scholarly journals Experimental and Statistical Study on Black Cotton Soil Modified with Cement–Iron Ore Tailings

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Paul Yohanna ◽  
Ianna M Kanyi ◽  
Roland K Etim ◽  
Oshioname A Ebere ◽  
Kolawole J Osinubi
Keyword(s):  
Regression Analysis ◽  
Analysis Of Variance ◽  
Iron Ore ◽  
Energy Levels ◽  
Black Cotton Soil ◽  
British Standard ◽  
Independent Variables ◽  
Compaction Test ◽  
Iron Ore Tailings ◽  
Dependent Variables

The investigation focused on the response of black cotton soil (BCS) treated with mixtures of iron ore tailings (IOT) and cement to varying compaction effort (CE). Preliminary tests showed that the un-treated soil is A-7-6 (22) on the basis of AASHTO protocols of classification while the USCS (Unified Soil Classification System) guidelines placed the soil in CH group. Laboratory tests carried out included cation exchange capacity, CEC, Specific gravity (Gs) and compaction test. Three compaction energy levels (i.e., British Standard heavy (BSH), West African Standard (WAS) and British Standard light (BSL)) were adopted for the compaction test. Test results showed that CEC decreased; Gs and MDD increased while OMC also decreased for all cement contents considered when admixed with the different IOT contents up to 10 % IOT by the soil dry weight. MDD values of 1.58, 1.59, 1.62, 1.64, 1.64 and 1.66 Mg/m3 were noted for 1% cement and 0, 2, 4, 6, 8 and 10% IOT content compacted with BSL energy. Also, OMC values of 21.2, 20.8, 20.5, 20, 20.3 and 20.2% were noted for 1% cement and 0, 2, 4, 6, 8 and 10% IOT content compacted with BSL energy. Same trend was noted for higher cement concentrations and compactive efforts. Regression models for MDD and OMC, considered as dependent variables while C (cement content), CE, IOT, Gs and PF (percentage of fine) as independent variables were developed using software (Mini-tab R15). The result of regression analysis shows that the independent variables considered greatly influence the dependent variables. ANOVA (Analysis of variance) was use to establish the levels of contributions of cement and IOT to the improvements recorded. Therefore, black cotton soil optimally treated with 4% cement 10% IOT blend and compacted with BSH energy is recommended for soil remediation or geotechnical engineering applications.  Keywords— Compaction effort, iron ore tailings, black cotton soil (BCS), Analysis of Variance, regression analysis.

Determination of specific activity of labeled ligands by nonlinear regression analysis

1993 ◽  
Vol 265 (5) ◽  
pp. E728-E735 ◽  
Author(s):  
J. A. Durr
Keyword(s):  
Regression Analysis ◽  
Nonlinear Regression ◽  
Binding Sites ◽  
Specific Activity ◽  
Specific Radioactivity ◽  
Nonlinear Regression Analysis ◽  
Independent Variables ◽  
Lysine Vasopressin ◽  
Dependent Variables

The specific radioactivity (SA) of 125I-lysine vasopressin (LVP) was determined by analyzing the binding B (cpm/tube) of variable amounts of tracer T (cpm/tube) to a constant amount of an LVP antibody, in the presence of known quantities L (mol/tube) of LVP standards. The parameters of the equations B = f(F) and B/F = g(T), describing B as a function of free F (cpm/tube) tracer or the ratios B/F as a function of T, were first calculated by nonlinear regression analysis of the results obtained with tracer alone. Then the dependent variables B or B/F were measured in the presence of LVP and analyzed with the same equations by substituting the independent variables F or T with (F + alpha FL) and (T + alpha L), respectively, where alpha (cpm/mol) represents a measure of the SA and FL (FL = L.F/T), free LVP, respectively. The SA was thus treated as an unknown parameter to be calculated by nonlinear regression. This method was compared with the traditional interpolation of the SA from the self-displacement and standard curves. Tracer and ligand were found to have the same affinity for the binding sites, since the set of equations B = f(F + alpha FL) and B/F = g(T + alpha L), describing the binding of the tracer in the presence of LVP and equations B = f(F) and B/F = g(T) to which these equations reduce in the absence of LVP (L = 0), had identical binding parameters. To be valid, any method based on self-displacement requires that the tracer and standards have the same affinity for the binding sites.(ABSTRACT TRUNCATED AT 250 WORDS)

