Explorations in statistics: regression

2011 ◽  
Vol 35 (4) ◽  
pp. 347-352 ◽  
Author(s):  
Douglas Curran-Everett
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Statistical Regression ◽  
Essential Component ◽  
The Relationship ◽  
Residual Plots

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This seventh installment of Explorations in Statistics explores regression, a technique that estimates the nature of the relationship between two things for which we may only surmise a mechanistic or predictive connection. Regression helps us answer three questions: does some variable Y depend on another variable X; if so, what is the nature of the relationship between Y and X; and for some value of X, what value of Y do we predict? Residual plots are an essential component of a thorough regression analysis: they help us decide if our statistical regression model of the relationship between Y and X is appropriate.

Revisiting the Relationship Between Marketing Education and Marketing Career Success

2017 ◽  
Vol 39 (2) ◽  
pp. 109-123 ◽  
Author(s):  
Donald R. Bacon
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Career Success ◽  
Academic Major ◽  
Marketing Education ◽  
Classic Article ◽  
Using Data ◽  
The Relationship

In a replication of a classic article by Hunt, Chonko, and Wood, regression analysis was conducted using data from a sample of 864 marketing professionals. In contrast to Hunt, Chonko, and Wood, an undergraduate degree in marketing was positively related to income in marketing jobs, but surprisingly, respondents with some nonmarketing majors earned about the same as marketing majors in marketing jobs. Satisfaction with a marketing career was not significantly related to academic major. The income regression model explained 30% of the variance in marketing income, which is an improvement over the earlier study, but also indicates that most of the variance in marketing success is not explained by education. Implications are discussed.

scholarly journals The role of financial awareness for viable and sustainable small-medium enterprises in Kwa-Zulu Natal, Durban

2021 ◽  
Author(s):  
◽  
Thabiso Sthembiso Msomi
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Financial Accounting ◽  
Access To Finance ◽  
Pearson’S Correlation ◽  
Absolute Value ◽  
Pearson's Correlation ◽  
R Value ◽  
Financial Awareness ◽  
The Relationship

The objective of this study is to examine financial awareness for viable and sustainable smallmedium-enterprises in Kwa-Zulu Natal, Durban. In this study, the researcher examined factors for SME sustainability and viability as they influence organisational survival. The specific objectives are outlined as follows: to examine the influence of financial awareness on SME viability and sustainability; to establish the relationship between financial accounting skills and sustainable SMEs; to establish the relationship between financial awareness and financial accounting skills; and to determine the Influences of budgeting and financial awareness on SME sustainability. The quantitative research method was adopted for this study and the purposive sampling technique was chosen to select the participants for this study. The study collected primary data from respondents who are owners of SMEs in the retail, construction, manufacturing sectors, etc. Data was analysed using SPSS. A total of 310 research questionnaires was administered and 304 research questionnaires were returned for analysis (giving a 98% response rate). A regression analysis and Pearson’s correlation analysis were conducted to address the specific objectives of the study. The study identified access to market, access to finance and financial accounting skills as the independent variables, while SME sustainability was the dependent variable of the regression model. The findings suggest that access to finance has the largest absolute value (0.425), which indicates that access to finance uniquely accounts for the larger proportion of the variance in the regression model. The outcome of Pearson’s correlation shows moderate correlation (r value is 0.531) between financial accounting skills and sustainable SMEs. Moreover, there was a weak correlation (r value is 0.457) between financial awareness and financial accounting skills. The outcome of the regression analysis suggests that budgeting has the largest absolute value (0.372), which indicates that budgeting uniquely accounts for the largest proportion of the variance in the regression analysis. The Exploratory Factor Analysis revealed nine factors that are significant to ensure sustainability and viability. The implication of the outcome is that access to finance and budgeting accounts for SME sustainability. Based on the findings from this research, it is recommended that SMEs owners should pay much attention to access to finance and budgeting in running their businesses. Again, employee performance reviews contribute to enhancing the financial accounting skills and knowledge of staff of SMEs as well. They should seek expert or professional advice before taking a loan and they should avoid loan sharks as the interest charged by loan sharks are very high which may lead to potential debt trap. It is suggested that Government agencies should help SMEs to market their products and keep their businesses viable.

scholarly journals The Effect of Phase on Paper Thickness Optimization in the Paper Recycling Process Using Recycling Machine

2020 ◽  
Vol 2 (1) ◽  
pp. 19
Author(s):  
Fauzhia Rahmasari
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Multiple Linear Regression Model ◽  
Thickness Optimization ◽  
Recycling Process ◽  
Paper Recycling ◽  
Independent Variables ◽  
The Relationship

