Using R, Linear Regression Analysis - 1354 Words

As a Data Analyst, I am responsible for assisting in projections and forecasting of enrollment as well as institutional research projects. This includes use of Excel and R to run statistical analyses in answering enrollment and research questions. Key to projecting enrollment is a file we use called the â€Å"Decision Model† We track various aspects of enrollment to help predict future enrollment. For example, we track the amount of third semester pathway students since they will likely be matriculating into the Online Degree Program. We also track the percentage of third semester students who have historically matriculated. This way we can apply the same percentage to the current rate of third semester Pathway students to estimate new online students. This same principle is applied all throughout the decision model, enrollment is broken out into categories of different students and indicators that can help predict that category. Regression analysis is used often to answer research questions. Using R, linear regression helps to shed light on the effects of any number of factors into college success. In addition, I have been able to use skills from excel courses on a regular basis to create charts and graphs as well as prepare and analyze spreadsheets. Finally, the principles of thinking like an economist often contribute to projects that I worked on. Mostly when I’ve needed to understand why students are behaving in a certain way or thinking about how to present data in the mostShow MoreRelatedRegression Between Male Height, Age And Weight Essay1376 Words   |  6 PagesRebecca Parada MATH 110-02 Professor Mink Regression between Male Height, Age and Weight Biostatistics is important to study as undergraduates delve deeper into their studies of Biology and learn how the study of life is integrated into more than just their college-level science courses. Looking into the use of statistics at a scientific level at this stage of our education is preparing determined and enthusiastic students for the world of medicine as one day we will have to read and analyze setsRead MoreBusiness Operational Forecasting : An Overview1080 Words   |  5 Pagesdepend on analyzing data using mathematical computation models (Makridakis, Wheelwright, Hyndman, 2008). However, this paper focuses on the quantitative forecasting techniques. Quantitative methods eliminate expertise elements out of analysis and instead use numerical facts and figures as well as well past experiences to forecast on future state. Quantitative forecasting techniques include; simple regression analysis, simple moving average, polynomial regression analysis among others. ComparingRead MoreRegression Analysis1447 Words   |  6 PagesREGRESSION ANALYSIS Correlation only indicates the degree and direction of relationship between two variables. It does not, necessarily connote a cause-effect relationship. Even when there are grounds to believe the causal relationship exits, correlation does not tell us which variable is the cause and which, the effect. For example, the demand for a commodity and its price will generally be found to be correlated, but the question whether demand depends on price or vice-versa; will not be answeredRead MoreLinear Regression1142 Words   |  5 PagesLinear-Regression Analysis Introduction Whitner Autoplex located in Raytown, Missouri, is one of the AutoUSA dealerships. Whitner Autoplex includes Pontiac, GMC, and Buick franchises as well as a BMW store. Using data found on the AutoUSA website, Team D will use Linear Regression Analysis to determine whether the purchase price of a vehicle purchased from Whitner Autoplex increases as the age of the consumer purchasing the vehicle increases. The data set provided information about the purchasingRead MoreCh161260 Words   |  6 Pagestreating the average asking rent as the independent variable. Does a simple linear regression model appear to be appropriate? The below scatter diagram shows a possible curvilinear relationship between the average asking rent and the monthly mortgage on the median-priced home. Therefore, a simple linear regression model does not appear to be appropriate. b. Use a simple linear regression model to develop an estimated regression equation to predict the monthly mortgage on the median-priced home givenRead MoreRelationship Between Capita And College Graduation Rate1551 Words   |  7 PagesThe Excel Regression tool built a linear model using my data and variables to produce a summary output of my regression analysis. My equation provided by my Excel regression model can be written as Y=74.7255954+(-0.0000309729)X1+(12.95779303)X2+ÃŽ µ. This may seem difficult to understand so let me break it down. The regular equation used with two independent variables can be stated: Y=B0+B1X1+B2X2+ÃŽ µ. This equation is formulated by using the â€Å"Coefficients† column on the Excel Regression Analysis for eachRead MoreReal Estate Data Set1099 Words   |  5 Pagesgive an educated guess on a linear regression model for pricing real estate using a real facts date set using numbers and facts. Normally two approaches are used for valuing a re al estate property: income and sales comparison. The sales assessment approach values a real estate property based on sale prices of similar properties. In this case the properties with familiar individuality are basically on the same price level, it would be typical to use a linear regression model to complete this demonstrationRead MoreData Analysis : Correlation, Univariate And Multivariate Regression Models Essay1200 Words   |  5 Pages2.4 Data Analysis: Correlation, Univariate and Multivariate regression models Multivariate regression is a statistical tool used to predict the functional relationship between some dependent variable and a set of independent variables [13, 14]. It comes as a generalization to simple univariate regression models therefore it will be introduced accordingly. However selecting which variables best influence the survival rate in LC is quite difficult. Out of 153 collected prognostic variables, only fewRead MoreIv.Proposed Model. This Section Introduced The Proposed1333 Words   |  6 Pagespredicting failure of agile software projects. The proposed model is composed of three parts: as shown below in figure 4. - Review recent papers to extract important of failure factors in agile software projects. - The proposed model uses multiple linear regressions to determine critical failure factors in agile software projects. - The proposed model uses fuzzy logic for predicting failure of agile software projects. Figure4. The Proposed Model for Predicting Failure of Agile Software Projects Read MorePay for Performance in the NFL1697 Words   |  7 Pagesin the National Football League. Many different positions in football are difficult to obtain good performance measures. Offensive lineman, special teams players especially do not have good measures of individual performance that are tracked. This analysis will focuses on two groups of NFL players, quarterbacks and running backs where individual performance measures are readily available. Analytical Technique A correlation study will be done on a variety of performance measures and the salaries