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Linear Regression and Regression Analysis

2 pages (500 words)

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... Regression and Regression Analysis Regression is a technique in statistics that enables estimation of the relation existing among variables. The technique seeks to estimate the strength of the relationship between one variable with another or a set of variables. However, when applying this technique, the statistician makes assumptions with regard to the variables and their relationship. Regression is based on the assumptions that there exists a linear relationship between the involved variables and that they have an additive relationship. There are many regression techniques one of them being linear regression. Linear regression refers to an approach that involves modeling the relationship that...

Multiple Regression

20 pages (5000 words)

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... Regression 0 General Purpose Multiple regression is simply an extension of linear regression, a statistical process which seeks to find the linear relationship between an independent variable and a dependent variable. In the case of multiple regression, the main purpose is to find the linear relationship between the dependent variable and a number of independent variables (Yan & Su, 2009). Multiple regression is one of the most widely used tools in statistical analysis because it is a very good reflection of real world situations. That is, a certain outcome is almost always affected by a number of predictors rather than just a single one (Dekking, 2005). Oftentimes, when a model is too simple that...

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Regression Analysis

4 pages (1000 words)

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... Analysis Assignment - 2 Table of Contents Introduction (Background) 3 Sampling Procedure 4 Scatterplot and Correlation Analysis 5
Regression Analysis 7
The GNP per Head and the Cars per Head 7
The GNP per Head and the Number of Commercial Vehicles 8
Conclusion 9
References: 11
Appendix: 12
Introduction (Background)
The data has been collected in 1986 about car ownership and car use in developing countries that contains figures about the population, the GNP per head, cars per head and the total of commercial vehicles.
In this paper, first, a (bivariate) sample of 30 countries from data collected in 1986 about car ownership and car use in developing countries will be drawn. Than the relationship betwee...

Regression Analysis

3 pages (750 words)

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... This paper is about analyzing the relationship between the benefits offered to an employee and his/her total, intrinsic and extrinsic job satisfaction. A study like this can help the management in retaining employees and in avoiding legal or ethical issues which could have surfaced if the employee is not satisfied with his job. Introduction In order to check the relationship between benefits and the intrinsic, extrinsic and total job satisfaction, 3 bivariate regressions are run. Using the regression equations the linear relationship between the independent variable (benefit) and the 3 sets of dependent variables (total job satisfaction, intrinsic job satisfaction and extrinsic job satisfaction) is...

Regression Paper

3 pages (750 words)

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... Paper Table Linear Regression Table on Annual Wage Indicators Mean Std. Deviation Correlation t Sig. Interpretation r2
.227a
Industry
.2300
.48938
-.008
-.325
.746
significant linear relationship
Occupation
2.5700
1.81606
.041
.978
.331
insignificant linear relationship
Southern Resident
.3300
.47258
-.081
-.802
.425
significant linear relationship
Nonwhite
.1000
.30151
-.122
-1.56
.122
significant linear relationship
Hispanic
.0600
.23868
.038
.034
.973
significant linear relationship
Marriage
.6700
.47258
.248
2.482
.015
insignificant linear relationship
Female
.4700
.50161
-.356
-4.07
.000
significant linear relationship
Union Member
.1800
.38612
.052
.035
.972
significant linear re...

Multiple Regression

6 pages (1500 words)
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... Investigating the determinants of property crime in the United s Introduction This report is an investigation of the determinants of property crimes in the United States. By property crimes, typically the references is to burglary, larceny, theft and motor vehicle theft. We seek to gain an understanding of what socio-economic characteristics of a particular state make it more susceptible to a larger number of property crimes. Data and methodology By using multiple regression analysis, the report is in pursuit of obtaining statistical evidence for or against commonly held beliefs regarding causality of various factors and crime. We use a State-wide data set that includes a record of property crimes...

Multiple regression

1 pages (250 words)

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... Analysis The following case study included framing a regression equation of Income on Age, education and working hours of the participants. Regression equation is the estimate of the relation between the dependant variable (criterion) with the independent variables (predictors). The independent variable chosen in our study was the Income while the independent variables were age, education and working hours of the participants. Hypothesis testing of the regression equation is based on the p value and the coefficient of determination R2. The null hypothesis will contend that there is no significant relation of the dependant variable with the independent variables if the p value of the framed...

Multiple regression

6 pages (1500 words)
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... Summary Multiple regression is an effective technique to identify a relationship between one dependent variable and multiple independent variables. It is hypothesized the property crime rates per thousand inhabitants is dependent on multiple factors such as per capita income, school dropout percentage, population density, percentage of people living in urban area and so on. In order to establish a certain relationship between the variables, multiple regression was used. While crimes is the dependent variable, other variables such as state, per capita income, dropouts, average precipitation, public aid recipients, population density, unemployment, percentage of people living in urban areas were...