ANALISIS PENGARUH FIRM SIZE DAN PROFITABILITAS TERHADAP ISLAMIC SOCIAL REPORTING (ISR) DENGAN EARNING GROWTH SEBAGAI VARIABEL MODERATING PADA JAKARTA ISLAMIC INDEX (JII)

1970 ◽  
Vol 18 (1) ◽  
pp. 137-150
Author(s):  
Titin Hartini
Keyword(s):  
Regression Analysis ◽  
Data Analysis ◽  
Firm Size ◽  
Sampling Technique ◽  
Social Reporting ◽  
Analysis Method ◽  
Earning Growth ◽  
Independent Variables ◽  
Dependent Variables ◽  
The Relationship

This study aims to determine and analyze the effect of Firm Size and Profitability on Islamic Social Reporting, and see whether Earning Growth can strengthen or weaken the relationship between independent variables to the dependent variable. This research takes object in companies registered in Jakarta Islamic Index (JII) for period 2011-2015, amounted to 30 companies and obtained by 12 companies by using purposive sampling technique. Data analysis method used is multiple regression analysis. Based on the results of simultaneous research all the variables berpegaruh against Islamic Social Reporting, but partially, only Firm Size that affect the Islamic Social Reporting. In addition, Earning Growth can not strengthen or weaken the relationship between independent variables and dependent variables.

scholarly journals Regresi Median Pada Copula Bivariat

2019 ◽  
Vol 3 (1) ◽  
pp. 07
Author(s):  
Geraldus Anggoro Rinadi ◽  
Leopoldus Ricky Sasongko ◽  
Bambang Susanto
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Median Regression ◽  
Independent Variables ◽  
Bivariate Data ◽  
Dependent Variables ◽  
Frank Copula ◽  
The Relationship

Abstrak: Analisis regresi adalah analisis yang sering digunakan dalam segala bidang yang bertujuan untuk memodelkan hubungan antara dua jenis variabel tak bebas dengan satu atau variabel bebas. Regresi linier masih memiliki beberapa kekurangan, maka dari untuk mengatasinya dengan regresi median. Copula dapat digunakan untuk mendeteksi hubungan data bivariat dengan peubah-peubah yang berbeda. Hasil penelitian menunjukkan kurva kuantil bersyarat terbaik berdasarkan MSE terkecil Data I yaitu copula Plackett sebesar 0.8650. Sedangkan nilai MSE terkecil Data II yaitu copula Gaussian sebesar 0.3954. Nilai MSE terkecil Data III yaitu copula Frank sebesar 0.5575. Terakhir, nilai MSE terkecil Data IV yaitu copula Clayton sebesar 0.3190.Abstract:  Regression analysis is an analysis that is often used in all fields which aims to model the relationship between two types of non-dependent variables with one or independent variables. Linear regression still has several drawbacks, so to overcome this by median regression. Copula can be used to detect bivariate data relations with different variables. The results showed that the best conditional curves based on the smallest MSE of Data I were Plackett copula of 0.8650. While the smallest MSE value is Data II, which is a Gaussian population of 0.3954. The smallest MSE value of Data III is Frank copula of 0.5575. Finally, the smallest MSE value is Data IV which is copula Clayton of 0.3190.

scholarly journals Thai Silk Product Industry Development In The Northeastern Region Of Thailand

2011 ◽  
Vol 8 (10) ◽  
Author(s):  
Nak Gulid ◽  
Sirivan Serirat ◽  
Suphada Sirikudta ◽  
Udom Sayaphan ◽  
Aurathai Lertwannawit ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Quantitative Analysis ◽  
Brand Personality ◽  
Purchasing Behavior ◽  
Silk Industry ◽  
Independent Variables ◽  
Northeastern Region ◽  
Dependent Variables ◽  
The Relationship ◽  
Product Industry

