In this work, multiple regression analysis was carried out via experiments and data analysis to attain the optimal reacting conditions of the KMnO4-H2SO4-Na2SO3 chemiluminescence system for acrylamide concentration detection through static injection analysis, i.e. KMnO4:3.8×10-4 mol/L; Na2SO3:1.8×10-3 mol/L; H2SO4:3.6×10-2 mol/L. In addition, the correlation and the linear regression equation of acrylamide concentration and relative luminous intensity were obtained under the optimal...
Topics: Multiple Regression Analysis, Static Injection Analysis, Acrylamide, Chemiluminescence
This study examines the determinants of savings among members of cooperative societies in Anambra state. Specifically, it provides empirical evidence on the socio-economic characteristics of members of the co-operatives and ascertains which of the socio-economic characteristics significantly determine savings mobilization among members of the cooperative groups. It also ascertained the range of savings of the members of the cooperative groups and identified the cooperative members' reasons for...
Topics: Savings, Cooperative Societies, Regressions, Multiple Regression Analysis, Loans
64
64
Mar 5, 2021
03/21
by
@ impact
texts
eye 64
favorite 0
comment 0
The intention of this paper is to study the impact of macroeconomic factors on BSE Banked. The study period covers ten years, from 2010 to 2019. For the purpose of the study, predominant macroeconomic factors have been selected based on the literature review.
Topics: BSE Banked, Macroeconomic Factors, Correlation and Multiple Regression Analysis
From the best-fit lines corresponding to sets of families of conditional judgements, the constant stimulus family and the constant condition family, both defined for a same scale object, the coordinate values of the point of intersection of both lines (indifference point) are obtained. These values are studied in relation to the mean values of the single object judgments and the conditional object judgements. Estimations are made of the variation of these coordinate values when a stimulus is...
Topics: ERIC Archive, Evaluative Thinking, Multiple Regression Analysis, Responses, Stimuli
A linear relationship was found between judgements given by 160 subjects to 7 objects presented as single stimuli (alpha judgements) and judgements given to the same objects presented with a condition (gamma judgements). This relationship holds for alpha judgements and the gamma judgements that belong to a family of constant stimulus and varying conditions (CSF). The corresponding regression coefficient, operating as a multiplicator, estimates the contrast effect, i.e. it measures the degree in...
Topics: ERIC Archive, Evaluative Thinking, Multiple Regression Analysis, Responses, Stimuli
Grouping is a statistical procedure through which members of the same group are considered as a single unit of observation. There are various ways to assign group membership and various ways to assign values of variables to groups. There are methodological problems associated with grouping in general and with particular methods of grouping. This paper argues that a wide variety of complex analytical problems concerning inferences from grouped observations can be understood from the use of a few...
Topics: ERIC Archive, Multiple Regression Analysis, Research Methodology, Sampling, Statistical Bias
A basic requirement for job satisfaction among sewing line workers is a working environment that allows workers to perform their work at an optimal level in a comfortable environment. The working environment plays an essential role in workers job satisfaction and the impact of job satisfaction on productivity. A causal study was conducted to examine the impact of the working environment on job satisfaction and productivity of workers in the garment manufacturing industries. In this study, six...
Topics: Industrial Engineering, job satisfaction, working environment, productivity, multiple regression...
Hierarchial causal models are described as pictorial representations of multiple regression equations. These models are particularly helpful for three reasons: (1) the formulation of problems in a path analytic framework forces a degree of explicitness that is often not present in research reports that rely solely on regression; (2) they provide a powerful aid to the substantive interpretation of results; and (3) they aid in the interpretation of relationships between unmeasured variables....
Topics: ERIC Archive, Mathematical Models, Multiple Regression Analysis, Path Analysis, Research Methodology
In multiple regression analysis, where resulting predictive equation effectiveness is subject to shrinkage, it is especially important to evaluate result replicability. Double cross-validation is an empirical method by which an estimate of invariance or stability can be obtained from research data. A procedure for double cross-validation is discussed, using heuristic and actual research data to illustrate a non-generalizable outcome and a generalizable outcome. The procedure involves the use of...
