Explore BrainMass

Explore BrainMass

    Regression Model Validation

    Regression model validation is the process of deciding whether the numerical results quantifying hypothesized relationships between variables, obtained from regression analysis, are in fact acceptable as descriptions of the data. The validation process can involve analysing the goodness of fit of the regression residuals is random, and checking whether the model’s predictive performance deteriorates substantially when applied to data that were not used in model estimation.

    A high R2 does not guarantee that the model fits the data well. This is because Anscombe’s quartet shows a high R2 can occur in the presence of misspecification of the functional form of a relationship or in the presence of outliers that distort the true relationship. The problem with the R2 as a measure of model validity is that is can always be increased by adding more variables into the model, except in the unlikely event that the additional variables are exactly uncorrelated with the dependent variable in the data sample being used.

    The residuals from a fitted model are the difference between the responses observed at each combination values of the explanatory variable and the corresponding prediction of the response computed using the regression function. If the model fit to the data were correct, the residuals would approximate the random errors that make the relationship between the explanatory variables and the response variable a statistical relationship. 

    © BrainMass Inc. brainmass.com April 25, 2024, 11:02 am ad1c9bdddf

    BrainMass Solutions Available for Instant Download

    Predict small-business mean annual revenue for US metro areas

    A small business analyst seeks to determine which variables should be used to predict small-business mean annual revenue for U.S. metropolitan areas. The analyst decides to consider the independent variables age, the mean age (in months) of small businesses in the metropolitan area; and BizAnalyzer, the mean BizAnalyzer score of

    Correlational Analysis in SPSS

    Construct a research question using the General Social Survey dataset, which can be answered by a Pearson correlation and bivariate regression. Use SPSS to answer the research question. Post your response to the following: 1. What is your research question? 2. What is the null hypothesis for your question? 3. What research

    Creating suitable regression model

    Using any data of your choice or use the attached: build an optimized regression model eliminating non-significant Betas. Provide the Betas for the significant variables. How can a institution use these results to optimize its cost and labor in acquiring new students (enrollments)?  How can one use these results to sharpen

    Regression Assumptions

    Based on the text on regression assumptions and your additional research, discuss the potential impact of assumption violation on interpretation of regression results. Is there any influence of the assumption violation on the business decision making? If so, how? If not, why?

    Logistic Regression Model

    Question 1. The logistic regression model produced the following table of predictions: a. Find the likelihood of the data (true values) using your predictions. b. Find the log-likelihood of the data using the probabilities from your predictions. c. What is the null model prediction? (single prediction for a

    Locally Weighted Regression

    In this exercise will investigate locally weighted regression models to predict the prize winnings ($1000s) given a variety of information about performance and success statistics for LPGA golfers in 2009.The table attached (see excel file) contains data related to performance and success statistics for LPGA golfers in 2009. The

    Ridge Regression

    TQ6: Ridge Regression This exercise work will investigate ridge regression to predict the prize winnings ($1000s) given a variety of information about performance and success statistics for LPGA golfers in 2009.The table attached (see excel file) contains data related to performance and success statistics for LPGA golfers in 20

    Partial Least Squares Regression

    TQ5: Partial Least Squares Regression Investigate PLS models to predict the prize winnings ($1000s) given a variety of information about performance and success statistics for LPGA golfers in 2009. The table attached (see excel file) contains data related to performance and success statistics for LPGA golfers in 2009. The matri

    Finding the estimated equation of multiple regression

    A study investigated the relationship between audit delay (delay), the length of time from a company's fiscal year-end to the date of the auditor's report, and variables that describe the client and the auditor. Some of the independent variables that were included in this study follow. Industry A dummy variable coded 1 if t

    Principal Component Analysis and Regression

    TQ4: Principal Component Analysis and Regression NOTE: Use MATLAB or MINITAB OR SAS and Include all your code The table attached (see excel file) contains data related to performance and success statistics for LPGA golfers in 2009. The matrix X contains 11 predictor variables: 1. Average drive (yards) 2. Percent of fairways

    Regression model using MATLAB

    The table attached (see excel file) contains data related to performance and success statistics for LPGA golfers in 2009. The matrix X contains 11 predictor variables: 1. Average drive (yards) 2. Percent of fairways hit 3. Percent of greens reached in regulation 4. Average putts per round 5. Percent of sand saves (2 shots t

    Excel on the topic of multiple regression

    I need assistance completing this assignment in excel format CHAPTER 13 EXERCISE 6 The owner of Maumee Ford-Mercury-Volvo wants to study the relationship between the age of a car and its selling price. Listed below is a random sample of 12 used cars sold at the dealership during the last year. Car Age (years) Selling Pri

    Campus safety concerns at Capella University

    As a result of recent campus safety concerns at Capella University, you have been engaged by campus security team leaders to gather and analyze data about on-campus crime rates in schools in the state of Minnesota. Crime data from 181 Minnesota campuses has been compiled in the Campus Crime Data file. Write a management report f

    Multiple regression analysis in SPSS..

