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Regression Analysis

Forecasting - Linear Regression

I'm working on linear regression and I'm stuck on the equation because I'm coming up with a negative number which I don't think is an accurate forecast. The problem also asks for error tests, which I think I have the correct formulas for and will work once the first part is done. Please help! Full details and questions attached

Regression analysis between work fatalities and unemployment

A highway employee performed a regression analysis of the relationship between the number of construction work-zone fatalities and the number of unemployed people in a state. The regression equation is Fatalities _ 12.7 _ 0.000114 (Unemp). Some additional output is: Predictor Coef SE Coef T P Constant 12.726 8.115 1.57 0.134

Statistics Questions

Please see the attached file. 15.2 Teenagers make up a large percentage of the market for clothing. Below are data on running shoe ownership in four world regions (excluding China). Research question: At α = .01, does this sample show that teenage running shoe ownership depends on world region? (See J. Paul Peter and Jer

Time series analysis

Barbara lynch is the product manager for a line of skiwear produced by Health Co Industries and privately branded for sale under several different names .A part of Ms Lynch's is to provide a Quarterly forecast of sale for the northern United State ,a region composed of 27 states stretching from Maine to Washington. A 10 years hi

Multiple regression analysis problems

3. The director of marketing at Reeves Wholesale Products is studying the monthly sales. Three independent variables were selected as estimators of sales: regional population, per-capita income and regional unemployment rate. The regression equation was computed to be (in pounds). Y' = 64,100 + 0.394X1 + 9.6X2 + 11,600X3

Bingo Hamburger Co has a chain of 12 stores in a large city.

Bingo Hamburger Co has a chain of 12 stores in a large city. Sales figures and profits for the stores are given in the following table. Obtain a regression line for the data & predict profit for a store assuming sales of $10 million. X Y SALES PROFITS $7 $.15 2 .10

Regression Analysis: Example Problem and Solution

I am trying test what is the positive or negative correlation between the price of a gallon of retail gasoline and the company profits. The company profits range from 0 to 25 billions dollars, while the gas prices range from $2.71 to $3.79 dollars per gallons. Use the regression equation: Y'= a + bX

Forecasting using different methods

A manufacturer has experienced the following monthly demand for one of their products Month Actual Demand (in cases) Feb 1500 March 2860 April 2950 May 3490 June 3000 July 3200 Aug

simple linear regression models

Develop simple linear regression models for predicting Games Won as a function of each of the independent variables in the 2000 NFL Data.xls worksheet individually. Do the assumptions of linear regression hold for your models? How do these models compare to the multiple regression models?

When to use Correlation or Regression Analysis

1. Please describe a situation in which a correlation analysis or regression analysis could contribute to a better decision. The situation can be from a work, of general interest, or experienced in private life. 2. Please describe a situation in which correlation analysis or regression analysis can be (or was) misused to

Statistics - Regression Output - Interpretation

In the following regression, X = total assets ($ billions), Y = total revenue ($ billions), and n = 64 large banks. (a) Write the fitted regression equation. (b) State the degrees of freedom for a two-tailed test for zero slope, and use Appendix D to find the critical value at α = .05. (c) What is your conclusion about

Scatter Plot for Absences Versus Grades

10. You are given the following data. Number of Absences Final Grade 0 96 1 91 2 78 2 83 3 75 3 62 4 70 5 68 6 56 a. Make a scatter plot for the data. b. Find the correlation coefficient for the data. c. Find the equation for the regression line for the data, and predict the final grade of a student who misses 3

Example Regression Analysis: Problem and Solution

The following data represent Aggregate Consumption (Y) and Disposable Income (X) for one country. Year Y X 1993 103 114 1994 105 118 1995 108 126 1996 107 130 1997 122 136 1998 124 140 1999 128 148 2000 130 156 2001 142 160 2002 147 164 2003 154 170 2004 151 178 a. Draw a scatter diagram for th

Regression analysis is adopted to predict direct labor cost (y) on the basis of branch size (x) of a product produced in a job shop. Step by step method for regression analysis is discussed here. Regression coefficients, coefficient of determination, scatter diagram and significance of regression model are explained in the solution.

Always get overwhelmed by the amount of material when covered at a comprehensive level. Attached is the study material of what to be prepared to cover at the conclusion of this course. I have worked through them but get stumped at several points. Can you provide a systematic approach to these problems and provide a reference to

Correlation and Regression

See attachment for the problems I am struggling with. Thanks in advance for any help provided. In the following 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 if there is a linear correlation betwe

The Minnesota Department of Transportation

The Minnesota Department of Transportation hoped that they could measure the weights of big trucks without actually stopping the vehicles by using a newly developed "weight-in-motion" scale. To see if the new device was accurate, they conducted a calibration test. They weighed several trucks when stopped (static weight) assumin

Regression Analysis for life insurance data

Would like step-by-step guidance with the attached statistics problems. 1. Compute the regression equation (Solving of both "a" and "b") and compute the standard error of the estimate. Sample size = 20 X= amount of disposable Income (000$) Y= amount of life insurance (000$) Sum of X = 334 Sum of Y = 799 Sum of X*Y=

Forecasting using Regression Analysis

Demand for stereo headphones and CD players for joggers has caused Nina Industries to experience growth of almost 50% over the past year. The number of joggers is continuing to expand, so Nina expects demand for headsets to also expand. Demands for the stereo headsets for last year was as follows: January 4,200 February 4,

Multiple Regression example

Reggie is really excited because he managed to bust out enough manners to convince a lady to go to prom with him (take that, R^2 of .025!). Reggie realizes that manners alone will not be enough to woo his lady friend and guarantee a happy night out, and so he decides to research the style choices of 15 of his most idolized fashi