scholarly journals Contribution of changing precipitation and climatic oscillations in explaining variability of water extents of large reservoirs in Pakistan

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ibrar ul Hassan Akhtar ◽  
H. Athar
Keyword(s):  
Water Availability ◽  
Regression Models ◽  
Precipitation Amount ◽  
Average Error ◽  
Linear Regression Models ◽  
Climatic Oscillations ◽  
Major Threat ◽  
Storage Reservoirs ◽  
Multiple Linear Regression Models

AbstractMajor threat that Pakistan faces today is water scarcity and any significant change in water availability from storage reservoirs coupled with below normal precipitation threatens food security of more than 207 million people. Two major reservoirs of Tarbela and Mangla on Indus and Jhelum rivers are studied. Landsat satellite’s data are used to estimate the water extents of these reservoirs during 1981–2017. A long-term significant decrease of 15–25% decade−1 in water extent is found for Tarbela as compared to 37–70% decade−1 for Mangla, mainly during March to June. Significant water extents reductions are observed in the range of −23.9 to −53.4 km2 (1991–2017) and −63.1 to −52.3 km2 (2001–2010 and 2011–2017) for Tarbela and Mangla, respectively. The precipitation amount and areas receiving this precipitation show a significant decreasing trend of −4.68 to −8.40 mm year−1 and −358.1 to −309.9 km2 year−1 for basins of Mangla and Tarbela, respectively. The precipitation and climatic oscillations are playing roles in variability of water extents. The ensuing multiple linear regression models predict water extents with an average error of 13% and 16% for Tarbela and Mangla, respectively.

scholarly journals Linear Regression Models Used for the Description of Long-Term Epizootic Process in Tuvinian Natural Plague Focus (Karginsk Mezofocus)

2012 ◽  
pp. 43-47
Author(s):  
N. A. Kol ◽  
A. F. Chul'dum ◽  
M. G. Rostovtsev ◽  
Yu. A. Kalush
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Regression Models ◽  
Stepwise Regression ◽  
Climatic Conditions ◽  
Linear Regression Models ◽  
Epizootic Process ◽  
Multiple Linear Regression Models

The results of modeling showed the dependence of epizootic activity in Tuvinian natural plague focus on climatic conditions (average monthly amount of precipitations in the current year and the preceding four years and temperatures in the current and the preceding three years). The multiple linear regression models were used to predict the activity of zoonosis development within a year. The models obtained by means of stepwise regression were most approximated to the natural zoonotic process. The amount of precipitations in winter months and temperature in spring and summer were of the greatest significance for epizootic activity.

scholarly journals Impact of Inflation and Unemployment on Economic Growth of Pakistan

2021 ◽  
Vol 6 (4) ◽  
pp. 282-288
Author(s):  
Muhammad Ramzan
Keyword(s):  
Economic Growth ◽  
Diagnostic Tests ◽  
Regression Models ◽  
Error Term ◽  
Least Square ◽  
Linear Regression Models ◽  
Ordinary Least Square ◽  
White Test ◽  
Multiple Linear Regression Models

This paper aims to identify the influence of inflation and unemployment on the economic growth of the country. This study recommends some essential policies about unemployment and inflation in the economic growth of Pakistan. In this study, the “Ordinary Least Square (OLS)” method is used with different diagnostic tests for determining the fitness of data for the investigation; and the data is collected from 1980 to 2018. The econometric results suggest that the time series is stationary because the values of t-statistic are more than t-tab and sig value is also significant. The error term on ADF is significant and that ensures that there is long term association. The results of ECM indicate that inflation and unemployment are away from the value of equilibrium. The results of multiple linear regression models indicate that inflation and unemployment are statistically insignificant, and the overall model is also statistically insignificant. There is no multicollinearity and there is no heteroscedasticity as per White test. By running the Ramsay Reset test, the researcher concludes that the model is not specified because the sig value of the t-test and f-test is significant.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

scholarly journals Isotonic quadriceps endurance is better associated with daily physical activity than quadriceps strength and power in COPD: an international multicentre cross-sectional trial

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Erik Frykholm ◽  
Sarah Gephine ◽  
Didier Saey ◽  
Arthur Lemson ◽  
Peter Klijn ◽  
...  
Keyword(s):  
Physical Activity ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Regression Models ◽  
Sedentary Time ◽  
Quadriceps Strength ◽  
Linear Regression Models ◽  
Cross Sectional ◽  
Quadriceps Function ◽  
Multiple Linear Regression Models

