Regression analysis

DATA COLLECTION AND ANALYSIS Data Collection This study uses a unique dataset, which is a subset of the data that has been used by Bhansali and Zhu [12]. The dataset includes estimated IT expenditure of 329 large companies for 2005. The data was collected by phone interviews using a questionnaire designed by the research team. The questionnaire was distributed to the participants before interviews. The data was collected from approximately 600 firms; since some of these organizations are…

Multicollinearity Multicollinearity is one of the common problems in spatial regression analysis. Sometimes some or all of the explanatory variable are highly correlated in the sample data, which means that it is difficult to tell which of them is influencing the dependent variable (Barrow, 2009, p. 306). Hence, to check whether the independent variables are correlated with each other, a correlation matrix for the three indicators was measured using excel. The correlation matrix in table 2…

Using the figures in the table above, the following regression equation was obtained. Y = 0.668 + (-0.016) X1 + (0.185) X2 + (0.224) X3 + (0.118) X4 + (0.270) X5 Interpretation 1. A constant value of 0.668 indicates that if there is no independent variable (Reliability, Responsiveness, Assurance, Empathy, and Tangible), the dependent variable (customer satisfaction) is positive. 2. X1 regression coefficient = -0.016 means that if the service of dimensions X1 has decreased; the level of customer…

3.12: Data Analysis process Overall, the objective of the research analysis is to try to answer the research questions formulated in Chapter 1. Accordingly, a conceptual framework and propositions have been developed from these questions, and justified in the literature review section. Therefore, the data analysis will be pursued to gather evidence pertaining to the several concepts identified. Quantitative data from the questiormaire survey will be analyzed by utilizing the Statistical…

statistical significance of the variables and the regression equation indicating how it will impact your decision to open the pizza…

Total oil expenditure to Total food expenditure (R) .θ is the disturbance term, α is the intercept term and a, b, c, d, e and f are the corresponding coefficients of the independent variables. Based on the survey data obtained from 360 respondents a regression model is constructed. Ordinary Least Square Estimation technique is used to estimate the parameters. The overall significance of the model was tested using One way ANOVA (F test) which yielded an F value 49.190 and the exact probability…

Data For the purpose of this analysis, I choose to use the World Bank 2007 data to come up with a detailed conclusion. I used 32 different countries scattered throughout the world in my analysis, to provide an unbiased result. Three relevant variables were chosen to be analyzed and discussed later on in this section. These variables as mentioned earlier include foreign direct investments, agriculture and industry. The graph provided below is a summary statistic of the three variables in thirty…

their implementation. Regression Equation For the periods before the Lei Seca, most of the studies showed there was a positive trend in the number of accidents due to driver under the influence. Then, according to the program theory of change and logic model it is understood that the program is supposed to have an initial direct impact on the level of number of accidents due to drivers under the influence, as well as an impact on the slope of this trend. Thus, the regression equation for this…

As an entity that sells tickets to games, they need to forecast the demand for those tickets in order to help maximize their revenue potential. The chapter talks about regression analysis which the Orlando Magic uses, more specifically multiple regression analysis. The magic applied the multiple-regression model using several key variables that can affect ticket sales to forecast demand more accurately for games. Some of the independent variables the magic used in their forecasting model…

Evaluation Paper Description: This quantitative study uses a least-squares regression model to determine the predictive power of socio-economic factors on district-level student achievement on new, Common Core-aligned standardized assessments. We posit that educators may use our methodology and model to control for socio-economic factors, and more equitably compare school district performance. Purpose We used a least-squares regression model to determine the predictive power of socio-economic…