This research aims to study the relationship between independent variables (value, motivation, brand personality, attitude toward product and demographic factor) and dependent variables (purchasing behavior and trend to buy in the future) of Thai silk industry in Northeastern region, Thailand. Quantitative analysis is allowed in this study. This research includes 400 customers who buy Thai silk in two provinces (Roi-Et and Khon-Khen) in the Northeastern region in Thailand. Multiple regression analysis was employed in this study. The result shows that motivation and value are strong influenced on purchasing behavior and trend to buy product in both provinces. However, brand personality and attitude toward product are partially supported our expectations.

scholarly journals Analysis of Relationship Between Personality and Favorite Places with Poisson Regression Analysis

2018 ◽  
Vol 16 ◽  
pp. 02001 ◽  
Author(s):  
Ha Yoon Song ◽  
Hwa Baek Kang
Keyword(s):  
Regression Analysis ◽  
Poisson Regression ◽  
Human Mobility ◽  
High Tendency ◽  
Independent Variables ◽  
Location Data ◽  
Dependent Variables ◽  
Independent Variable ◽  
The Relationship ◽  
University Laboratory

A relationship between human personality and preferred locations have been a long conjecture for human mobility research. In this paper, we analyzed the relationship between personality and visiting place with Poisson Regression. Poisson Regression can analyze correlation between countable dependent variable and independent variable. For this analysis, 33 volunteers provided their personality data and 49 location categories data are used. Raw location data is preprocessed to be normalized into rates of visit and outlier data is prunned. For the regression analysis, independent variables are personality data and dependent variables are preprocessed location data. Several meaningful results are found. For example, persons with high tendency of frequent visiting to university laboratory has personality with high conscientiousness and low openness. As well, other meaningful location categories are presented in this paper.

To Lag or Not to Lag?: Re-Evaluating the Use of Lagged Dependent Variables in Regression Analysis

2017 ◽  
Vol 6 (2) ◽  
pp. 393-411 ◽  
Author(s):  
Arjun S. Wilkins
Keyword(s):  
Regression Analysis ◽  
Parameter Estimates ◽  
Coefficient Estimates ◽  
Estimation Strategy ◽  
Independent Variables ◽  
Robust Estimates ◽  
Wide Range ◽  
Dependent Variables ◽  
Data Generating Process ◽  
Parameter Values

Lagged dependent variables (LDVs) have been used in regression analysis to provide robust estimates of the effects of independent variables, but some research argues that using LDVs in regressions produces negatively biased coefficient estimates, even if the LDV is part of the data-generating process. I demonstrate that these concerns are easily resolved by specifying a regression model that accounts for autocorrelation in the error term. This actually implies that more LDV and lagged independent variables should be included in the specification, not fewer. Including the additional lags yields more accurate parameter estimates, which I demonstrate using the same data-generating process scholars had previously used to argue against including LDVs. I use Monte Carlo simulations to show that this specification returns much more accurate coefficient estimates for independent variables (across a wide range of parameter values) than alternatives considered in earlier research. The simulation results also indicate that improper exclusion of LDVs can lead to severe bias in coefficient estimates. While no panacea, scholars should continue to confidently include LDVs as part of a robust estimation strategy.

scholarly journals Categorical Variables in Regression Analysis: A Comparison of Dummy and Effect Coding

2012 ◽  
Vol 4 (2) ◽  
pp. 202 ◽  
Author(s):  
Hussain Alkharusi
Keyword(s):  
Regression Analysis ◽  
Group Membership ◽  
Regression Coefficients ◽  
Categorical Variables ◽  
Sample Sizes ◽  
Independent Variables ◽  
Coding Method ◽  
Dependent Variables