AbstractEfforts to manage the recycling of paper waste into new paper have been carried out in recent times. It takes a tool or machine that is able to effectively and efficiently recycle used paper into new paper. There are several factors that affect the effectiveness of paper recycling machines, one of which is the paper thickness. One method that can be used to analyze the factors that influence paper thickness in the paper production process using a paper recycling machine is regression analysis. Regression analysis is data analysis techniques in statistics that is used to examine the relationship between several independent variables and dependent variable. However, if we want to examine the relationship or effect of two or more independent variables on a dependent variable, the regression model used is a multiple linear regression model. This study purposes are to analyze the factors that influence paper thickness using a paper recycling machine using multiple linear regression and to inform the modeling about that. The results showed that the factors that affect the paper thickness optimization are destruction and press phase. AbstractUpaya pengelolaan daur ulang sampah kertas menjadi kertas baru telah banyak dilakukan pada jaman sekarang. Dibutuhkan suatu alat atau mesin yang mampu secara efektif dan efisien dalam mendaur ulang kertas bekas menjadi kertas baru. Terdapat beberapa faktor yang mempengaruhi tingkat efektifitas mesin daur ulang kertas diantaranya adalah ketebalan kertas. Salah satu metode yang dapat digunakan untuk menganalisis faktor-faktor yang mempengaruhi ketebalan kertas pada proses produksi kertas menggunakan mesin daur ulang kertas adalah analisis regresi. Analisis regresi merupakan teknik analisis data dalam statistika yang digunakan untuk mengkaji hubungan antara beberapa variabel bebas dengan variabel tidak bebas. Namun, jika ingin mengkaji hubungan atau pengaruh dua atau lebih variabel bebas terhadap satu variabel tidak bebas, maka model regresi yang digunakan adalah model regresi linier berganda. Tujuan dalam penelitian ini yaitu menganalisis faktor-faktor yang mempengaruhi ketebalan kertas menggunakan mesin daur ulang kertas menggunakan regresi linier berganda serta memberikan informasi pemodelan mengenai hal tersebut. Hasil penelitian menunjukkan bahwa faktor yang mempengaruhi keoptimalan ketebalan kertas adalah fase penghancuran dan pemadatan kertas

scholarly journals The Application of Statistical Regression for Geographical Data Analysis

2004 ◽  
Vol 11 (2) ◽  
Author(s):  
P Priyono
Keyword(s):  
Regression Analysis ◽  
Data Analysis ◽  
Subject Matter ◽  
Causal Relation ◽  
Computer Software ◽  
Statistical Technique ◽  
Statistical Regression ◽  
Close Attention ◽  
Geographical Data ◽  
The Relationship

Application of regression statistic to analyse geography data is getting familiar, as the reason that geography object is really wide, kwantitative approach of geography and availibilty computer software of regression analysis which is getting complete and refresentative. The way of making decision and prediction constitutes the superiority of regression analysis and constitutes the issue which is often met by geographer in the study of geography object. It not only phenomena of human geography, but phisycal geography phenomena is also able to be approtached by regression analysis. For user the attentions that ought to be noticed are 1) regression statistic ought to be appraised as a fool and not as a brain, so that researcher is the main important operator; 2) mastery of geography subject matter constitutes an essential basis; 3) statistic is able to work if there is a detum which is able to fulfill the term of requirements and preceded by a logic causal relation; 4) close attention of reasearcher is highly required; 5) when must, researcher use the  statistic and the relationship between data type and statistical technique.

Regression Analysis

2018 ◽  
pp. 170-205
Author(s):  
Quan Li
Keyword(s):  
Economic Growth ◽  
Regression Analysis ◽  
Statistical Model ◽  
Regression Model ◽  
Ordinary Least Squares ◽  
Theory And Practice ◽  
Model Fit ◽  
Theoretical Argument ◽  
Markov Theorem ◽  
The Relationship

This chapter teaches how to use R to conduct regression analysis to answer the question: Does trade promote economic growth? It demonstrates how to specify a statistical model from a theoretical argument, prepare data, estimate and interpret the statistical model, and use the estimated results to make inferences and answer the question of interest. More specifically, it discusses the logic of regression analysis, the relationship between population and sample regression models, how to estimate a regression model in theory and practice, the estimation of sample regression model using OLS (ordinary least squares), the interpretation of estimation results, the statistical inference in regression analysis using hypothesis testing and confidence interval, the types of sum of squares and overall model fit, and how to report the model results. The validity of regression analysis is contingent upon the assumptions of the Gauss-Markov theorem being met.