Multiple Regression

2 pages (500 words)

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... Multiple Regression Below is the data that I have been collecting to There is a difference between simple regression and multiple regression. Simple regression analysis is used to establish the relationship between one variable and the other. One set of the variables is the dependent variable and the other set is the independent variable. The independent variable changes and in turn affects the dependent variable. Simple regression is used to establish whether or not indeed the independent variable determines the change that takes place in the dependent variable. It is also used to establish the way in which the two variables are related, such that on having one of the variables, it is possible to...

Regression Analysis

3 pages (750 words)

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... Regression analysis assumptions Regression analysis assumptions A summary of the assumptions used in the paper and justifications for using the same is briefly discussed. Assumption 1: Non-linearity assumption This assumption is pegged on the assumption there is no linear relationship between the studied variables. As a matter of fact, the use of this assumption is meant to abridge or rather offer basis for development of a hypothesis that the proposed relationship will fail to hold. It disputes the existence of a relationship between the proposed variables (Good & Hardin, 2009). In essence, it allows for evaluation of the fixed and random effects models in non-linear modeling frameworks and simply...

Multiple Regression

10 pages (2500 words)

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... Regression Multiple Regression is a tool which involves a single dependent variable and two or more independent variables. The general form of the multiple regression is Y= a +b1X1 +b2X2+b3X3...+bnXn + e which can be estimated by Y= a +b1X1 +b2X2+b3X3...+bnXn, where a is the intercept and bi's are the partial regression coefficients.
The various statistics associated with Multiple Regression are
Regression Coefficient: The estimated parameter of b
Standard Error of Estimate:
Is the standard deviation of the actual values of Y from the predicted values of Y
Standard Error
The standard deviation of b ie SE(b)
Coefficient of Multiple Determination: R2 which gives the % of the variance in the depen...

Regression analysis

2 pages (500 words)

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... Under what conditions would you use correlation and/or regression analysis Include comments on the type of data needed, the types of questions that these tools can answer, and a work-related suggestion for their use. Consider both linear and multiple correlation and regression.
Answer.
The multiple regression was used in the context of comparing and estimating the effects of two variables of which one is independent and the other dependent on first one. eg; The increase of population and the increase in demand of land and housing. In the prescribed case the increase of population is taken as independent and the demand which depends on it is taken as a dependent variable. The change in the dependent...

Regression Analysis

3 pages (750 words)

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... of unit Regression Analysis Table of content Introduction Assumption and Testing 5 Conclusion 5 Work Cited 6
Introduction
Regression analysis estimates the extent to which two or more variables are related. Evaluation of the statistical relationship between two variants is fundamental in highlighting how one variable affects the other within a statistical setup. In this work, the focus is to employ various aspects of regression and correlation analysis to be able to explore how imports and export ratios affect the GDP of the UAE.The GDP values will take the Y axis (Independent variable) while the other two variants, X1 and X2 will be used as the dependent variables. The data used in this analysis...

Econometric Regression Analysis

2 pages (500 words)

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... Regression Analysis Summary Rationally, literature reviews are related. The following article has summarized massive literature writtenon a certain topic, to give rationality to the difficulties, often dissimilar, expressions conveyed about a certain problem. The article can also serve as a helper for new ideas. Nevertheless, literature surveys often do not discover anything estimating agreed agreement. Ironically, this is simply as real for the methodical economic literature as it is for the writers and scholars of this article. For the completing of the dissonance to be fruitful, the authors have offered a quantitative method for studying the experiential economic literature (Muller 324)....

Statistics: Regression with MINITAB

11 pages (2750 words)

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... Alfalfa is one of the crops used to determine the good production of dairy cows. It is considered that the rent of the land planted toalfalfa is relative to the other agricultural purposes would be higher in the area with high density of dairy cows and lower in counties where liming is required. The basis of this can be proving by using the regression analysis, this study shows the relationship of the rent of land to the other factors, based on the data provided.
The Analysis of relationship between the fertilizer and the variety of corn in farm land will be analyzed by using one way ANOVA test. This will give us some factors of which is the best fertilizer to be used and the population means yield...

Linear Regression Exercises

5 pages (1250 words)

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... head: Linear Regression Exercise Linear Regression Analysis College: The total sample size was 378 2) The mean incomeis $1,485.49 and mean number of hours worked is 33.52 3) The correlation coefficient between the outcome and the predictor variables is 0.3.It is statistically significant at P< 0.001 because it falls between the range of 0-1.The association is positively correlated implying that it is directly proportional. For instance, when the number of hours worked increase so does the income. The correlation between the variables was moderate and positive, r = 0.3, If r is close to 0, it implies that there is less or no relationship between the variables (Bryman and Cramer, 1990). 4) The...

Regression Analysis Questions

1 pages (250 words)

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... Analysis Example of use of Regression Analysis, and three things to consider With nominal data, an analysis can only give insight into the data because of broad categorizations. However, to understand the intricacies that pertain to each category, for instance, the use of more robust methods of analysis is necessary, such as the regression analysis. For instance, regression analysis can establish what percentage of sales given other factors is necessary to attain a certain profit level. When making use of the regression analysis tool, the three key things worth consideration are the response variable, the explanatory variable, and the constant. The explanatory variable is the scale upon which the...

