Explore BrainMass

Explore BrainMass

    Regression Analysis

    BrainMass Solutions Available for Instant Download

    Question about Regression Analysis

    Data: Hours 342 426 317 545 264 451 1049 631 512 266 492 562 298 1. An agent for a residential real estate company in a large city would like to be able to predict the monthly rental cost of apartments based on the size of the apartment. Data for a sample of 25 apartments in a particular neighborhood are provid

    Multiple regression analysis: Size of bill vs number of days the bill is late

    See attached file for data. Need assistance in producing the charts, graphs and analysis associated with this project. This exercise involve multiple regression analysis. We want to determine whether the size of the bill has an effect on the number of days the bill is late. The statistical analysis of the data involves

    Box-Jenkins vs. Regression Analysis

    I will be discussing with classmates the Box-Jenkins identification process and am looking for some direction/key points for the following question: What is the main difference between using Box-Jenkins ARIMA and regression analysis and how could it be best used within a business setting?

    Statistical Analysis

    Production costs for a large number of previous orders of varying sizes for a product are in the attached file. An analyst computes the production cost per unit in each order and averages these to get $50. Using this he gives a cost estimate of $24,000 for a new order for 500 units. Is this a reasonable cost estimate? Explai

    The Regression Effect

    A human resources director, on learning about the regression effect, decides to hire people who have been fired by their previous employer for poor performance. He argues that the regression effect says people who perform very poorly in their previous job tend to perform well in their next job. Is this what the regression effe

    MA 14-34. Cost Estimation, Interpretation, and Analysis

    Carolina Table Company produces two styles of tables, dining room and kitchen. Presented is monthly information on production volume and manufacturing costs: Please see Ms Excel attachment Required: a. Use the high-low method to develop a cost-estimating equation for total manufacturing costs. Interpret the meaning of t

    Regression analysis is performed.

    In table 4.1 of your text, an equation was estimated after applying regression analysis techniques on the data of A, B, C, D sets of Y = 3 + 0.5X. What does 3 and .5 mean? Is this slope positive or negative? Is the slope positive or negative of the equation Y = 5 â?" 0.3X? How can you quickly tell whether or not it is a po

    Multiple regression models to predict birth rates

    Please see attached file for proper format. 13.30 A researcher used stepwise regression to create regression models to predict BirthRate (births per 1,000) using five predictors: LifeExp (life expectancy in years), InfMort (infant mortality rate), Density (population density per square kilometer), GDPCap (Gross Domestic Produ

    Relationship between age-adjusted percent smoking & time

    The estimated age-adjusted percent of persons 18 years of age and over who smoke cigarettes are shown below for females and males for selected years. Estimated Age-Adjusted Percent Smoking Cigarettes Year Female Male 1965 33.7 51.2 1974 16.9 42.8 1979 25.3 37 1985 22.5 32.2 199

    Analyze Role of Researcher in Regression Analysis

    At the heart of quantitative research is regression analysis. A regression model simply measures the association of two variables - variation: the dependent variable's observed value from its mean in relation to the independent variables observed value from its predicted value. I refer to this as 'variation of numbers in a col

    Regression Analysis

    The IRS wants to develop a method for deteting whether or not individuals have overstated their deductions for charitable contributions on their tax returns. To assist in this effort, the IRS supplied data found in the file Dat9-7.xlsx that accompanies this book listing the adjusted gross income (AGI) and charitable contribution

    Correlation and Regression question

    1- Refer to the following information to answer Questions A through D.To help gain a better understanding of the relationship between the return on the common stocks of small companies and the return on the S&P 500 Index, you run a simple linear regression to quantify this relationship using the monthly return on small stocks as

    Predict used selling price based on mileage.

    Please see attached file for figure. The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. The bivariate data given below were taken from a sample of sixteen Cadets, each bought new two years ago, and each sold used within the past month. For each Cadet in the sample, we have liste

    ANOVA and Regression Analysis Project

    See attachment for missing data tables. Assume that you are working on a team that has been commissioned by a large school district to collect and analyze data related to a recent curriculum experiment designed to improve student scores on state-wide standardized tests. The schools in this district are predominantly large, u

    Hypothesis testing

    Statistics Problems 1. Given: The paired sample data of the age and alcohol consumption of men result in a linear correlation coefficient close to 0. Conclusion: Older men tend to consume more alcohol than young men What is the error in the stated conclusion? 2. The eruption height and the time interval after erupt

    Regression Analysis: Cost Vs Output

    Describe each cost category as fixed or variable based upon the following simple regression results where cost is the dependent variable Y and output is the independent variable X. **See attached spreadsheet for formulas and applicable data** Output Cost1 ($) Cost2 ($) Cost3 ($) 0 17,000 11,000 0 100 10,000 7,000 1,000

    Statistics Quiz

    1)Go out and find at least 20 observations of ordered-pair data where one variable (X) is independent and (Y) is dependent. Here is my problem: Consider the following table, which contains measurements on two variables for ten people: the number of hours the person spent riding a bicycle in the past week and the number of mont


    Level Master - Please See attached data file. You work in the shipping and logistics department for Beast Buy, an American mail order company that specializes in pet food for VERY exotic pets. Beast Buy has four warehouses/distribution centers that provide product to each of four different regions in the US; Atlanta services

    ANOVA Analysis for Different Warehouse Distribution Centers.

    You work in the shipping and logistics department for Beast Buy, an American mail order company that specializes in pet food for VERY exotic pets. Beast Buy has four warehouses/distribution centers that provide product to each of four different regions in the US; Atlanta services the southeast, Boston services the northeast, Cle

    Regression for salary data

    See attached data file. The data for this problem are fictitious, but they are not far off.) For each of the top 25 business schools, the file P11_61.xlsx contains the average salary of a professor. Thus, for Indiana University (number 15 in the rankings), the average salary is $46,000. Use this information and regression

    Regression Analysis: Incarceration Services of AIU data

    See attached data file. First run a regression analysis using the Incarceration Services column of all data points in the AIU data set from Unit 1 as the independent variable and the Legal Services satisfaction column of all data points in the AIU data set as the dependent variable. Run a second regression analysis using t

    Regression Function for Salary and Age Variables

    See the attached data file. Use Excel's regression function with Salary as the dependent variable (y variable) and Age as the independent variable (x). Write the regression equation explicitly. Compare to the scatter plot equation. The assignment must be presented in a Word document. Copy and paste material from Excel. C

    Linear Regression and Correlation of a Random Sample

    8. The following hypotheses are given. H0: p >= 0 H1: p < 0 A random sample of 15 paired observations have a correlation of -.46. can we conclude that the correlation in the population is less than zero? Use the .05 significance level.

    Regression Table

    2. Assume that you are a policy analyst. Your staff has collected cross-sectional data on the determinants of average length of stay in various hospitals. A staff member hands you the following table or regression results, assuming that you know how to interpret it. Table. Regression Results for the Impact of Various Factors on