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Regression Analysis

In the Following Regression X = total assets

In the following regression X = toatl assets ($billions). Y = total revenue ($billions), and n = 64 large banks. (a) write the fitted regression. 9b) State the degrees of freedom fro a two tailed test for zero slope, and use Appendix D to find the critical value at a = .05. (c) What is your conclusion about the slope? (d) Interp

Multiple Regression for Vanguard Corp

The director of a marketing at Vanguard Corp believes that sales of the company's bright side laundry detergent (s) are related to Vanguard's own advertising expenditure (a), as well as the combined advertising expenditures of its three biggest rival detergents (r). The marketing director collects 36 weekly observations on S, A

Hypothesis Testing: ANOVA and Regression Coefficients

See the attached file. Predictor Coef StDev Constant -150 90 X1 2000 500 X2 -25 30 X3 5 5 X4 -300 100 X5 0.60 0.15 Source DF SS MS F Regression 5 1,500.00 Error 15 Total 20 2,000.0 a. Complete the ANOVA table. b. Conduct a global test of hypothesis, using the .05 si

Statistics - Regression Model .

Observations are taken on sales of a certain mountain bike in 30 sporting goods stores. The regression model was Y = total sales (thousands of dollars), X1 = display floor space (square meters), X2 = competitors' advertising expenditures (thousands of dollars), X3 = advertised price(dollars per unit). (a) Write the fitted re

Simple Regression Analyses

Prepare a report using Excel as your processing tool to process three simple regression analyses. 1. 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.


Look at the data below for the income levels and prices paid for cars for ten people: Annual Income Level Amount Spent on Car 38,000 10,000 40,000 14,000 117,000 37,000 17,000 2,500 23,000 6,000 79,000 18,000 33,000 4,000 66,000 5,000 15,000 1,000 52,000 5,00

Statistics - Fitted Regression for Vehicle ads

Below are fitted regressions based on used vehicle ads. Observed ranges of X are shown. The assumed regression model is AskingPrice = f (Vehicle Age). (a) Interpret the slopes. (b) Are the intercepts meaningful? Explain. (c) Assess the fit of each model. (d) Is a bivariate model adequate to explain vehicle prices? If not, what

Statistics - Find the Regression Equation

Statistics Find the regression equation, letting the first variable be the independent (x) variable. Find the indicated predicted values. Caution: When finding predicted values, be sure to follow the prediction procedure described in the section. Appendix B Data Set: Discarded Plastic and Household Size Refer to Data Set 1

Correlation and regression analysis

Residual Plot: Consider the data in the table below. A. Examine the data and identify the relationship between x & y. B. Find the linear correlation coefficient & use it to determine whether there appears to be a significant linear correlation between x & y. C. Construct a scatter plot. What does it suggest about the relatio

Statistics -Correlation Hypothesis and Regression Hypothesis

Please assist with a 5-step hypothesis test on the slope of a linear regression line. I have the scatter plot, line of best fit (including equation of the line). But I don't know how to test a hypothesis for the slope of a linear regression. also explain if there is a 5-step hypothesis test for the correlation coefficient by

Regression equation for predictions

Find the equation of the regression line for the given data. Use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown below. Calories, X 160 170 130 130 90 180 Sodium, Y 415

Regression analysis

Imagine you are a real estate investor presented with a regression analysis of home sales near one of your investment properties. Use Stat tools regression mod3l to determine: Which is a better predictor of selling price:appraised value, square footage, or number of bedrooms? A) How much value is added per $1000 OF APPR

Regression Analysis

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 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

Cost Drivers for the American Micro Devices

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 costs?is not accurate en

Description of Correlation Analysis

Task: Make a scatter diagram of the following scores: (a) describe in words the general pattern of correlation, if any; (b) figure the correlation coefficient; (c) figure whether the correlation is statistically significant (use the .05 significance level, two-tailed); (d) explain the logic of what you have done, (e)

Regression Analysis Significance in Statistics

Problem: Do Hispanics earn more than white individuals at a large company, for which lawsuit filed. Attached data include, 1. Employee ID, 2. Job title, 3. Ethnicity, 4. Yrs. Working. 1. Is pay different by ethnicity and if so are they statistically significant, and what is meaning of such. Consider some of the arguments t

Unit 5 Statistics Help...please

Hi, I need help with this assignment. I am using a different Dataset then what is in the solution library. My data set is 0903A.Xls.My school uses Turn it which is a similarity score and if it matches too high The assignment mentions a DATA SET 903A which i have provided - I have attached this information. Thank you and ple

Regression analysis problems - Bus Inc. sells widgets

Bus Inc. sells widgets. Sales dept says there is a positive linear relationship between the advertising expenditures and sales. Sales department recently analyzed the sales over 42 weeks. For each week in the sample, Bus Inc sales (SALES) and their advertising expenditures (ADVERT) were recorded. A simple regression analysis was

Calculate and interpret the correlation between variables.

3 pages Details: 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

Correlation and Regression.

Suppose r = 0. What is the slope (provide your answer both as a calculation and a description of what the slope of the regression line would look like)? What is the y-intercept (provide your answer as a calculation)? Why does your answer for the y-intercept make sense?

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

Forecasting for the Census Bureau

Problem 1 The U.S. Census Bureau publishes data on factory orders for all manufacturing, durable goods, and non-durable goods industries. Shown here are factory orders in the United States from 1987 through 1999 ($ billion). a) Use these data to develop forecasts for the years 1992 through 1999 using a 5-year moving average.

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