Discussion topic: Regression

1 pages (250 words)

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... Regression period Intelligence, defined as the ability of a human being to comprehend new situations or react to new and challenging scenarios by abstract thinking and application of learned knowledge to reason. Intelligence quotient (IQ) tends to be a measure of the intelligence of an individual (Boeree, 2003). It is a score arrived at after taking a set of standardized tests, and it acts as an indicator of academic prowess. People with scores under 70 are said to be mentally retarded while those with scores over 130 regarded as having a superior IQ (Boeree, 2003). The data provided on the IQ of the child and the mother is normally distributed with respect to descriptive statistics meaning that the ...

Interpretation of Regression Results

5 pages (1250 words)

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... Analysis of Regression Model In order to test the hypotheses, the multiple regression analysis has been conducted. The multiple regression analysis has not only highlighted the relationship between the dependent and independent variables but it has also explained the extent to which these variables are related to each other. Following are the details of the regression model and the interpretation of the results drawn from the regression analysis.
Regression Model
The regression model that has been used in this research study is as follows:
E = α + β1Temp + β2Humidity + β3Wind+ β4Dummy1 + + β5Dummy2 + Error term
Where,
E = Bundled Load
Variable 1 = Temperature = x1
Variable 2 = Humidity = x2
Vari...

Statistical Inference and Regression

10 pages (2500 words)

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... Statistical Inference and Regression Statistics is the study that involves collecting, organizing, analyzing, and interpreting data. Statistics deals with many aspects, which includes the planning of data collected that involves the designs of surveys and the experiments (Bethea & Boullion, 2005). Statistics can as well be considered as a mathematical body that pertains to the collecting, analyzing, interpretation, and presenting of data. Because of having empirical roots with the focus on applications, it is also considered as a distinct mathematical science but not just a branch of mathematics. Those who impress statistics tend to improve on the quality of data, the experimental designs, as well...

Multiple Regression Analysis

3 pages (750 words)

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... regression analysis: Factors affecting economic growth November 28, Multiple regression analysis: Factors affecting economic growth
Executive summary
Economic growth is one of the significant factors to governments’ responsibilities. Existing literature suggests that factors such as labor force, foreign direct investment, and foreign trade influence economic growth. This report investigated relationship between economic capacity (measured through gross domestic product) and the factors. Using data from the Central Intelligence Agency and Excel for data analysis, the report identifies positive effects of labor force and imports and negative effects of foreign direct investments inflow and export on e...

Regression Paper

8 pages (2000 words)

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... Estimation of Car Sale per Year in Marion County, Indiana This study is meant for the purpose of determiningand examining factors that contribute to the sale of cars a year long in Marion County. Here, a simple table will be proposed as an aid in examining and reporting the estimations of regression analyses. The key to the proposal is the determination of variables contributing to the sale of car in Marion County. The data used is retrieved from the year 2010-2013, for the purpose of a linear regression analysis. These variables include, but are not limited to, population (than to people moving into the county), and youth turning 18 years old and active population in Marion County. I retrieved my...

Regression analysis project

2 pages (500 words)

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... Project: Statistics Regression Analysis Project PROBLEM 2 Model Specification The model to be used in this test is Logistic regression with the following model:
P = kv
Where p is the probability that someone will be tested with prostate cancer, k is the coefficient of regression, and v is the most significant variable in determining the probability p. Outliers in this dataset include cancer, inv and cap since they have fixed and immeasurable quantities compared to the rest of the variables.
Transformation and important Variables
The necessary transformation in this regression process is the binomial transformation using “mylogit” function. The most important variable in this case is c.vol, because th...

Regression and Statistical Effects

5 pages (1250 words)

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... the Profitability of Long-Life s in a Noncontractual Setting: An Empirical Investigation and Implications for Marketing Summary The paper attempts to test the basic proposition of relationship marketing that the firm increases its bottom-line with long-term customer relationship as compare to short-term customer relationship. The author verifies four propositions:
There is a positive relationship between customer-firm relationship and profits of the firm.
Profits increase over time.
The cost of serving long-life customers is lower.
Long-life customers pay higher prices.
The author derives the customer lifetime for noncontractual relationship using the Negative Binomial Distribution (NBD)/ Pareto M...

Multi line regression

5 pages (1250 words)

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... Regression One field that has been of importance not only to researchers, but also the policy makers, business managers, medical professional engineers, marketing officers to mention but a few is statistics. Ideally, it entails using a large dataset to get meaning and to draw inferences and conclusion which later are used to make rational decisions, clear things out or expand human knowledge and understanding of underlying phenomenon (Osborne & Waters, 2002). In this case, how a country engages in international trade through imports and exports is one area that greatly depends on statistics in order to determine how well a country is doing in terms of trading with the relevant partners and in...

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