scholarly journals Estimating Sound Seeds per Cone in White Spruce

1989 ◽  
Vol 65 (4) ◽  
pp. 266-270
Author(s):  
W. H. Fogal ◽  
I. S. Alemdag
Keyword(s):  
Regression Model ◽  
Multiple Regression ◽  
Regression Models ◽  
White Spruce ◽  
Multiple Regression Model ◽  
Independent Variables ◽  
Independent Variable

White spruce cones were collected near Petawawa, Sudbury, and Oakville, Ontario during the 1982 and 1984 crop years. Cones were used to examine several regression models for estimating the number of sound seeds per cone as a function of seeds per cone section, cone length, and/or diameter. For the simplest models, using only one independent variable, highest coefficients of determination (R2) were found with sound seed per section. A multiple regression model, including all three independent variables and their interactions, was identified. It provided higher coefficients of determination than the model using sound seed per cone section as a single independent variable but did not provide much more precision for estimating sound seeds per cone. Regressions were specific for locations and crop years.

scholarly journals FAKTOR-FATOR YANG MEMPENGARUHI WISATAWAN MENGUNJUNGI PANTAI ZAKAT DI KOTA BENGKULU

2018 ◽  
Vol 6 (1) ◽  
Author(s):  
Syamsul Huda ◽  
Jalal Ikhwan
Keyword(s):  
Regression Model ◽  
Multiple Regression ◽  
Hypothesis Test ◽  
Multiple Regression Model ◽  
Test Stage ◽  
Dependent Variables ◽  
Independent Variable ◽  
To Come ◽  
Test Result

Syamsul Huda, Jalal Ikhwan; The research aims to determine the number of variables that affect tourists visiting Zakat beach in Bengkulu city. The population used is the visitors who visit Zakat beach. The type of data implemented is the primery daya. The way of implement it is by spreading out of questioners. The research puts on two variables. First, it is the independent variable. It consist of servicing, the trimming of the facilities, safety and earning. Where as the dependent variables focuses on the readability of the visitors to visit Zakat beach. The test stage are done by utilizing spss. To create the hypothesis test stages, it can apply the multiple regression model and t-statistic test. Building upon the hypothesis test result, it has been uncovered that the quality of servicing and safety have significant effects to the readibility of the visitors to come to see Zakat beach in Bengkulu city of Bengkulu province. It can be concluded that the trimming of the facility and earnings do not make significant effects towards the viusitors readability to pay a visit to Zakat beach.Key Words: Service, Facilities, Security and Income.

scholarly journals A Study on the Prediction of Daily Snowmelt Depth using Multiple Linear Regression

2020 ◽  
Vol 20 (6) ◽  
pp. 311-321
Author(s):  
YeoungRok Oh ◽  
Gyumin Lee ◽  
Kyung Soo Jun ◽  
Wooyeon Sunwoo ◽  
SeungWoo Baek ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Snow Depth ◽  
Meteorological Data ◽  
Multiple Regression Model ◽  
Independent Variables ◽  
Fresh Snow ◽  
Humidity Range

In this study, daily snowmelt was predicted using observed meteorological data and multiple regression analysis. Five observation stations (located in Daegwallyeong, Gwangju, Seosan, Mokpo, and Jeonju) were selected to analyze fresh snow depth from 2000 to 2010. The dependent variable used in the multiple regression analysis was daily snowmelt depth, and the independent variables were fresh snow depth, diurnal temperature range, temperature interception, diurnal humidity range, humidity intercept, and solar radiation. Seventy percent of the total observed data was used to develop a multiple regression model and the regression model was verified using the 30% of remaining data. The adjusted R-squared and Root Mean Square Deviation (RMSE) were used to examine the developed regression model. As a result, the adjusted R-squared was higher than 0.769 (except Daegwallyeong); thus the developed model represented well the daily snowmelt depth. Even Jeonju had an adjusted R-squared of 0.869. Also, the RMSE in all of the five stations was lower than 2.5 cm. The lowest value in Seosan was 1.7 cm. From the two types of verification, the developed multiple regression model was judged to be suitable to predict the daily snowmelt depth. However, multicollinearity should be explained, as rapid increases in temperature and sustained high temperature could not be reflected in the model. Therefore, if the limitations were resolved in further research, the model could be used to predict the amount of daily snowmelt depth more reliably.

