Explore BrainMass

Regression Analysis

Generate a linear regression equation and provide an analysis of the residuals.

For the y and x values listed in file XR15066, obtain the simple linear regression equation, then analyze the residuals by (a) constructing a histogram, (b) using a normal probability plot, (c) plotting the residuals versus the x values and (d) plotting the residuals versus the order in which they were observed. Do any of the as

Linear Regression Analysis.

The following data represent x = boat sales and y = boat trailer sales from 1995 through 2000.0 Year Boat sales (thousands) Boat trailer sales (thousands) 1995 649 207 1996 619 194 1997 596 181 1998 576 174 1999 585 168 2000 574 159 a. determine that least-squares regression line and interpret its slope b. estimate,

Market Research for 6000-square-foot house in Lake Louise

My brother would like to retire and move to a quieter place, probably away from me. I suggested area around Lake Louise. But he had a more remote location in mind...... He did some housing market research in a secret destination, and would like to have me taking a look at his data. Square Footage Asking Price (Canadian

Testing for a Linear Correlation.

In these two exercises, construct a scatter plot, find the value of the linear correlation coefficient r, find the critical value of r from Table A-6 by using α = 0.05, and determine whether there is a linear correlation between the two variables. Song Audiences and Sales The table below lists the numbers of audience

Regression analysis and interpretation.

Please see attached. According to the Capital Asset Pricing Model (CAPM), the risk associated with a capital asset is proportional to the slope ß obtained by regressing the asset's past returns with the corresponding returns of the average portfolio called the market portfolio. (The return of the market portfolio represents

Regression analysis questions.

3. Given are five observations collected in a regression study on two variables. X1 | 2 6 9 13 20 Y1| 7 18 9 26 23 a. Develop a scatter diagram for these data. b. Develop the estimated regression equation for these data. c. Use the estimated regression

Four questions about a least squares regression line.

1. The least squares regression line given above is said to be a line which "best fits" the sample data. The term "best fits" is used because the line has an equation that minimizes the ______, which for these data is______. 2. For the data point (225.3, 308.1), the value of the residual is_____. (Round your answer to at le

Regression analysis: interpret the results of a linear regression analysis.

After deciding on the appropriateness of a linear model relating coffee sales and maximum temperature, the managers calculate the equation of the least squares regression line to be Yhat = 2492.09 - 10.48X. 1) For these data, coffee sales values that are greater than the meand of the coffee sales values tend to be paired with

Degrees of Freedom and test statistic

Recently, students in a marketing research class were interested in the driving behavior of students. Specifically, the marketing students were interested if exceeding the speed limit was related to gender. They collected the following responses from 100 randomly selected students:

Step-by-step answer to Time Series Analysis

The monthly number of permits granted for building houses in a large city is seasonal (there tend to be more permits granted for construction during spring and summer months than during winter months). The following table shows the monthly seasonal indexes for building permits: JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

Regression Question using a Scatter-Plot

Please see the attached file. The scatter-plot above shows the proportion of perch eaten by bass against the number of perch in a pen before the bass were let in. There is a roughly linear pattern. The least-squares line for predicting proportion eaten from initial count of perch is: Proportion eaten= 0.120 + (0.0086 x count

Multiple regression equation. Given the computer output from a regression analysis, write the regression equation, describe the variables, and decide of some of the variables should be eliminated from the equation.

Thompson Machine Works purchased several new, highly sophisticated machines. The production department needed some guidance with respect to qualifications needed by an operator. Four variables were listed. X1 = Length of time employee was a machinist X2 = Mechanical aptitude test score X3 = Prior on -the-job rating X4 = A

Simple linear regression using MegaStat

Choose the dependent variable and the independent variable. Use Megastat or Minitab to obtain the bivariate regression and required graphs. a) Are the variables cross sectional data or time series data? b) How do you imagine the data was collected? c) Is the sample size sufficient to yield a good estimate? If not do you th

Statistics - Regression Analysis

Regression Analysis We want to investigate the relationship of several factors to employees' current salaries. Included in the data is a sample of 37 employees. The first column is an ID. The second column is the time, in months, in their current job (VAR 1). The third column is the time, in years of related job experienc

Interpreting the stepwise regression output

Please see the attached file. 13.30 A researcher used stepwise regression to create regression models to predict birth rate (births per 1000) using five predictors, life exp (life expectancy in yeras), inform (infant mortality rate), density (population density per square kilometer), GDP cap (Gross domestic product per capita),

Hypothesis Testing for the slope of a least squares regression line.

An advertising firm wishes to demonstrate to potential clients the effectiveness of the advertising campaigns it has conducted. The firm is presenting data from recent campaigns, with the data indicating an increase in sales for an increase in the amount of money spent on advertising. In particular, the least-squares regression

Regression analysis - Least Squares Regression Line

What is the least squares regression line equation ? What are the slope and the y-intercept? What is the R-squared value? Conclusion make specific comments and give reasons regarding any similarities or differences in the output results. Which regression produces the strongest correlation coefficient result? Why?

Quantitative Research Methods

Please see the attached file. 1) Help Elaborate Purpose Statement 100-200 words The dependent variable (Cost of the home in $) is determined by independent variables (Square footage, Number of bedrooms and Age) The most important independent variable in this relationship is the Square footage because the Cost of the hom

Interpreting Regression Coefficients

A real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently sold homes in the area, the variables y = sales price (in thousands of dollars) x1 = total floor area (in square feet) x2 = number of bedrooms x3 = distance to nea

Correlation, Causation and Regression

Question 1: What is correlation? Does correlation prove causation? Why or why not? Explain and provide examples to support your explanation. Questions 2: What are the differences between regression and correlation analysis?

Home Insulation Manufaturer: Regression Coefficients

Cellulon, a manufacturer of a home insulation, wants to develop guidelines for builders and consumers regarding the effects (1) of the thickness of the insulation in the attic of a home and (2) of the outdoor temperature on natural gas consumption. In the laboratory they varied the insulation thickness and temperature. A few of

Linear regression

See attached What is the slope of the least-squares regression line for these data?

Basic estimation techniques

Given cellar capacity constraints, The Kalamazoo Brewing Company (KBC) currently sells its microbrews in a seven-state area. The company's marketing department has collected data from its distributors at each state. Data on the quantity and price (per case) of microbrews sold in the state of Ohio, as well as the average incom

Multiple regression

See attachment. 7. The following equation was estimated as the demand function for gasoline (number of observations equals 1,682, and standard errors are in parentheses): _lnQ = 3.95 - 0.525lnP - 0.263lnAge + 0.129lnY - 0.211lnPc + 0.796LnD - 0.103U + 0.182R_ (1.51) (0.105) (0.920)

Correlation and Regression - Let x be the age of licensed driver in years. Let y be the percentage of all fatal accidents(for a given age)due to failure to yield the right of way. For example, the first data pair says that 5% pof all fatal accidents involving 37year olds are due to failure to yield the right of way. ...

Let x be the age of licensed driver in years. Let y be the percentage of all fatal accidents(for a given age)due to failure to yield the right of way. For example, the first data pair says that 5% pof all fatal accidents involving 37year olds are due to failure to yield the right of way. X: 37, 47, 57, 67, 77, 87 Y: 5, 8, 10 ,