Road traffic accidents (RTA) are commonly encountered incidents that can cause injuries, death, and property damage to members of society. Ethiopia is one of the highest incident rates of road traffic accidents. Report of Transport and Communication from 2012 to 2014, shows an increment in the number of traffic accidents in Ethiopia. Amhara region accounted for 27.3% of the total road traffic accident-related deaths in Ethiopia during the year 2008/9, which is the highest share among all regions in Ethiopia. The current research aims to model the trend of injury, fatal and total road traffic accidents in the Amhara region from September 2013 to May 2017. Monthly reported traffic accidents were obtained from the traffic department of the Amhara region police commission. The most universal class of models for forecasting time series data called Auto-regressive Integrated Moving Averages (ARIMA) models were applied to model the trends and patterns of road traffic accident cases in the Amhara region. The average number of observed injury RTA, fatal RTA, and total RTA were 27.2, 14, and 78.2 per month respectively. It was observed that a relatively large number of RTA’s are reported on Tuesday, Thursday, and Saturday relative to other days of the week. The data also reveals that more than 60% of accidents involve drivers between the ages of 18–30 years. ARIMA (2,0,0) (1,0,0) ARIMA (2,0,0) and ARIMA (2,0,0) (1,1,0) were fitted as the best model for total injury accidents, fatal RTA and total RTA data respectively. A 48 months forecast was made based on the fitted models and it can be concluded that road traffic accident cases would continue at the non-decreasing rate in the Amhara region for the predicted periods. Therefore, the findings of this study draw attention to the importance of implementing improved better policies and close monitoring of road trafficking to change the existing non-decreasing trend of road traffic accidents in the region.

TVET plays a significant role in human resource development and, as a result, in a society’s progress and prosperity. The study is aiming at identifying the key factors influencing students’ academic success at polytechnic colleges. The study’s target population was regular Bahir Dar Polytechnic College students in the 2019/2020 academic year. Stratified random sampling was employed to conduct a cross-sectional survey of 536 participants. The author employed SPSS version 25 and WinBUGS 1.4 for quantitative data analysis. Bayesian logistic regression was used to model the factors that significantly influence TVET students’ academic achievement. Gender, age, family monthly income, study hours, stimulant use during the study, English language proficiency, EGSECE score, previous perceptions of TVET, teacher satisfaction, and field of study placement satisfaction were identified as factors that significantly influenced TVET students’ academic achievements. Being female, having a low family income, studying for a shorter period, using stimulants while studying, having a low English language proficiency, having a low EGSECE result, having a negative perception of TVET, and having low satisfaction with field of study were all linked to lower academic achievement in this study. According to the findings, students should spend more time in learning and consume fewer stimulants during their studies. The Ministry of Education should modify the TVET curriculum to aid students in improving their English language skills. Teachers in TVET should also receive ongoing capacity-building training. Finally, rather than imposing norms and limits (in terms of student achievement), TVET colleges should respect students’ free choice of training sector (department).