Topics: ERIC Archive, Equations (Mathematics), Estimation (Mathematics), Heuristics, Mathematical Models,...
The inferences allowable with a significant F in regression analysis are discussed. Included in this discussion are the effects of specificity of the research hypothesis, incorporation of covariates, directional hypotheses, and the manipulation of variables on the interpretation of significance for such purposes as causal and directional inferences. The position is taken that the research hypothesis dictates the variables to be tested and hence included in the regression models. If the...
Topics: ERIC Archive, Analysis of Variance, Hypothesis Testing, Multiple Regression Analysis, Statistical...
640
640
Jul 23, 2012
07/12
by
S.M.A.Khaleelur Rahman, M.Mohamed Sathik, K.Senthamarai Kannan
texts
eye 640
favorite 0
comment 0
Identifying anomalous values in the real-world database is important both for improving the quality of original data and for reducing the impact of anomalous values in the process of knowledge discovery in databases. Such anomalous values give useful information to the data analyst in discovering useful patterns. Through isolation, these data may be separated and analyzed. The analysis of outliers and influential points is an important step of the regression diagnostics. In this paper, our aim...
Topics: Cut-value, Cookâs D, DFFITS, multiple regression analysis, outlier detection, ijorcs,...
Variable selection techniques in stepwise regression analysis are discussed. In stepwise regression, variables are added or deleted from a model in sequence to produce a final "good" or "best" predictive model. Stepwise computer programs are discussed and four different variable selection strategies are described. These strategies include the forward method, backward method, forward stepwise method, and backward stepwise method. General and specific criticisms of the...
Topics: ERIC Archive, Comparative Analysis, Computer Software, Decision Making, Methods Research, Multiple...
The purpose of this paper is to examine the validity of regression estimates when skewed dichotomous scales are used as independent variables. When Pearson product-moment correlations are used to measure zero-order associations involving dichotomous variables, the resulting coefficients underestimate the true associations. As a result, using product-moment correlations involving dichotomous variables in regression equations apparently yields biased partial regression estimates. The analysis...
Topics: ERIC Archive, Correlation, Estimation (Mathematics), Matrices, Multiple Regression Analysis,...
Aggregation, or grouping, is a statistical procedure through which all members of a study within a specified range of scores (usually observed scores) are assigned a common or "group" score (for example, the group mean). The various social science methodology literatures agree on the costs of grouping: not only does one always lose information in grouping, in a wide variety of situations grouping introduces systematic error (bias). For most educational research applications the...
Topics: ERIC Archive, Error Patterns, Multiple Regression Analysis, Research Methodology, Statistical Bias,...
A basic approach to the problem of evaluating or predicting a crew's performance for the VT community is presented. The method uses an application of multiple regression analysis techniques to a model which has training parameters as its variables. The results would allow the squadron or wing commanding officer to predict a crew's performance before the actual flight and to determine how to allocate training time for the squadron.
Topics: crew performance, prediction of ASW crew performance, multiple regression analysis, VP training...
Several statistical techniques that can be used to ameliorate the difficulties inherent in the data analysis of longitudinal studies are presented. The first step in longitudinal data analysis is graphing. This permits visual inspection of the data, and with educated viewing can yield insights into the nature of the underlying mechanisms. The next level of sophistication is to apply regression analysis and change point analysis to the curves obtained from the graphical analysis. It is usually...
Topics: ERIC Archive, Data Analysis, Factor Analysis, Graphs, Longitudinal Studies, Multiple Regression...
