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Regression Essay Examples

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Purpose of project Over the years at Queen’s Royal College I have seen teachers having stern conversations with students for reaching to school late habitually. These students are faced with consequences such as: “in-house suspension” or community service for regular late coming. I myself have been a victim of these punishments. It is believed that…

Personal consumption expenditures price index

In their volume Consumer Demand in the United States: Analyses and Projection (Cambridge, Mass: Harvard University Press, 1970), p. 119, H. S. Houthakker and L. D Taylor presented the following results for their estimated demand equation for local bus service over the period from 1929 to 1961 (excluding the 1942 through 1945 war years) in…

Exploratory Data Analysis

Exploratory Data Analysis Using the dataset Chamorro-Premuzic. sav, exploratory statistical analysis was carried out on the variables in the dataset. Scatter plots were formulated t give a clear visual view of the data for Extroversion and Agreeableness. Descriptive statistics were also formulated for the variables. 2. Decision about the missing data 3. Correlation A correlation…

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Multicollinearity

One problem that can arise in multiple regression analysis is multicollinearity. Multicollinearity is when two or more of the independent variables of a multiple regression model are highly correlated. Technically, if two of the independent variables are correlated, we have collinearity; when three or more independent variables are correlated, we have multicollinearity. However, the two…

Ways to Overcome the Autocorrelation Problem

Several approaches to data analysis can be used when autocorrelation is present. One uses additional independent variables and another transforms the independent variable. •Addition of Independent Variables Often the reason autocorrelation occurs in regression analyses is that one or more important predictor variables have been left out of the analysis. For example, suppose a researcher…

Verifying the assumptions again

From the normal probability plot and the histogram, we observe that the normality assumption is till valid. We need to verify that the assumptions for regression analysis still hold, since we have removed some variables from our analysis. The residual plots all reveal that the residuals are normally distributed. See Appendix VIII. However, there still…

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