Explore BrainMass

Regression Analysis

Key Data Regarding Multiple Regression Analysis

See attached file for full output. Municipalities and states have been asked by the Department of Energy to assess their energy requirements for each of the alternative fuels. In particular, they have decided to focus initially on natural gas, given the enormity of U.S. reserves and its relative cleanliness. Following ar

Correlation and Regression Analysis

The owner of a retail store randomly selected the following weekly data on profits and advertising cost. Week Advertising Cost ($) Profit ($) 1 0 200 2 50 270 3 250 420 4 150 300 5 125 325 1. Compute the least squares estimated line and predict

Confidence levels, regression analysis, and ANOVA: 3 problems

See attached file. 2. A random sample of 10 examination papers in a course, which was given on a pass or fail basis, showed the following scores. Create a 95% confidence interval for the population with a mean of 75 and Standard Deviation of the population of 10. A. Does this mean fall within that interval, what does t

Home Market Value vs Age: Scatter Chart, Trendline, Regression

See attached data file for data tables 1. Using the data in the Excel in the file Home Market Value, construct a scatter chart for market value versus age and add a linear trendline. Compare the coefficient of determination with the model developed in this chapter. What do you conclude? 2. Using the data in the Excel f

Multiple regression analysis.

The manager of Collins Import Autos believes the number of cars sold in a day (Q) depends on two factors: (1) the number of hours the dealership is open (H) and (2) the number of salespersons working that day (S). After collecting data for two months (53 days), the manager estimates the following log-linear model: Q= aHbSc a)

Multipe Regression Equation for Size and Selling Price

A real estate association in a suburban community would like to study the relationship between the size of a single-family house (as measured by number of rooms) and the selling price of the house (in thousands of dollars). Two different neighborhoods are included in the study, one on the east side of the community (=0) and the

Hypothesis Identification Article Analysis: What can analytics do for a company?

Using the "Competing on Analytics" article by Thomas H. Davenport prepare an analysis of how to compete on analytics. Have at least one industry example from the article. State at least one principle from the article. Based upon the article briefly conclude your review with explaining 'What can analytics such as statistics do

Please help with these statistic problems

Problem 1: (a) How does correlation analysis differ from regression analysis? (b) What does a correlation coefficient reveal? (c) State the quick rule for a significant correlation and explain its limitations. (d) What sums are needed to calculate a correlation coefficient? (e) What are the two ways of testing a correlation

MCQs: Hypothesis Testing & Time series Analysis

See attached file for graphs. 1) if the null hypothesis is not rejected, it can be assumed the proportions are __________ and the differences in them are due to chance. a) equal b) unequal c) small d) large 2) A pharmaceutical company is testing the effectiveness of a new drug for lowering cholesterol. As part of this

Regression Models that Predict Selling Price & SAT Scores

Thirteen students entered the undergraduate business program at Rollins College two years ago. The following table indicates what their grade-point averages (GPAs) were after being in the program for two years and what each student scored on one part of the SAT exam when he or she was in high school. Is there a meaningful relati

Linear regression to justify advertising

You are the marketing manager, in charge of a $1 million advertising budget, for two branches of the Long and Foster Real Estate Company. Because of slumping sales, the company president announces plans for an across-the-board budget cut of 10 percent. However, each department manager will have an opportunity to present his/he

Statistics: Track and Field

The long jump is a track-and-field event in which a competitor attempts to jump a maximum distance into a sandpit after a running start. At the edge of the pit is a takeoff board. Jumpers usually try to plant their toes at the front edge of this board to maximize their jumping distance. The absolute distance between the front ed

Data tables with excel regression with dependent variable

The data table in the excel file tabulates a pizza parlor's advertising expenditures and sales for 8 consecutive quarters. The marketing manager wants to know how much of an impact current advertising will have on sales two quarters from now. While running a regression with the dependent variable sales and the independent var

Regression Analysis: Predicted value

The regression analysis in the Excel file relates US annual energy consumption in trillions of BTUs to the independent variable US Gross Domestic Product (GDP) in trillions of dollars. Excel Output US Energy Consumption (in trillion BTUs) vs. Gross Domestic Product ($trillions) Regression Statistics

Simple regression or multiple regression

Market researcher Ally Nathan is studying the relationships among price, type (classical or steel string), and consumer demand for acoustic guitars. She wants to find the relationship between demand and price, controlling for type. To determine this relationship, she should A-Run a simple regression of the dependent variable


In a regression analysis with multiple independent variables, multicollinearity can be caused by: A- A strong nonlinear relationship between the dependent variable and one or more independent variables. B-A strong heteroskedastic relationship between the dependent variable and one or more independent variable.

Research: Regression and Correlation Analysis

Please help answer the following question. Provide at least 200 words. What is the possible uses of regression and correlation analysis in doctoral-level research? Would I be able to use these techniques in my dissertation, or any application in other areas?

Description of Correlation and Regression Analysis

6. For the following scores, X Y 3 12 6 7 3 9 5 7 3 10 a. Compute the Pearson correlation. b. With a small sample, a single point can have a large effect on the magnitude of the correlation. Change the score X = 5 to X= 0 and compute the Pearson correlation again. You should find that the change ha

Regression Analysis and Correlation Coefficient..

See data file attached. Do workers who receive more education miss fewer work days? The attached data represents the number of sick days taken by 20 Delta workers along with the number of hours of education they received. Analyze the data using both regression and correlation techniques. Use Excel to show output / results.

Critical Value for Sales and Advertising Data

Exhibit 12-2 Regression analysis was applied between sales data (in $1,000s) and advertising data (in $100s) and the following information was obtained. Y with hat= 12 + 1.8x n= 17 SSR = 225 SSE = 75 sb1= 0.2683 1. Refer to Exhibit 12-2. The critical F

Linear and Multiple Regression Analysis

1. It is believed that GPA (grade point average, based on a four point scale) should have a positive linear relationship with ACT scores. Given below is the Excel output from regressing GPA on ACT scores using a data set of 8 randomly chosen UB students. Regressing GPA on ACT Regression Statistics Multipl

Regression Analysis

In this question, the datasets contain country-level data on total fertility rates and girls' educational levels, in both developing and developed countries. In the answer, examine the relationship between a country's total fertility rate (TOTRATE, the outcome in these analyses) and the aggregate educational level of girls i