Artificial neural networks (ANN) and multiple regression analysis (MRA) were used to predict the rheological properties of oil well cement slurries. The slurries were prepared using class G oil well cement with a water-cement mass ratio (w/c) of 0.44, and incorporating a new generation polycarboxylate-based high-range water reducing admixture (PCH), polycarboxlate-based mid-range water reducing admixture (PCM), and lignosulphonate-based mid-range water reducing admixture (LSM). The rheological...
Topics: Cement slurry, Oil well, Yield stress, Plastic viscosity, Artificial neural network, Multiple...
Virtually all parametric statistical procedures have been shown to be special cases of canonical correlation analysis, which is a useful research methodology particularly when augmented by the calculation of canonical structure, index, and invariance coefficients. A logic for conducting stepwise canonical correlation analysis based upon evaluation of canonical communality coefficients is presented. The coefficients indicate how much of a variable's variance is reproducible from the canonical...
Topics: ERIC Archive, Correlation, Multiple Regression Analysis, Multivariate Analysis, Predictor...
The intention of this paper is to provide an overall reference on how a researcher can apply multiple linear regression in order to utilize the advantages that it has to offer. The advantages and some concerns expressed about the technique are examined. A number of practical ways by which researchers can deal with such concerns as correlation/causation, upward bias R-squared, and multicollinearity are discussed. (MS)
Topics: ERIC Archive, Multiple Regression Analysis, Research Methodology, Research Tools, Social Sciences,...
This description of the technical details required for using the HIER-GRP computer program, which was developed to group or cluster regression equations in an iterative manner so as to minimize the overall loss of predictive efficiency at each iteration, contains a discussion of the basic algorithm, an outline of the essential steps, specifications of the computer system requirements, descriptions of necessary control cards, and explanations of the program output. Appendices include the...
Topics: ERIC Archive, Algorithms, Cluster Analysis, Computer Programs, Multiple Regression Analysis,...
The important and sometimes difficult-to-grasp concept of regression suppressor variable effects is explored. An inquiry into the phenomenon of suppressor effects is accomplished via a synthesis of the existing literature and the use of a small heuristic data set to improve the accessibility of the concept. Implications for researchers are also forwarded and it is suggested that the search for suppressor variables in an effort to remove unwanted predictor variable variance may prove less...
Topics: ERIC Archive, Heuristics, Multiple Regression Analysis, Predictive Measurement, Predictor...
Interpretation of emergent variables on the basis of structure coefficients (zero order correlations between original and emergent variables) is potentially very misleading and should be avoided in favor of interpretation on the basis of scoring coefficients. This is most apparent in multiple regression analysis and its special case, two-group discriminant analysis. Six examples of real and hypothetical data illustrate the pitfalls in interpretation based on structure coefficients. Much of the...
Topics: ERIC Archive, Correlation, Discriminant Analysis, Mathematical Models, Multiple Regression...
Statistics such as chi-square, phi, and Cramer's V are related to the R squared statistic of regression analysis. It is shown that the proportion of variance accounted for can be computed from many contingency table situations. (JKS)
Topics: ERIC Archive, Expectancy Tables, Hypothesis Testing, Multiple Regression Analysis, Nonparametric...
This paper explains in user-friendly terms why multivariate statistics are so important in educational research. The basic logic of canonical correlation analysis is presented as a simple or bivariate Pearson "r" procedure. It is noted that all statistical tests implicitly involve the calculation of least squares weights, and that all parametric tests can be conducted using canonical analysis, since canonical analysis subsumes parametric methods as special cases. Canonical analysis is...
Topics: ERIC Archive, Educational Research, Heuristics, Least Squares Statistics, Multiple Regression...
Although partial correlation is a correlation of residuals, the correlation of the true-score components of these residuals is not equivalent to the partial correlation of the true scores themselves. The source of this discrepancy is explained and its implications are briefly discussed. (Author)
Topics: ERIC Archive, Correlation, Multiple Regression Analysis, Statistical Analysis, True Scores,...