Some Conditions Affecting the Utility of Subjectively Weighted Models in Decision Making

1979 ◽  
Vol 49 (2) ◽  
pp. 583-590 ◽  
Author(s):  
Lars Nystedt ◽  
Kevin R. Murphy
Keyword(s):  
Decision Making ◽  
Regression Model ◽  
Multiple Regression ◽  
Regression Models ◽  
Multiple Regression Model ◽  
Linear Multiple Regression ◽  
Multiple Regression Models ◽  
Highly Correlated ◽  
Degree Of Overlap

The accuracy of multiple regression models, models employing subjective weights and models employing relative subjective weights in reproducing judgments was studied. Multiple regression models were most accurate. When subjects were divided into two groups according to the degree of configurality shown in their matrix of subjective weights, striking differences were found in the degree of overlap of the multiple regression models and the models employing subjective weights. In particular, when subjective policies were essentially linear, the predicted judgments produced by these policies were highly correlated with the predicted judgments of the multiple regression models. When subjective policies were highly configural, the subjective models accounted for variance in judgments not accounted for by the linear multiple regression model.

Using trade show information to enhance company success: an empirical investigation

2012 ◽  
Vol 27 (5) ◽  
pp. 384-391 ◽  
Author(s):  
Harriette Bettis‐Outland ◽  
Wesley J. Johnston ◽  
R. Dale Wilson
Keyword(s):  
Regression Model ◽  
Multiple Regression ◽  
Information Acquisition ◽  
Value Of Information ◽  
Multiple Regression Model ◽  
Content Type ◽  
Independent Variables ◽  
Trade Show ◽  
Trade Shows ◽  
The Relationship

PurposeThis paper seeks to provide an exploratory empirical study of the variables that are part of the return on trade show information (RTSI) concept, which is based on the use and value of information gathered at a trade show.Design/methodology/approachThe research is designed to explore relationships and identify those variables that are a particularly important part of the RTSI concept. The paper provides an exploratory test of the relationship between a series of variables that are related to the value of information gathered at trade shows. Data were collected from trade show attendees approximately 60 days after the trade show. A multiple regression model was developed that explores the relationship between the dependent variable that focuses on information value and the independent variables on various aspects of information acquisition, information dissemination, and information use.FindingsThe final multiple regression model found a significant relationship for several variables and has an adjusted R2 value of 0.552. Four significant independent variables were identified – one each in the information use and the shared information categories and two in the information acquisition category. These findings present an interesting picture of how information is used within an organization after it is acquired at a trade show.Research limitations/implicationsThe research is limited by the multiple regression model used to explore the relationships in the data. Also, data from only one trade show were used in the model.Practical implicationsThis paper focuses on the intangible, longer‐term benefits as important considerations when determining the value of new trade show information to the firm. The evaluation of trade show information also should include these intangible benefits, such as improved interdepartmental relations or interactions as well as discussions with other trade show participants in finding new uses for information that impacts the company's future success, as well as shorter‐term benefits such as booth activity.Originality/valueThe paper offers a unique approach for determining the value of information acquired at trade shows. Though information gathering has been included as an outcome variable in previous trade show studies, no other research has studied the value of this new trade show information to the company.

scholarly journals RETURN ON INVESTMENT ANALYSIS OF UNLICENSED SOLAR ENERGY PROJECTS IN TURKEY

2020 ◽  
Vol 8 (1) ◽  
pp. 903-923
Author(s):  
Murat ERTUĞRUL ◽  
Mustafa Hakan SALDI
Keyword(s):  
Solar Energy ◽  
Regression Model ◽  
Multiple Regression ◽  
Return On Investment ◽  
Research Question ◽  
Multiple Regression Model ◽  
Power Capacity ◽  
Independent Variables ◽  
Energy Projects ◽  
Investment Rates

First of all, this study aims to show how the power size and currency affect the return on investment percentages of unlicensed solar energy projects in Turkey. Commonly, the investors have confusions on their minds while taking investment decisions. Particularly, there are definite variables which may affect a solar energy project’s return on investment percentage and so the research question of how a multiple regression model can represent this percentage comes back to minds too. In order to simulate investment scenarios, this study is designed by using the sample of unlicensed solar energy installations which have the capacity of 250 KW, 500 KW and 1000 KW. According to the cash flow analyses for these samples the effects of power size and currency variables to return on investment percentages are observed. Therefore, the multiple regression model of return on investment percentages is offered by taking into account the power capacity and currency as independent variables to estimate the future cash flows by comparing each cases. As a result, the correlations are observed between dependent variable and independent variables. Especially, the power capacity has significant effect on return on investment rates of projects in accordance with the fundamental rule of risk-reward relation in finance. Also, the share of currency risk is calculated to prove how the volatility in currency index may affect the return on investment rates.