The use of categorical variables in regression involves the application of coding methods. The purpose of this paper is to describe how categorical independent variables can be incorporated into regression by virtue of two coding methods: dummy and effect coding. The paper discusses the uses, interpretations, and underlying assumptions of each method. In general, overall results of the regression are unaffected by the methods used for coding the categorical independent variables. In any of the methods, the analysis tests whether group membership is related to the dependent variables. Both methods yield identical R2 and F. However, the interpretations of the intercept and regression coefficients depend on what coding method has been applied and whether the groups have equal sample sizes.

scholarly journals Pengaruh Harga dan Promosi Terhadap Keputusan Pembelian Helm Merek GM Pada Mahasiswa/i Sekolah Tinggi Ilmu Ekonomi Haji Agus Salim Bukittinggi

2020 ◽  
Vol 1 (2) ◽  
pp. 42-52
Author(s):  
Hariman Syaleh ◽  
Rohimah Nur Nasution
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Secondary Data ◽  
Multiple Linear Regression Analysis ◽  
Purchasing Decisions ◽  
Independent Variables ◽  
Dependent Variables ◽  
Positive Effect

This research is motivated by many types and brands of helmets offered to consumers in the market. So that each helmet company must create a strategy to maintain and achieve a higher market share. The problem in this study is "How is the influence of price, quality and promotion of the decision to purchase GM brand helmets for STIE HAS Bukittinggi students. The data used are primary and secondary data. The research data was obtained through questionnaires to 68 respondents. The variables used were dependent variables, namely purchasing decision (Y) and independent variables namely price (X1), and promotion (X2). The method of analysis used by the writer in this research is multiple linear regression analysis. The results of multiple linear regression analysis obtained the following equation: Y = 15,070 + 0,222 X1 + 0.782 X2 obtained that prices and promotions have a positive effect on purchasing decisions. The results of the t test and f test are partially and simultaneously have a significant effect on purchasing decisions.

scholarly journals Approaches to Control Mechanisms and Their Implications for Companies ’ Profitability: a Study in UAE

2020 ◽  
Vol 4 (2) ◽  
pp. 11-20
Author(s):  
Essia Ries Ahmed ◽  
Tariq Tawfeeq Yousif Alabdullah ◽  
Muhammad Shabir Shaharudin
Keyword(s):  
Regression Analysis ◽  
Financial Sector ◽  
Listed Companies ◽  
Foreign Ownership ◽  
The Other ◽  
Control Mechanisms ◽  
Insider Ownership ◽  
Independent Variables ◽  
Dependent Variables

This study tries to evaluate and test the role of control mechanisms represented by foreign ownership and insider ownership on companies’ profitability in the listed companies in the UAE and whether independent variables are matter in determining the profitability of such companies. This study utilized companies belong to non-financial sector for the year of 2019 with a sample of 50 companies to be analyzed in the current study. To test the independent and dependent variables, regression analysis was used via using SPSS. The findings show that insider ownership has insignificant impact on companies’ profitability On the other hand, the findings revealed evidence to support the effect of foreign ownership on companies’ profitability. Moreover, there is insignificant evidence reflected the fact that companies’ size has insignificant impact on companies’ profitability. This study added further evidence in Dubai context where there is a rare and unique studies that have been done in this important context. It takes in tits account to investigate both insider and foreign ownership and their impact companies’ profitability

ADDENDUM

PEDIATRICS ◽  
1982 ◽  
Vol 69 (5) ◽  
pp. 562-562
Keyword(s):  
Psychometric Properties ◽  
Analysis Of Variance ◽  
Grade Level ◽  
Independent Variables ◽  
Dependent Variables

Copies of the ICTD test with results of each question by grade level are available from one of the authors (C.F.J.). All tables including those that indicate CCDA distribution by grade and sex; analysis of variance with ICDT scores as dependent variables and sex, grade, and CCDA as independent variables; analysis of variance with CDA scores as dependent variables; and discussion of the psychometric properties of ICDT are also available from one of the authors (M.A.).

Sign in / Sign up

Export Citation Format

Share Document