The Automatic Interaction Detector (AID) is discussed as to its usefulness in multiple regression analysis. The algorithm of AID-4 is a reversal of the model building process; it starts with the ultimate restricted model, namely, the whole group as a unit. By a unique splitting process maximizing the between sum of squares for the categories of each variable while minimizing the error sum of squares (within group sum of squares), AID-4 seeks out that variable which has the largest between sum...
Topics: ERIC Archive, Branching, Correlation, Mathematical Models, Multiple Regression Analysis, Predictor...
The extent to which standardized regression coefficients (beta values) can be used to determine the importance of a variable in an equation was explored. The beta value and the part correlation coefficient--also called the semi-partial correlation coefficient and reported in squared form as the incremental "r squared"--were compared for variables in 2,341 two-predictor equations and 8,670 three-predictor equations to examine the information they provided for evaluating variable...
Topics: ERIC Archive, Comparative Analysis, Correlation, Equations (Mathematics), Mathematical Models,...
Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested in explaining the most variability in the dependent variable with the fewest possible predictors, perhaps as part of a cost analysis. Two...
Topics: ERIC Archive, Multiple Regression Analysis, Predictor Variables, Regression (Statistics),...
This study predicts gymnastic performance, arousal, and anxiety measures from past performances. Pulse rate and the Palmar Sweat Index were utilized as indicants of arousal. Anxiety was assessed by means of the State-Trait Anxiety Inventory. Eighteen members of the Ithaca College women's varsity gymnastic team were tested throughout the 1973-74 competitive season. Regression analysis revealed that past performance loaded most heavily in the prediction equation. Arousal and anxiety measures were...
Topics: ERIC Archive, Anxiety, Arousal Patterns, Gymnastics, Higher Education, Multiple Regression...
The purpose of this study was to explore the use of robust variance estimation for combining commonly specified multiple regression models and for combining sample-dependent focal slope estimates from diversely specified models. The proposed estimator obviates traditionally required information about the covariance structure of the dependent effect size estimates, making it a potentially flexible method for conducing meta-analyses of regression estimates. A series of Monte Carlo simulations...
Topics: ERIC Archive, Robustness (Statistics), Multiple Regression Analysis, Meta Analysis, Effect Size,...
Fixed-width confidence intervals for a population regression line over a finite interval of x have recently been derived by Gafarian. The method is extended to provide fixed-width confidence intervals for the difference between two population regression lines, resulting in a simple procedure analogous to the Johnson-Neyman technique. (Author)
Topics: ERIC Archive, Analysis of Covariance, Mathematical Applications, Mathematical Models, Multiple...
The behavior of two real-time computer simulation models of melody recognition was compared with the performance of human subjects in this study. One of the models, INT1, recognized melodies by comparing specific intervals with stored intervals. The other model, CONT1, performed by comparing the contour of the stimulus melody with an array of melody intervals. The 20 intermediate and advanced psychology majors who volunteered to participate in the study were tested on the speed and accuracy of...
Topics: ERIC Archive, Computer Simulation, Higher Education, Melody, Models, Multiple Regression Analysis,...
77
77
Mar 5, 2021
03/21
by
@ impact
texts
eye 77
favorite 0
comment 0
The core purpose of this study is to analyse the impact of macroeconomic factors and stock returns of big companies, mid cap companies and small companies listed in national stock exchange in India. The study period covers ten years from 2010 to 2019. For the purpose of the study, predominant macroeconomic factors have been selected based on the literature review.
Topics: Macroeconomic Factors, National Stock Exchange, Portfolios, Big Companies, Mid Cap Companies, Small...
The study deals with the job component method of establishing compensation rates. The basic job analysis questionnaire used in the study was the Position Analysis Questionnaire (PAQ) (Form B). On the basis of a principal components analysis of PAQ data for a large sample (2,688) of jobs, a number of principal components (job dimensions) were identified. Scores on these dimensions, and the ratings on the original individual elements of the PAQ, were used in a multiple regression procedure for...
