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Regression Analysis

Regression and Estimating Costs

Production costs for a large number of previous orders of varying sizes for a product are in the file production.xls attached below. 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

MR and LR in SPSS

Problem:SLP (Session Long Project) The dataset FEV.sav contains 6 variables: ID, age in years, FEV=forced expiratory volume in liters, height in inches, sex 0=female, 1=male, and smoke=current smoking s ...there is moreshow problemSLP (Session Long Project) The dataset FEV.sav contains 6 variables: ID, age in years, FEV=forc

Multiple Regression Analysis

TWO SEPARATE PARTS TO THIS******* Hello! We are practicing multiple regression analysis and are needing to come up with an example. Here's what I need help with (and ANY set of data will do!): THIS IS A TWO-PART QUESTION: A Draft of the Project(10 credits), and then the Project (15 credits)--- I would like the draft firs

Correlation, Linear Regression, Chi Square

1) What information is provided by the numerical value of the Pearson correlation? 2) In the following data, there are three scores (X, Y, and Z) for each of the n = 5 individuals: X Y Z 3 5 5 4 3 2 2 4

Applying Time Series Methodologies Simulation

Applying Time Series Methodologies Simulation Complete the simulation Applying Time Series Methodologies located on . During the third cycle of the simulation, you will need to make a decision regarding sales forecasts for Blues Inc. After completing the simulation, prepare a 350-word memo to Myra Reid, the Vice President, Pr

Multiple regression model in Excel

Data Set to be used: Lottery Education Age Children Income 5 15 50 2 41 7 10 26 0 22 0 13 40 3 24 10 9 46 2 20 5 14 40 3 32 5 15 39 2 42 3 8 36 3 18 0 16 44 1 47 0 20 47 4 85 6 10 52 1 23 0 18 51 2 61 0 17 41 2 70 12 9 42 2 22 7 12 53 1 27 11 9 72 1 25 2 16 38 2 43 11 12 41 5 34 2 14 50 3 53 7 9 41 3 20 0 16

Independent Variables in Regression Analysis

In regression analysis, the independent variable is: a) used to predict other independent variables b) used to predict the dependent variable c) called the intervening variable d) the variable that is being predicted

Regression results for a bivariate model

12.59 A common belief among faculty is that teaching ratings are lower in large classes. Below are MINITAB results from a regression using Y = mean student evaluation of the professor and X = class size for 364 business school classes taught during the 2002-2003 academic year. Ratings are on a scale of 1 (lowest) to 5 (highes

Regression and Correlation

6. Given the following: Salary (in Thousands) annual absences 22 2.3 23 2.0 25 2.0 27 1.8 31 2.2 32 1.5 34 1.2 37 1.3 40 0.6 a. Graph the data _ b. What is x _ c. What is y d. Find b0 e. Find b1 f. Determi

Regression analysis

Life insurance companies are interested in predicting how long their customers will live, because their premiums and profitability depend on such numbers. An actuary for one insurance company gathered data from 100 recently deceased male customers contained in the file longevity.xls. He recorded the age at death of the customer

Choice of Cost Driver

Study Appendix 3. Richard Ellis, the director of cost operations of American Micro Devices, wishes to develop an accurate cost function to explain and predict support costs in the company's printed circuit board assembly operation. Mr. Ellis is concerned that the cost function that he currently uses? based on direct labor cos

Regression and Correction

You are investigating the relationship between training (x) and performance (y) for your company's employees. The variable y in the following table represents the average job performance rating verses the number of days of training per year for the employees. Training Time(x) Performance(y) 2.49 147.1 2.57 130.1

Regression and Correlation Analysis

1. A Realtor considers the relationship between home size and Market Price. Home Size (1000's), Market Price (1,000s) 2.180 224 2.250 258 2.570 299 2.920 366 3.190 338 3.330 428 a. Determine the correlation coefficient. b. Is there a strong relationship? If so determine the line of

The Solution to Statistics - Regression

In the following regression, X = weekly pay, Y = income tax withheld, and n = 35 McDonald's employees. (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 the slope? (d) Int

Predictions from the least-squares regression line

Fill in the blank: For these data, temperature values that are greater than the mean of the temperature values tend to be paired with values for electricity use that are ____ (greater than or less than) the mean of the values for electricity use. According to the regression equation, for an increase of one degree Fahrenheit