scholarly journals PENGARUH JUMLAH ZAKAT PRODUKTIF, UMUR PRODUKTIF, JUMLAH TANGGUNGAN, DAN PENGAWASAN TERHADAP PRODUKTIVITAS USAHA (SURVEY PADA MUSTAHIK KABUPATEN PIDIE)

2020 ◽  
Vol 5 (2) ◽  
pp. 288-296
Author(s):  
Assafriani Assafriani ◽  
Meutia Fitri
Keyword(s):  
Regression Model ◽  
Multiple Regression ◽  
Secondary Data ◽  
Multiple Regression Model ◽  
Information Collection ◽  
Independent Variable ◽  
Variable Influence ◽  
And Control

This study aims to determine the influence of   productive zakat amount, productive age, dependents of mustahik, and controll towards  productivity of mustahik reaching. This research is conducted by taking samples of mustahik who earn productive zakat from Baitul Mal Pidie and chosen sample for 53 mustahik. The data and information collection used in this study was documentation technique. The data used was the secondary data which directly collected from Baitul Mal Pidie. The testing of independent variable influence toward the dependent variabel used this study was multiple regression model by using SPSS 23.The result of the reseach shows that simultaneously productive zakat amount,productive age, dependents of mustahik, and control have an effect productivity of mustahik reaching.   However partially only variable productive zakat amount and controll that effect the productivity of mustahik reaching. Productive age and dependents of mustahik are not affect the productivity of mustahik reaching

scholarly journals Effects of game location, quality of opposition, number of foreign players and anthropometric characteritics in elite handball games

Kinesiology ◽  
2017 ◽  
Vol 49 (2) ◽  
pp. 194-201 ◽  
Author(s):  
Thierry Debanne ◽  
Guillaume Laffaye
Keyword(s):  
Regression Model ◽  
Multiple Regression ◽  
Regression Models ◽  
Multiple Regression Model ◽  
Previous Season ◽  
High Contribution ◽  
Anthropometric Characteristics ◽  
Multiple Regression Models ◽  
The Difference

The aims of this study were (1) to investigate the influence of game location, quality of opposition, age of players, and anthropometric characteristics of backcourt and pivot players as well as the number of foreign players in a team on goal difference between the teams in the French (LNH) and German (Bundesliga) national men’s professional leagues, and (2) to predict goal difference of match final scores in these two national leagues using a multiple regression model. Archival data were obtained from the open access official websites to collect a sample of 165 handball matches (LNH [N=89], and Bundesliga [N=76]) of the first part of the 2015/2016 regular season. The linear regression model predicted the winner in 79% of cases with a mean accuracy of four goals. The coefficients of determination found in both multiple regression models were r²=.67 and r²=.49 for the LNH and the Bundesliga, respectively. The models revealed a high contribution of the difference in the end-of-previous season goal-average per match ranking and a moderate contribution of the game location to goal difference. The models also highlighted differences in the way games were won in these leagues with a contribution of foreigners, anthropometric characteristics and age only in the Bundesliga.

scholarly journals Determinants of Profitability of Indian Public Sector Banks

2016 ◽  
Vol 2 (3) ◽  
Author(s):  
Naresh Kedia
Keyword(s):  
Public Sector ◽  
Regression Model ◽  
Multiple Regression ◽  
Multiple Regression Model ◽  
Independent Variables ◽  
Public Sector Banks ◽  
Its Analysis ◽  
Interest Income ◽  
Net Profit

In this study, we have analyzed the determinants of profitability of Indian Public Sector Banks which reveals four independent variables that affect the net profit: Non-performing assets, Credit Deposit Ratio, Net Interest Income and Operating Expenses. We have used the Multiple Regression Model for its analysis. We found out that, only two of these independent variables i.e. Credit Deposit Ratio and Net Interest Income affect the net profitability of Indian Public Sector Banks in a major way.

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