Topics: ERIC Archive, Job Analysis, Multiple Regression Analysis, Predictive Validity, Questionnaires,...
An investigation of the effects of randomly missing data in two-predictor regression analyses is described. The differences in the effectiveness of five common treatments of missing data on estimates of R-squared values and each of the two standardized regression weights is also investigated. Bootstrap sample sizes of 50, 100, and 200 were drawn from three sets of actual field data. Randomly missing data were created within each sample, and the parameter estimates were compared with those...
Topics: ERIC Archive, Comparative Analysis, Computer Simulation, Estimation (Mathematics), Mathematical...
Replicating the work of others who hypothesized that status inconsistancy increases political liberalism, this study involved a random sample of rural Michigan population. Utilizing multiple regression analysis, respondents were scored on the variables of occupation, income, education, religion, and political party preference. Hypotheses tested were: (1) political liberalism is inversely related to achieved socioeconomic status; (2) controlling for additive effects of achieved statuses on...
Topics: ERIC Archive, Correlation, Education, Hypothesis Testing, Income, Multiple Regression Analysis,...
Self-direction in learning is a major topic in the field of adult learning. There has been extensive coverage of the topic by theorists, researchers, and practitioners. However, there have been few studies which look at learner self-direction specifically as a personality trait. The present study addresses the relationship between learner self-direction and other personality traits of college students when the traits represented by the five-factor model of personality (Digman, 1990) are...
Topics: ERIC Archive, Personality Traits, Undergraduate Students, Independent Study, Correlation, Multiple...
A relatively new area of psychological investigation is the identification of biographical and psychological variables which contribute to an individual's decision to move from or to stay in a geographical area. This study is an attempt to utilize biographical and psychological data on 50 college students in a multiple linear regression to predict a newly defined Mobility Index, which was derived from having subjects place themselves into groups according to mobility plans. Using the multiple...
Topics: ERIC Archive, Biographical Inventories, Mobility, Multiple Regression Analysis, Prediction,...
Evaluations in education often throw away important information because of a penchant for averages. Multiple regression techniques are used to estimate the average effect of policies across schools, and usually school performance is represented by the average score of its students on an achievement test. The author suggests some ways of broadening educational evaluations: (1) to consider "outliers," or exceptional performers among schools; and especially, (2) to consider other...
Topics: ERIC Archive, Academic Achievement, Educational Assessment, Evaluation Methods, Multiple Regression...
A review of cross-validation shrinkage formulas is presented which focuses on the theoretical and practical problems in the use of various formulas. Practical guidelines for use of both formulas and empirical cross-validation are provided. A comparison of results using these formulas in a range of situations is then presented. The result of these comparisons indicate that one should use Cattin's formula to estimate cross-validated R, employing either Wherry or Olkin-Pratt estimates of the...
Topics: ERIC Archive, Correlation, Estimation (Mathematics), Mathematical Formulas, Mathematical Models,...
The study deals with learning styles and ways of thinking in facilitating effective teaching. The objective of this study was to investigate the relationship between students' learning style and ways of thinking toward effective teaching. This study was conducted by using correlational design. The population of the study were 360 university students of English education academic year 2015/2016 in State University of Medan. The samples were 82 university students selected by using random...
Topics: ERIC Archive, Cognitive Style, College Students, Correlation, Teacher Effectiveness, Foreign...
The purpose of this study was to investigate the relationship between the Texas Higher Education Assessment (THEA) scores and the Graduation rate of college students attending a Historically Black College or University (HBCU). Using a Regressional analysis that tested the predictability of the Reading, Writing, and Mathematics scores on the THEA to the Graduation rates 4 and 5 years later, it was found that none of these scores were strong predictors of graduation (strongest standardized beta...
Topics: ERIC Archive, Higher Education, Scores, Predictor Variables, Graduation Rate, Black Colleges,...