scholarly journals Prospects for the creation and use of paired and multiple correlation and regression models in beekeeping

2021 ◽  
pp. 58-63
Author(s):  
O. Galatiuk ◽  
A. Lakhman ◽  
T. Romanishina ◽  
V. Behas
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Air Temperature ◽  
Economic Performance ◽  
Quality Data ◽  
Anthropogenic Factors ◽  
Multiple Correlation ◽  
Correlation And Regression Analysis ◽  
The Relationship ◽  
Natural And Anthropogenic Factors

In animal husbandry, including beekeeping, there are a growing number of independent consultancy services to analyse the performance of the industry in relation to disease monitoring status and preventive measures to maintain proper bee family health. In order to provide expert advice, these services must always be backed up by quality data and accurate statistical analysis. It would give clear instructions on how to interpret the results obtained when processing them, and show directions for improving disease prevention. Currently, there are problems related to improving the control of infectious diseases in bees, as various natural and anthropogenic factors have a multidirectional effect on the economic performance of beekeeping. There are also concerns about the control of infectious animal and insect diseases, which is a multifaceted series of causes due to natural and anthropogenic factors that have a polyvector effect on the economic performance of beekeeping. Therefore, the experimental application of different types of correlation and regression analysis in this industry by constructing pairwise and multivariate dependencies and their statistical interpretation was the aim of the paper. The correlation and regression model under study contains four sets of characteristics: result variable (y) - the amount of honey from 20 different apiaries in one season and factor variables: x1 - air temperature in the apiaries; x2 - amount of probiotic "Enteronormin Iodis + Se" to stimulate the immune system as one of the preventive methods; x3 - number of beehives in each apiary. Linear proportional relationships between apiary productivity and the factors included in the regression model are obtained. According to the results of the correlation-regression analysis, paired correlation coefficients showed that the relationship between air temperature in the apiary and produced honey is medium connection (r1 = 0,666), the relationship between the amount of probiotic applied per frame and produced honey is tight (close) connection (r2 = 0,813), the relationship between the number of beehives and produced honey is medium connection (r3 = 0,633). The regression coefficients show how the amount of honey produced in an apiary changes when each factor changes by one, with the other factors in the equation fixed. So, raising the temperature by 1 °C increases the honey production by 216 kg in each apiary, while increasing the concentration of "Enteronormin Iodis + Se" by 1 cm3 per beehive frame increases the nectar production by 1,12 kg for one hive. The coefficient of multiple determination (R2 = 0,954163) identifies a close relationship in the model created (95% of the factors investigated determine apiary performance). Therefore, modelling in the form of linear and multiple correlation and regression analysis is feasible in beekeeping. Key words: beekeeping, modeling, system analysis, factor and result characteristics.

scholarly journals REGRESSION ANALYSIS OF THE SEISMIC AND GEOPHYSICAL PARAMETERS AND ITS APPLICATION FOR SEISMICITY STUDY OF THE TRANSCARPATHIAN REGION

2020 ◽  
pp. 49-53
Author(s):  
M. Homyak ◽  
D. Malytskyy ◽  
О. Astashkina ◽  
M. Makhnitskyy ◽  
S. Kravets ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Statistical Model ◽  
Environmental Parameters ◽  
Observation Point ◽  
Statistical Regression ◽  
Earthquake Parameters ◽  
Geoacoustic Emission ◽  
Carpathian Region ◽  
Different Depths ◽  
The Relationship

The purpose of this work is to interpret the experimental data (deformation, geoacoustic and earthquake parameters) and to establish their relation with the seismicity of the Transcarpathian region using statistical (regression) analysis. The correlation of geophysical parameters is described, namely: deformation, geoacoustic emission and seismic characteristics of magnitude and energy class.For construction of the statistical (regression) model, geoacoustic and deformation data for the period of 2014, as well as data of the seismological catalog provided by the seismicity department of the Carpathian region (Subbotin Institute of Geophysics of NAS of Ukraine) were used. The statistical model of seismicity is built to analyze various geophysical parameters and to establish their relationship with each other by means of regression analysis.This interconnection will give an opportunity to understand how seismicity influences the change of various environmental parameters of the Transcarpathian region. The deformation and geoacoustic data used in the work were obtained at the mode geophysical station (MGS) "Beregove" and the observation point "Janoshi" (Transcarpathia). The basic regression analysis formulas used to construct a linear statistical model are given. According to the seismic catalog, a graph of dependence between energy class (K) and magnitude (MD) for the period 2002–2016 was constructed, which confirmed their dependence, as well as a histogram of seismic activity for the period 2002–2016, from which it follows that the largest number of events was in 2015. The tables, on which graphs of seismicity dependence on deformation and geoacoustics, are presented. The relationship between the magnitude (MI) and the offset shift (lg DP) in depth (h) is shown. Studies were conducted for different depths: 1) up to 2 km, 2) from 2–5 km, 3)5–10 km and 4) from 10 km or more. The results showed that the greater the depth, the greater the relationship between the magnitude (MI) and the offset shift (lg DP) is. Such studies are needed to identify the effect of seismicity on the change of other environmental parameters, in particular, temperature, characteristics of earthquake foci, which will allow building an existing model of seismicity of the Transcarpathian region.