F Test of a Multiple Regression Model for a Finance Department

(Let B = beta) The finance department of an automobile insurance company uses a multiple regression model to estimate the total number of accident claims that will be filed each month. Based on the most recent 17 months of claims data, the company has selected 4 independent variables that it believes are related to accident c

Regression Equations and Prediction

For the following data, find the regression equation for predicting Y from X. X Y 7 16 5 2 6 1 3 2 4 9 A) SSX = 25, SP = 20, Y-hat = .8X - 6 B) SSX = 10, SP = 20, Y-hat = 2X - 5 C) SSX = 10, SP = 20, Y-hat = 2X - 4 D) SSX = 1

Regression model for real estate data

Refer to the data included in the Excel file, which report information on homes sold in the Somewhere, USA, during a recent year. Use the selling price of the home as the dependent variable and determine the regression equation with number of bedrooms, size of the house, whether there is a pool, whether there is an attached gara

Multiple Regression Analysis

Problem 1 A regression of attitude toward legalizing marijuana on age (X1) and education (X2) produced the following estimated coefficients and standard errors for a sample of 265 persons: b1 = -6.24 Sb1 = .346 b2 = +0.33 Sb2 = 0.12 Test one-tailed alternatives to the null hypotheses that ß2 > 0; use a = .01. Pro

Regression models

37. A regional commuter airline selected a random sample of 25 flights and found that the correlation between the number of passengers and the total weight, in pounds, of luggage stored in the luggage compartment is 0.94. Using the .05 significance level, can we conclude that there is a positive association between the two v

Multiple choice question form regression analysis

Please determine if the question is true or false. If the question is false than give a brief description why T F 1. One of the objectives of simple linear regression is to predict the value of the independent variable X as a linear function of the dependent variable Y. T F 2. Regression analysis is limited to establishin

Regression analysis problem

The following regression analysis was designed to explain firm revenues from the number of employees, using a company database of 42 firms. Revenues are measured in millions of dollars, while employees represent the number of people. Regression analysis to predict Revenue from Employees. The prediction equation is: Revenue

Correlation Analysis and Linear Regression

Describe a situation in which a correlation analysis or regression analysis could contribute to a better decision. The situation can be from a work situation, of general interest, or one experienced in a private life situation. Note:This is reffering to formal statistical correlation and linear regression.

Regression analysis

An independent mail delivery service wants to study factors that affect the daily gas usage of its delivery trucks.....

Anova, regression calculations in Excel

1. A research study is documenting the results of an investigation weight loss medication on eight overweight adult males, according to body mass index. Their pre-treatment weight is recorded and compared against their post-treatment weight four weeks later. Pre-Treatment: 185 174 160 225 191 200 172 175 Post-Treatment: 180

Regression analysis

1. A hospital administrator is reviewing the relationship between the length of in-patient stays, x, in days and the total cost of care, y, in dollars. She collected the following sample data: X= 4 6 1 8 10 Y= 1105 1545 345 2125 2785 (a) Construct the regression model in the form , which is the best fit for this biv

Multiple Regression in Excel

Problem #1: The Texas Transportation institute at texas A&M university conducted a survey to determine the number of hours per year drivers wasted sitting in traffic. the table below shows the number of hours wasted per year sitting in traffic. Denver Miami San Francisco 70

Regression ,Hypotheses testing and confidence intervals

1. Scores on a statistics test are normally distributed with a mean of 80 and a SD of 5. The average for a class of 30 is 90. The teacher of that class says that her class has done significantly better than average. a. What null hypothesis would you use to test the teacher's statement? b. What is the mean and the

Regression analysis for advertising expense.

Ann's furniture store is a family business that has been selling to retail customers in the Chicago area for many years. They advertise extensively on radio, TV, and the Internet, emphasizing the low prices and easy credit terms. The owner would like to review the relationship between sales and the amount spend on advertising.

Regression analysis problems .

A town assessor was trying to determine a relationship between the size of a parcel of land (x) and the selling price (y) the assessor used the data in the following table. Size in acres (x) Selling price in thousands of dollars (y) 0.5 25 1.0 40 1.5 55 2.0 65 2.5 75 3.0 80 a. Draw a scatter diagram. Does the sellin