AbstractKnowledge about modifiable determinants of daily physical activity (PA) in patients with chronic obstructive pulmonary disease (COPD) is crucial to design effective PA interventions. The present study aimed to determine the contribution of quadriceps strength, power and endurance to daily PA in COPD. Additionally, for quadriceps endurance, we also aimed to determine to what extent the association varies according to the mode of movement (isotonic, isometric, or isokinetic). Using a multicentre cross-sectional trial design we determined the contribution of quadriceps function to daily PA (steps, sedentary time and time spent doing moderate-to-very-vigorous physical activity [MVPA]) using bivariate and partial Pearson correlation analysis (r) and multiple linear regression models (ΔR2). Pre-determined controlling factors were sex, age, body mass index (BMI), COPD-assessment test, forced expiratory volume in one second in percent of the predicted value (FEV1pred), and distance walked on the 6-minute walk test. Eighty-one patients with COPD (mean ± SD: age 67 ± 8 years, FEV1pred 57 ± 19%, daily steps 4968 ± 3319, daily sedentary time 1016 ± 305 min, and MVPA time 83 ± 45 min) were included. Small to moderate bivariate correlations (r = .225 to .452, p < .05) were found between quadriceps function and measures of PA. The best multiple linear regression models explained 38–49% of the variance in the data. Isotonic endurance was the only muscle contributor that improved all PA models; daily steps (ΔR2 = .04 [relative improvement 13%] p = .026), daily sedentary time (ΔR2 = .07 [23%], p = .005) and MVPA-minutes (ΔR2 = .08 [20%], p = .001). Isotonic endurance was also independently associated with most PA variables, even when controlling for strength, power or isometric-isokinetic endurance properties of the muscle (r = .246 to .384, p < .05). In contrast, neither strength, power, isometric-or isokinetic endurance properties of the muscle was independently associated with PA measures when controlling for isotonic endurance (r = .037 to .219, p > .05). To conclude, strength, power, and endurance properties of the quadriceps were low to moderately associated with PA in patients with COPD. Isotonic quadriceps endurance was the only quadriceps property that was independently associated with the different measures of PA after controlling for a basic set of known determinants of PA, quadriceps strength or power, or isometric or isokinetic quadriceps endurance. Future longitudinal studies should investigate its potential as a modifiable determinant of PA.

Prédiction de la composition corporelle post-mortem de cerfs de Virginie (Odocoileus virginianus) à partir de mesures morphologiques et massiques

1997 ◽  
Vol 75 (11) ◽  
pp. 1790-1795 ◽  
Author(s):  
Chantal Bois ◽  
Michel Crête ◽  
Jean Huot ◽  
Jean-Pierre Quellet
Keyword(s):  
Odocoileus Virginianus ◽  
Regression Models ◽  
Carcass Composition ◽  
Chemical Analyses ◽  
Linear Regression Models ◽  
Mass Measurements ◽  
Composition Corporelle ◽  
Independent Variables ◽  
Multiple Linear Regression Models ◽  
Field Stations

Morphologic and mass measurements were taken on 24 complete white-tailed deer (Odocoileus virginianus) carcasses of varying ages and both sexes in southern Quebec. Each carcass was divided into three parts (skin, viscera, rest) to determine water, protein, fat, and ash content by chemical analyses. Fat content of carcasses varied between 0.8 and 17.4%. Multiple linear regression models were selected to predict carcass composition from morphologic and mass measurements. Two situations were considered: measurements taken at the laboratory on whole animals and measurements taken at field stations on eviscerated carcasses provided by hunters. All selected models can be applied to any deer without taking into account age or sex; they include 1 – 4 independent variables. For whole animals, adjusted R2 of models varied between 0.99 (water) and 0.89 (ash); models developed for field stations were less precise, the lowest R2 values being 0.82 and 0.73 for ash and fat, respectively. These models can be useful for research and management purposes.

scholarly journals Association between Anxiety, Quality of Life and Academic Performance of the Final-Year-Students in Latvia

2021 ◽  
Vol 18 (11) ◽  
pp. 5784
Author(s):  
Inta Zile ◽  
Ieva Bite ◽  
Indra Krumina ◽  
Valdis Folkmanis ◽  
Lilian Tzivian
Keyword(s):  
Quality Of Life ◽  
Longitudinal Study ◽  
Regression Models ◽  
Linear Regression Models ◽  
Academic Achievements ◽  
School Year ◽  
And Gender ◽  
Type Of School ◽  
Multiple Linear Regression Models

The main objective of this study was to investigate the association between final-year students’ anxiety level and quality of life (QOL) with their academic achievements. A longitudinal study was performed in regular schools and in high-rated gymnasiums at the beginning and at the end of the school year. Multiple linear regression models were built for the association between level of anxiety/QOL with academic achievements. Type of school and gender—but not the level of anxiety—were the main predictors of academic achievements of 287 adolescents (e.g., for mathematics, the effect estimates were: β = −1.71 [95% confidence interval −2.21; −1.21]; β = −0.50 [−0.95; −0.06], β = 0.09 [−0.02; 0.20] for the type of school, gender, and changes in level of anxiety, respectively). To conclude, particular efforts should be made to reduce the level of anxiety in girls, especially those that study in high-rated schools.

scholarly journals FAKTOR-FAKTOR YANG MEMPENGARUHI PRODUKSI SUSU SAPI PERAH KELOMPOK TANI TERNAK SAPI PERAH (KTTSP) KANIA, KABUPATEN BOGOR

2019 ◽  
Vol 11 (2) ◽  
pp. 148-160
Author(s):  
Adam Adinegoro ◽  
Edmon Daris ◽  
Zulmanery Z
Keyword(s):  
Linear Regression ◽  
Dairy Cattle ◽  
Multiple Linear Regression ◽  
Milk Production ◽  
Regression Models ◽  
Linear Regression Models ◽  
Factors Affecting ◽  
Cattle Ranchers ◽  
Multiple Linear Regression Models

The purpose of this study are: (1) to identify and to analyze the factors that influence milk production of dairy cattles, and (2) to determine the elasticity of milk production. This research was conducted at the Dairy cattle group KANIA, Bogor. Data were obtained from interviews and questionnaires with cattle ranchers. Multiple linear regression models and elasticity calculations were employed to analyze the data with the Excel 2007 and software for Statistical Product and Service Solution (SPSS) version 16. Results of the analysis revealed that the factors affecting milk production is labor, forages, and feed concentrates. The result of the calculation of the elasticity indicated that all production variables are elastic variables.

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