Prediction of winter minimum temperature of Kolkata using statistical model

MAUSAM ◽  
2021 ◽  
Vol 57 (3) ◽  
pp. 451-458
Author(s):  
TAPAN KANTI CHAKRABORTY

Lkkj & dksydkrk ¼vfyiqj½ ds U;wure rkieku dk okLrfod iwokZuqeku 12 ?kaVs iwoZ tkjh djus ds mn~ns’; ls ik¡p izkpyksa ij vk/kkfjr cgq jSf[kd lekJ;.k ekWMy fodflr fd;k x;k gS A blds iwoZ lwpdksa dk p;u vfyiqj os/k’kkyk ls izkIr lrg vk¡dM+ksa rFkk ekSle dk;kZy; dksydkrk ds fuEu Lrj ds iou vk¡dM+ksa ds vk/kkj ij fd;k x;k gS A ;g ekWMy 237 fnuksa ds ¼o"kZ 1997&2000 dh vof/k ds tuojh ,oa Qjojh ekg ds½ vk¡dM+ksa ds uewuksa rFkk dkQh yach vof/k ¼o"kZ 1988&2004½ ds U;wure rkieku ds vk¡dM+ksa es fLFkjrk dh tk¡p ds vk/kkj ij fodflr fd;k x;k gS A bl ekWMy dh tk¡p 178 fnuksa ds vk¡dM+ksa ds Lora= uewus ds vk/kkj ij dh xbZ gS A bl ekWMy dh {kerk dh tk¡p lkaf[;dh; vk¡dM+ksa ds vk/kkj ij dh xbZ gS vkSj bls ldkjkRed ik;k x;k gSA bl ekWMy dk mi;ksx ekSle iwokZuqekudRrkZ }kjk U;wure rkieku ds iwokZuqeku dk vkdyu djus ds fy, fd;k tk ldrk gS vkSj ;fn ckny rFkk iou dh xfr ds :[k esa ckn esa ifjorZu laHkkfor gks rks mlesa lq/kkj fd;k tk ldrk gS A  Five parameter multiple linear regression model for objective forecasting of minimum temperature of Kolkata (Alipore) with 12 hours lead period has been developed. The predictors are chosen from the available surface data of Alipore observatory and low level wind data of M. O. Kolkata. Model has been developed from data sample comprising of 237 days (in January and February, period: 1997 – 2000) after stationarity test of minimum temperature data of much longer period (1988–2004). The model is tested with independent sample of 178 days. Efficiencies of the model have been tested with statistical skill score and found to be positive. The model can be used by the forecaster for assessing prediction minimum temperature and modify if cloud cover and wind flow pattern are expected to change subsequently.  

Author(s):  
Mahdi Abrar

The objective of this research is to see the influence of weather on the prevalence of Newcastle Disease (ND) in chicken in Kabupaten Aceh Utara (North Aceh). Data used in this research were obtained from Dinas Peternakan North Aceh for the number of chicken suffered ND and from Badan Meteorologi dan Geofisika Lhokseumawe, North Aceh for the form of weather. Multiple Linear Regression Model with five independent variables (the average of rainfall per month, the average of maximum temperature, the average of minimum temperature, the velocity of the wind, and the average of humidity per month) was used to see the influence of wheather to the prevalence of Newcastle Disease. Proportion the number of chicken suffered from ND which is the ratio of the number of chicken suffered from ND to the total number of chicken was used as dependent variables. The result shows that the best model is Ŷ= 120.529278 – 1.33 x wind humidity + 1.907 x wind velocity.


2018 ◽  
Author(s):  
Afriyeni

This study aims to determine the effect of each component contained in profitability as ROA , ROE , ROA, and NPM on the price of bank shares listed on the Indonesia Stock Exchange. Object of this research is the price of bank shares listed on the Indonesia Stock Exchange . Statistical model used in this study is a multiple linear regression model . Hypothesis testing is done in two ways, namely t statistical test (t-test) for the partial test and F test (Tes -F) to examine the effect of study variables simultaneously. The results based on t-tests from 2008 to 2012 found that profitability consisting of ROA, ROE, ROA, and NPM significant effect on stock price movements studied banking. Based on the F-test results obtained the overall study, that earnings have a significant effect on stock prices in 2008, with a significance level of 0.107 and in 2012 with a significance level of 0.140, while in 2009, 2010, and 2011 earnings no significant effect on stock prices , where in 2009, with a significance level of 0.644 , in 2010 with a significance of 0.788 and in 2011 with a significance of 0.527 .


2002 ◽  
Vol 18 (6) ◽  
pp. 835-844 ◽  
Author(s):  
Christian Nellemann ◽  
Stein R. Moe ◽  
Lucas P. Rutina

Spatial vegetation utilization of elephants was investigated within mixed woodland savanna along the Chobe River in northern Botswana in the dry season of 1998. Using multiple linear regression, accumulated stem breakage by elephants was predicted by a terrain index, distance to water, stand density, number of trees > 4 m tall, tree height, density of Combretum apiculatum, C. elaeagnoides, C. mossambicense and the density of other (accumulated) tree species. Within mixed woodland at 2–7 km distance from the river fine-grained terrain ruggedness was the most important factor contributing to 55% of observed differences in use by elephants, while distance to water and the density of C. apiculatum contributed an additional 20% and 4%, respectively to the multiple linear regression model. Stem breakage was, on average, almost twice as high in rugged terrain compared with flat terrain at similar distance to water within the same vegetation type. Rugged terrain had 2–3-fold higher proportion of plots with very high Combretum shrub densities. These results suggest that the terrain index may be useful in management, predicting the areas most sensitive to vegetation change in a woodland system with increasing elephant densities.


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