Multiple Regression Model Essay - 2133 Words

Project: Multiple Regression Model Introduction Today’s stock market offers as many opportunities for investors to raise money as jeopardies to lose it because market depends on different factors, such as overall observed country’s performance, foreign countries’ performance, and unexpected events. One of the most important stock market indexes is Standard Poors 500 (SP 500) as it comprises the 500 largest American companies across various industries and sectors. Many people put their money into the market to get return on investment. Investors ask themselves questions like how to make money on the stock market and is there a way to predict in some degree how the stock market will behave? There are lots and lots of†¦show more content†¦Decrease in house prices is one of the possible contributors to recession because the home owners lose their equity in their houses. Considering such recession scenario, the stock market always becomes bearish. Additionally, house market is considered more st able investment than stock market. When stock market drops, people are willing in the houses and HPI goes up. We assume that HPI and stock market shouldn’t move in the same direction thereby we don’t take into consideration the complex scenario of 2008. ÃŽ ²4: 10-Year Treasury Constant Maturity Rate impacts on the number of issued bond and is used as risk free rate to calculate the excess return on the investment. It also has an influence on the stock market. ÃŽ ²5: Gross Domestic Product of the US is important for business profit and this can drive the stock prices up. Investing in the stock market seems reasonable when the economy is doing well. If the economy is growing fast then the stock market should be affected positively, the investors are more optimistic about the future and they put more money into market more. This variable is crucial for the dependent one. ÃŽ ²6: Gross Domestic Product of Spain. Since Europe is currently in a recession, we wanted to include the GDP of Spain, as one of the weakest economies in Europe now, to check if there is any relationship betweenShow MoreRelatedStages Of Hierarchical Multiple Regression Model1343 Words   |  6 Pagesstage hierarchical multiple regression was conducted with Partner’s Body Type as the dependent variable. Age was entered at stage one of the regression and Body Type and Relationship Status were entered at stage two. The variables were entered in this order since people are more likely to be in a relationship as they get older, thus we wanted to determine if the other variables had a unique contribution that was not already accounted for by age. The hierarchical multiple regression revealed that atRead MoreProject Complexity Based On A Multiple Regression Model Essay1436 Words   |  6 PagesAdjusted lead time: The number of months required to develop a project of aver age project complexity, based on the adjustment method, which is based on a multiple regression model. Project complexity: the complexity of project developed measured based on different factors that incorporates, platform design, body style, and powertrain into overall index (European projects had the highest complexity index overall, while united states and Japanese projects decreased complexity) Adjusted engineeringRead MoreCurrent Variables For Multiple Linear Regression Models1870 Words   |  8 PagesMultiple linear regression models are commonly used in demand estimations to assess the impact of the multiple independent variables to a dependent variable (Kros, Nadler, 2008). In demand estimation, the demand equation is the regression equation. This task is about demand estimation for a leading brand of low-calorie, frozen microwavable food. The following is the demand estimation on the food product with the given regression equation and independent variables. Compute the Elasticities forRead MoreA Note On Quantitative And Quantitative1185 Words   |  5 Pagesverbal b value, x2=GRE score on verbal. B3=predictor 3ï‚ ®ability to interact easily b value, x3=ability to interact easily. Equation- Ã" ®=a+b1(x1) +b2(x2) +b3(x3)ï‚ ®Overall college GPA=2.250+0.002(GRE, quantitative+0.028(ability to interact). Step 1-If the model is significant with a significant value of 0.014, less than 0.05. High F value (3.907), lower significance value (.014). Step 2=Amounted accounted for=R2=.203ï‚ ®20.3% of the variance is accounted for by the predictors. There was a moderate effect sizeRead MoreTypes Of Contingencies, Designing A Contingency, And Owner s Contingency912 Words   |  4 Pagesbase estimate cost that was calculated considering the project as risk free. They claimed that implementing the ERA method improved the accuracy in estimating the contingency amount during pretender stages. Chen and Hartman (2000) studied multiple linear regression (MLR) and artificial neural network (ANN) for prediction of contingency. The authors obtained required data from a large oil and gas owner company for ANN training. They found the ANN method better than the MLR method. Hence, this studyRead MoreQuestions On The Equation For Regression1545 Words   |  7 Pagesthe equation for regression. These are the results: Ã" ®=b+mx or Ã" ®=mx+b, Ã" ®= dependent variableï‚ ®overall, a= constant b, b1=predictor 1ï‚ ®GRE score on quantitative b value, x1 = GRE score on quantitative. b2=predictor 2ï‚ ®GRE score on verbal b value, x2=GRE score on verbal. B3=predictor 3ï‚ ®ability to interact easily b value, x3=ability to interact easily. Equation- Ã" ®=a+b1(x1) +b2(x2) +b3(x3) ï‚ ®Overall college GPA=2.250+0.002 (GRE, quantitative+0.028(ability to interact). Step 1-If the model is significant withRead MoreA Case Study on Cost Estimation and Profitability Analysis at Continenta l Airlines11162 Words   |  45 Pagesapplication of regression analyses to be used as a tool pursuant to understanding cost behavior and forecasting future costs using publicly available data from Continental Airlines. Speciï ¬ cally, the case focuses on the harsh ï ¬ nancial situation faced by Continental as a result of the recent ï ¬ nancial crisis and the challenges it faces to remain proï ¬ table. It then highlights the importance of reducing and controlling costs as a viable strategy to restore proï ¬ tability and how regression analysis canRead MoreThe Human Development Index ( Hdi ) And The Gdp Per Capita1607 Words   |  7 PagesOrganize the data collected into a table using Microsoft Excel to display it. Create a scatter plot of the data to find the r^2 value, regression line, and the regression equation using Microsoft Excel to represent the data collected. Use a graphing calculator to validate the correlation coefficient (r), coefficient of determination (r^2), and the regression equation. Conclude and interpret results. Discuss validity of conclusions and calculations. Discuss possible improvements This data tableRead MoreRegression And Correlation Analysis Paper Essay1128 Words   |  5 PagesStatistics Project PART C: Regression and Correlation Analysis A. Introduction and Summary Report: ALLSEASONS is a Chicago company that specializes in residential heating and cooling systems. Their call center has 100 employees who handle both inbound and outbound calls to schedule appointments for service technicians. Call center employees can schedule any type of appointment but they are assigned to one of three specialized teams, as noted below. During the first week of September the callRead MoreCase Study : Locating New Pam And Susan s Stores1658 Words   |  7 PagesMultiple Regression Project Case Study: Locating New Pam and Susan’s Stores Kim Ramirez Northeaster University MGSC 6200 Information Analysis Professor Grigorios Livanis Instructor Demetra Paparounas April 17, 2016 Introduction: Pam and Susan’s is a chain of discount department stores. There are currently 250 stores, mostly located throughout the South. As the company has grown and wants to expand, Pam and Susan’s is in the search of the most profitable