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Regression Analysis

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

MBA question on crop yields. How can I use regression analysis to test theories of crop yields.

For my project I plan to pull information from the State of California, Department of Agriculture on the nut crop yields. They have historical information on prior years yields. I also plan to pull a couple of other variables that impact yields like rainfall and acres planted. Using this historical information I want to be able

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

Time Series & Forecasting

Listed below is the net sales in \$ million for Home Depot, Inc. and its subsidiaries from 1993 to 2002. Year Code Net Sales 1993 1 9,239 1994 2 12,477 1995 3 15,470 1996 4 19,535 1997 5 24,156 1998 6 30,219 1999 7 38,434 2000 8 45,738 2001 9 53,553 2002 10 58,247 C. Compute a 3-year moving average.[use MS Excel

The Solution to a Regression Model

Problem Data for a sample of houses sold recently in the suburb of a large metropolis are given below. Assuming that selling price is dependent on area of the house complete the following questions. Area of House (hundreds of square feet) Selling Price (thousands of dollars) 20 250 19 220 27 350 28 390 30 320 15 200

Hypothesis Test

What data set will your team use for the Week 5 paper? Baseball 2005 What is your research question? Is there a significant linear relationship between the size of Stadium attendance and the Stadium's team's annual salary? 0.05 level of significance. What is you numeric and verbal hypothesis statement? - H0: ß1 = 0 (t

Quantitative Analysis 4-12

See attached file.

Using Excel as your processing tool

Using Excel as your processing tool, work through three simple regression analyses. (USE ATTACHED DATASET EXCEL WORKSHEET) First run a regression analysis using the BENEFITS column of all data points in the AIU data set as the independent variable and the INTRINSIC job satisfaction column of all data points in the AIU data s

Statistics

Using Excel as your processing tool, work through three simple regression analyses. 1. First run a regression analysis using the BENEFITS column of all data points in the AIU data set as the independent variable and the INTRINSIC job satisfaction column of all data points in the AIU data set as the dependent variable. Creat

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?

Regression - Steps to fit a line using Least Squares

Can someone explain the steps to fit a line using least squares relying on technology for the computationally intense learning for middle grades students and the same for high school students which would be led through the technology, the hand computation, or both.

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

Provide a range of illustrative graphs regarding the provided data comparing various 'comtype' variables vs. sales. Also provide a regression analysis of the variables.

1.Open the file pamsue.xls. First, move the column for sales so that it is the rightmost column (it is now to the right of comtype). If the old sales column remains but appears empty, delete that column. 2.Obtain a scatterplot of the sales on the vertical axis against comtype on the horizontal axis. This will give you a go

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

A manager would like to know the relationship between the billable hours spent on a job and the total cost of the job including materials. The file jobs.xls contains the data and is attached below. Summarize the relationship. Need help on this problem.

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

What variables in the data affect pricing?

Using numerical data from the attached data set, I wish to use the research question "What variables in the data affect pricing?" I would like some assistance in formulating a hypothesis statement which can be tested with linear regression analysis on the collected data. I also wish to perform a regression hypothesis test on

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

Probability Problems of Correlation and Regression Lines

A number X is chosen uniformly at random from the numbers 1,2,3,4. After that another number Y is chosen uniformly at random among those at least as large as X. Compute E[X], E[Y], Var(X), Var(Y), Cov(X,Y), the correlation coefficient of X,Y and the regression lines.

Statistics - Using Precision Tree

DataPro is a small but rapidly growing firm that provides electronic data-processing services to commercial firms, hospitals, and other organizations. For each of the past 12 months, DataPro has tracked the number of contracts sold, the average contract price, advertising expenditures, and personal selling expenditures. These da

Regression equation: Example problem

The following data represent the number of weed-eaters sold per month at a local garden shop and their prices Price x \$34 36 32 35 30 38 40 Units sold y 3 4 6 5 9 2 1 a. Develop the estimated regression equation. b. PRedict the amount of sales for a co

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

Using Excel -three simple regression analyses.

Using Excel as your processing tool, work through three simple regression analyses. First run a regression analysis using the BENEFITS column of all data points in the AIU data set as the independent variable and the INTRINSIC job satisfaction column of all data points in the AIU data set as the dependent variable. Create a

Regression using the Benefit Column

First run a regression analysis using the BENEFITS column of all data points in the data set as the independent variable and the INTRINSIC job satisfaction column of all data points in the data set as the dependent variable. Create a graph with the trendline displayed. What is the least squares regression line equation? What are

Ratio to moving average/seasonal index

An analyst wants to use the ratio-to-moving average method to forecast a company's sales for the next few months. Beginning in March of , the analyst collects the following sales data (in millions of dollars). Estimate the seasonal index associated with July. Round your answer to at least three decimal places.