    Complete Smart Alex's Task #4 on p. 355 to perform a multiple regression analysis using the Supermodel.sav dataset from the Field text. You can follow the steps outlined on pp. 316-320 as a guide. Report your findings in APA format according to the guidelines in the PASW Application Assignment Guidelines handout. The final docu

    Simple regression analysis and multiple regression model predict

    Project Part III: Modeling Credit Balances for Pinnacle Fitness April 12, 2015 We are called upon by the senior management of Pinnacle Fitness to increase our credit volume. In order to do this, we will use linear regression analysis to identify those characteristics of our current credit customers. Using MINITAB perform a s

    Regression Analysis: Predictive Equations

    In 2012, the total payroll for the New York Yankess was almost $200 million, while the total payroll for the Oakland Athletics (a team known for using baseball analytics or sabermetrics) was about $55 million, less than one-third of the Yankees payroll. In the table attached to the Excel file, you will see the payrolls (in milli

    Regression and Correlation Analysis to Examine Medical Records

    Question 6 Medical records show strong positive correlations between the number of days a patient stays in the hospital, the total cost of the visit and the number of different illnesses the patient has (a) Does this mean more efficient management practices that reduce the length of hospital stays could reduce the number of dif

    Perform simple regression analysis and calculate Durbin-Watson statistic

    A freshly brewed shot of espresso has three distinct components: the heart, body, and crema. The separation of these three components typically lasts only 10 to 20 seconds. To use the espresso shot in making a latte, a cappuccino, or another drink, the shot must be poured into the beverage during the separation of the heart, bod

    Regression Analysis Calculation on Real Estate Company Case Study

    An agent for a residential real estate company in a large city has the business objective of developing more accurate estimates of the monthly rental cost for apartments. Toward that goal, the agent would like to use the size of an apartment, as defined by square footage to predict the monthly rental cost. The agent selects a sa

    Regression Analysis - Waterskiing & Theatres

    Using the attached data: Question 1 The owner of Showtime Movie Theatres, Inc., would like to estimate weekly gross revenue as a function of advertising expenditures. Develop an estimated regression equation with the amount of television advertising as the independent variable. Is this equation significan

    Quantitative Analysis - Descriptive Stats, Correlation & Regression

    The question calls for me to do a quantitative analysis of the attached data from a retail women's store. It should include calculations for correlations, descriptive statistics and multiple regressions. Basically, I am to use this information in an effort to give managerial recommendations. I'm not sure where to begin or w

    SPSS Regression Analysis

    1. Create a model for the relationship between the available variables and the test scores. 2. Transform enrollment counts and mean salary for new teachers by dividing by 1,000 and run the regression analysis using the following variables: enrolled students in 1,000s per pupil expenditures for gifted programs

    Normal Distribution and Simple Regression

    1. The Graduate Record Exam (GRE) has a combined verbal and quantitative mean of 1000 and a standard deviation of 200. Scores range from 200 to 1600 and are approximately normally distributed. For each of the following problems: (a) draw a rough sketch, darkening in the portion of the curve that relates to the answer, and (

    Multiple Regression Model for a Real Estate Broker

    You are a real estate broker who wants to compare property values in Glen Cove and Roslyn. Make sure to include dummy variable for location in the regression model a. Develop the most appropriate multiple regression model to predict appraised value. b. What conclusions can you reach concerning the differences in appraised valu

    Performing and Interpreting Simple Regression and the Results

    One of the assertions is that changes in Federal Reserve policy can affect inflation. Using the data on the growth rate of M2 and inflation in your spreadsheet, run a regression of the rate of inflation on the rate of growth of the money supply. Do the data support a connection between the rate of increase in the money supply a


    A regression model relating the yearly income (y), age (x1), and the gender of the faculty member of a university (x2 = 1 if female and 0 if male) resulted in the following information. y=5000+ 1.2x1 + 0.9x2 n=20 SSE=500 SSR= 1500 Sb1=.2 Sb2=.1 How do I calculate the t test stat foe x2? How do I determine the multiple coeff


    MGMT814-1402C-01 Quantitative Research Methods Task Name: Phase 2 Individual Project Deliverable Length: SPSS Outputs and 200-500 words answering questions Details: Weekly tasks or assignments (Individual or Group Projects) will be due by Monday, and late submissions will be assigned a late penalty in accordance with the la

    Logistic Regression with SPSS

    A researcher is analyzing a dataset to determine whether the independent variables predict students' reading level. The dependent variable is reading level (1=good reader, 0=poor reader). The four independent variables are age, SES (1=upper, 2=middle, 3=lower), teaching approach (1=computer, 2=traditional), and amount of readin

    Cronbach's Alpha Calculation

    1. Subscale 1 (Fear of computers): items 6,7,10,13,14,15,18 2. Subscale 2 (Fear of statistics): items 1,3,4,5,12,16,20,21 3. Subscale 3 (Fear of Mathematics): items 8,11,17 4. Subscale 4 (Peer evaluation): items 2,9,19,22,23 I was asked to analyze data using IBM SPSS Statistics I was asked to Calculate Cronbach's alpha on