Poor Acceptance of the Past is Related to Depressive Symptoms in Older Adults

GeroPsych ◽  
2020 ◽  
Vol 33 (4) ◽  
pp. 246-251
Author(s):  
Gozde Cetinkol ◽  
Gulbahar Bastug ◽  
E. Tugba Ozel Kizil
Keyword(s):  
Older Adults ◽  
Regression Analysis ◽  
Depressive Symptoms ◽  
Death Anxiety ◽  
Geriatric Depression ◽  
Ego Integrity ◽  
The Past ◽  
Depressed Group ◽  
Total Death ◽  
The Relationship

Abstract. Depression in older adults can be explained by Erikson’s theory on the conflict of ego integrity versus hopelessness. The study investigated the relationship between past acceptance, hopelessness, death anxiety, and depressive symptoms in 100 older (≥50 years) adults. The total Beck Hopelessness (BHS), Geriatric Depression (GDS), and Accepting the Past (ACPAST) subscale scores of the depressed group were higher, while the total Death Anxiety (DAS) and Reminiscing the Past (REM) subscale scores of both groups were similar. A regression analysis revealed that the BHS, DAS, and ACPAST predicted the GDS. Past acceptance seems to be important for ego integrity in older adults.

Using The Fully Modified M Method In Estimating The Effect Of Cultivated Area On Barley Production In Iraq For The Period 1970-2018

2020 ◽  
Vol 2020 (66) ◽  
pp. 101-110
Author(s):  
. Azhar Kadhim Jbarah ◽  
Prof Dr. Ahmed Shaker Mohammed
Keyword(s):  
Regression Model ◽  
Moving Average ◽  
Estimation Method ◽  
Estimation Methods ◽  
Autoregressive Moving Average ◽  
Moving Average Models ◽  
Error Terms ◽  
Relationship Of ◽  
The Relationship ◽  
Barley Crop

The research is concerned with estimating the effect of the cultivated area of barley crop on the production of that crop by estimating the regression model representing the relationship of these two variables. The results of the tests indicated that the time series of the response variable values is stationary and the series of values of the explanatory variable were nonstationary and that they were integrated of order one ( I(1) ), these tests also indicate that the random error terms are auto correlated and can be modeled according to the mixed autoregressive-moving average models ARMA(p,q), for these results we cannot use the classical estimation method to estimate our regression model, therefore, a fully modified M method was adopted, which is a robust estimation methods, The estimated results indicate a positive significant relation between the production of barley crop and cultivated area.

INTERAKSI BUDAYA ETIS DAN KECERDASAN SPIRITUAL PADA HUBUNGAN MUATAN ETIKA DAN PERILAKU ETIS MAHASISWA (Survey pada Pendidikan Vokasi Akuntansi di Yogyakarta)

Equity ◽  
2017 ◽  
Vol 20 (1) ◽  
pp. 1
Author(s):  
Rahmawati Hanny Y
Keyword(s):  
Regression Analysis ◽  
Data Analysis ◽  
Vocational Education ◽  
Ethical Behavior ◽  
Sampling Technique ◽  
Spiritual Intelligence ◽  
Ethical Culture ◽  
Research Use ◽  
Ethical Content ◽  
The Relationship

This study aims to analyze the interaction of ethical culture, spiritual intelligence, ethical content, and students' ethical behavior. The population in this study is a student at one of the leading accounting vocational education institutions in Yogyakarta. Sampling technique in this research use purposive sampling. The number of samples in this study was 368 respondents. Data analysis using Moderated Regression Analysis (MRA). The results of this study indicate that the content of ethics affect the student's ethical behavior. The interaction of ethical culture on the relationship between ethical content and ethical behavior suggests it can strengthen its influence. Similarly, the interplay of spiritual intelligence that demonstrates can strengthen the relationship between ethical content and student ethical behavior.

Sign in / Sign up

Export Citation Format

Share Document