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Regression Analysis

Statistic help

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.At the .05 level of significance determine if the correlation between rental cost and apartment size is significant? Rent Size 950 850 1600 1450 1200 1085 1

Multiple Regression Analysis

The task is to provide evidence, for or against, common perceptions about property crime. Are crime rates higher in urban than rural areas? Does unemployment or education level contribute to property crime rates? How about public assistance? What other factors relate to property crimes? The file named Data File may help answer s

General Statistics questions

1. What is the variable used to predict the value of another called? A) Independent B) Dependent C) Correlation D) Determination 2. Based on the regression equation, we can A) predict the value of the dependent variable given a value of the independent variable. B) predict the value of the independent

Multiple Regression

Please see the attached 2 problems. Please provide a step by step solution and also use Excel to arrive at the answers. Thank you. Problem 1: The US Government has asked for your assistance in determining the acceptability of structural bolts provided by a supplier. The bolts must be 1.84 centimeters in diameter. You select

Understanding variables and parameters in a regression

To understand a regression equation we need to understand what the variables are and what the parameters are. The variables in this case are "Nut Yield" in California, "precipitation" based on annual rainfall data, and "acres" which refers to the number of acres planted. Next are the parameters. "a" is the intercept. It te

Statistics - Correlation & Regression

The owner of Maumee Ford-Mercury wants to study the relationship between the age of a car and its selling price. Listed below is a random sample of 12 used cars sold at Maumee Motors during the last year. Age (Years) SELLING PRICE ($000) 9 8.10 7

Multiple regression problem and analysis

4. Market Planning, Inc. a marketing research firm, has obtained prescription sales data for 20 independent pharmacies (see below). In this table, the following variables are included: Sales over the past year (in units of $1,000), Floor space (square feet), Percentage of floor space dedicated to the pharmacy (square feet), Numb

Correlation and Regression applied to a dataset of alcohol-related crash history

Please take the data I provide and do the computations and graphing for me, then explain the results to me so that I can write a paper and give a presentation on it. Here is my assignment: Prepare a 1,000 - 1,500 word paper applying Regression and Correlation to a personal or business application the student is familiar

Quantitative analysis

4-20 The following data give the selling price, square footage, number of bedrooms, and age of houses that have sold in a neighborhood in the last 6 months. Develop three regression models to predict the selling price based upon each of the other factors individually. Which of these is best?

Building multiple regression model

I need help answering these questions. Enclosed in the multiple regression model that the questions refer too and also the Table A & B that are referred to in question 2 & 3. This case involves the decision to locate a new store at one of two candidate sites. The decision will be based on estimates of sales potential. Pro

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 ef

Regression model

Interpret the following: (a) Y = a + BX; Y = 3.5 + .7X, where Y = likelihood of buying a new car and X = total family income. (b) Y = a + BX; Y = 3.5 - .4X, where Y = likelihood of buying tickets to a rock concert and X = age.

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

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

Calculation of Regression and Correlation Coefficient

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. Determine the equation of th

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

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