selection process during the forward step to give opportunity for more columns to be selected as an estimated solution in each iteration. The results of simulation prove that the proposed technique succeeds to minimize the overall network power expenditure, prolong the network lifetime and provide better performance in CS data reconstruction.

Should vaccination be mandated? Individuals' perceptions on mandatory vaccination in Greece.

ObjectivesThe aim of this study was to explore factors that influence individuals' attitudes towards mandatory vaccination in Greece.MethodsA nationally representative cross‐sectional telephone survey was conducted via a random multistage selection process in October 2019 in Greece. The survey was designed to obtain information about whether vaccination should be mandated or not among adults 18 years of age or older. A multivariable logistic regression model was used to estimate the association between individuals' sociodemographic, contextual and clinical characteristics, utilization, satisfaction, and trust in the healthcare system and providers and their preference over mandatory vaccination.ResultsA total of 901 participants fully completed the survey (response rate 90%‐901/1001). About 85% of the respondents supported mandatory vaccination. Individuals who used preventive services more often compared to those who never or rarely used such, those who reported increased trust in official healthcare authorities' guidelines and recommendations compared to those who reported no trust and those who had underage children living in the household were significantly more likely to support mandatory vaccination. No differences were observed for sociodemographic factors and mandatory vaccination support.ConclusionThis survey revealed that most Greek citizens support mandatory vaccination, which was critically affected by the utilization of preventive services and trust in healthcare authorities. Our results suggest that healthcare policy interventions should promote mandatory vaccination through multi‐level initiatives to improve healthcare providers' and the general public's understanding of the value of vaccination.

The factor structure of the Center for Epidemiological Study - Depression Scale in people with multiple sclerosis

Background: Depression is common in multiple sclerosis (MS); however, its assessment is complicated by biological processes. In this context it is important to consider the performance of depression screening measures including that their factor structure is consistent with expectation. This study sought to identify the factor structure of the Center for Epidemiological Study - Depression Scale (CES-D) in people with MS (PwMS). Methods: Participants (N = 493) were those who had consented to take part in a large three-phase longitudinal study of depression in PwMS. CES-D questionnaires completed at phase 1 of the study were utilised. An error in the questionnaire meant it was most appropriate to consider data for 19 of the 20 CES-D questionnaire items. The data was split into two samples by a random selection process to create an exploratory, model development sample and a validation sample. The first sample was subject to confirmatory factor analysis. Following examination of model fit and specification errors, the original model was modified. The revised model was tested in the confirmation sample to assess reproducibility. Results: The analysis results supported the original four factor solution for the CES-D, that is: Depressed Affect, Positive Affect, Somatic Complaints/Activity Inhibition, and Interpersonal Difficulties. Conclusions: The CES-D appears to have a coherent structure with which to examine depression in PwMS.

Comparative Study of Nebulization with Salbutamol vs Saline Solution at the Acute Phase of Bronchiolitis of 100 Children Aged 1 to 23 Months

Introduction: Infant bronchiolitis is the most common acute viral infection infection of the lower respiratory tract in children. Many pharmacological interventions have been suggested, including bronchodilators, yet the efficacy of bronchodilators in the treatment of this infection is still controversial.
 Objectives: To evaluate the effect of nebulization of salbutamol vs. saline solution in the acute phase of bronchiolitis.
 Materials and Methods: Using a randomized selection process, 52 infant patients received salbutamol, and 48 received a saline solution. The patients included in the study were aged 1 to 23 months and presented with their first episode of wheezing. During patient selection, we excluded children who were asthmatic or had other pulmonary issues prior to their bronchiolitis episode. Three nebulizations were performed for each patient, at one-hour intervals, after admission to the hospital. Wang's score and oxygen saturation were recorded for each patient on arrival, then at 30 minutes after each nebulization.
 Results and Conclusion: During the treatment period (which lasts three hours), the mean Wang score decreased from 7 to 3.5, and the mean oxygen saturation increased from 92.5% to 95.6%. Statistical analysis of the data, based on a parametric statistical test of the Student type (T-test), shows that there is no significant difference between nebulization with salbutamol and those given saline solution. The evolution of the clinical scores leads to the general conclusion that we cannot recommend using salbutamol nebulization over saline solution for the treatment of bronchiolitis.