This paper contains information concerning the following: 1. An overview of multivariate analysis of variance, and discriminant (DA) and canonical (CA) analyses. 2. An introduction to specification and measurement errors, and collinearity. 3. The sparsity of information concerning specification and measurement errors and collinearity as they pertain to DA and CA. 4. Selected suggestions regarding how to deal with specification and measurement errors and collinearity as they pertain to DA and CA.
Topics: ERIC Archive, Multivariate Analysis, Multiple Regression Analysis, Discriminant Analysis, Error of...
The U.S. military has faced imposing force structure reductions during the last decade. Complementing the force structure reductions, four rounds of Base Realignment and Closure (BRAC) have been authorized to reduce surplus infrastructure. However, as the BRAC process unfolds, environmental cost issues are being placed under ever increasing scrutiny. Military environmental restoration costs have risen sharply (and above expectations) in recent years, with the unanticipated cost growth occurring...
Topics: Base Realignment and Closure (BRAC), Environmental Restoration, Naval Facilities Engineering...
Three simplifying conditions are given for obtaining least squares (LS) estimates for a nonlinear submodel of a linear model. If these are satisfied, and if the subset of nonlinear parameters may be LS fit to the corresponding LS estimates of the linear model, then one attains the desired LS estimates for the entire submodel. Two illustrative analyses employing this method are given, each involving an Eckart-Young (LS) decomposition of a matrix of linear LS estimates. In each case the factors...
Topics: ERIC Archive, Analysis of Variance, Least Squares Statistics, Mathematical Models, Mathematics,...
The parental satisfaction levels of a probability sample of 197 black mothers in the United States were examined. Three-fourths of the mothers described their relationships with their children as "very satisfying." Bivariate analysis showed that satisfaction did not vary significantly by marital status or family-household structure. Multiple regression analysis, however, indicated that mothers with the marital status of "separated" and those without husbands who resided with...
Topics: ERIC Archive, Black Mothers, Family Structure, Income, Marital Status, Multiple Regression...
The optimum weighting of variables to predict a dependent-criterion variable is an important problem in nearly all of the social and natural sciences. Although the predominant method, multiple regression analysis (MR), yields optimum weights for the sample at hand, these weights are not generally optimum in the population from which the sample was drawn. A method was developed that sacrifices some "prediction" in the sample at hand in order to achieve a more reliable and stable...
Topics: ERIC Archive, Correlation, Error Patterns, Factor Analysis, Matrices, Multiple Regression Analysis,...
This annual report presents data on bond elections and bond sales for financing the construction of public elementary and secondary school facilities. Data, summarized by state, are presented in tables and charts containing information on the number and dollar value of bond issues voted on and passed, and the number, dollar value, and net interest cost of bonds sold. In 1975 approval of public school bond issues averaged 46.0 percent of the dollar value and 46.3 percent of the number of issues...
Topics: ERIC Archive, Bond Issues, Educational Finance, Elections, Elementary Secondary Education, Interest...
Eight pigeons were trained in a concurrent-chains procedure in which the terminal-link immediacy ratio followed an ascending or descending series. Across sessions, one terminal-link delay changed from 2 s to 32 s to 2 s or from 32 s to 2 s to 32 s, while the other was always 8 s. For all pigeons, response allocation tracked changes in delay and was biased towards the 8-s alternative on the descending series, indicating a hysteresis effect, and was more sensitive to changes in the terminal-link...
Topics: ERIC Archive, Prediction, Models, Experiments, Reinforcement, Equations (Mathematics), Intervals,...
The stepwise regression method of selecting predictors for computer assisted multiple regression analysis was compared with forward, backward, and best subsets regression, using 16 data sets. The results indicated the stepwise method was preferred because of its practical nature, when the models chosen by different selection methods were similar in number of variables, variables included, and amount of variance explained. The best subset method worked very well for these data sets, and was...
Topics: ERIC Archive, Comparative Analysis, Computer Simulation, Mathematical Models, Multiple Regression...
