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Regression Analysis

Multiple Regression explanation

I am working to develop an equation for Y that is based on up to 10 different X variables. I am trying multiple regression. What I need to know is what tests I run to determine the suitability of the model? For example how do I determine if simple, linear regression is suitable or if I need to try a different, non-linear form?

Statistical Analysis of Diamond Data

O Perform some quick research (likely on the web) to describe color, quality, and certification of diamonds. o Respond to the following (based on the data in the Excel file) and support each with some reference to a statistical tool or graphical analysis. (1) If someone wanted a large but inexpensive diamond, what col

Statistics Questions

1) If the Z-value is used to test a null hypothesis that the population mean equals a given number, large positive and negative values of Z will lead to a rejection of H0. TRUE OR FALSE. 2) In a two-tailed hypothesis (large sample), test the test statistic is determined to be -2.5. The p-value for this test is _____________ 3)

Economics - Demand Problems/Calculations

Economics - Demand Problems/Calculations. See attached file for full problem description. 1. Assume you have to analyze the following data provided to you from the Accounting Department. a) From Column A and E in the demand schedule above, what is the price elasticity of demand when our price is between $1600 and $1450 per u

LP Model/Surplus & Artificial Variables/Integer

1. What are the assumptions and requirements for an LP model to be formulated and used? Under what conditions will an LP problem: be unbounded? be infeasible? have more than one optimal solution? 2. The administrator of a large hospital made the state, "I would like to use LP, but it's a technique that operates under co

Problems on the Spearman rank correlation coefficient, statistical decision theory, multiple regression, Chi -Square, time series analysis, nonparametric statistics, quality control, etc.

1. You are a corporate inspector for an organization with 10 manufacturing plants, and you are interested in determining how well each plant audit score correlates with injury experience. The individual plant audit scores and their injury frequency rates for the year, along with their respective rankings, are tabulated in the fo

Multiple regression analysis with the attached data

1. Can I perform a multiple regression analysis with the attached data that I've collected without changing that data or adding to it? Please explain why or why not to help me understand. 2. Can I perform a multiple regression analysis with the attached data that I've collected and additional data derived from that collectio

Regression Formula

I'm not sure of how to use the regression formula correctly to compute a simple regression equation y = mx + b for the data that I attached. What would the approximate number of housing starts be at the following interest rates: 8.5%, 4.5%, 3.7%, 2.3% If I were the owner of a business in the housing construction sect

Regression analysis of annual sales based on advertising expense

Reliable Furniture is a family business that has been selling to retail customers in the Chicago area for many years. They advertise extensively on radio and TV, emphasizing their low prices and easy credit terms. The owner would like to review the relationship between sales and the amount spent on advertising. Below is informat


Manatees are large, gentle sea creatures that live along the Florida coast. Many manatees are killed or injured by powerboats. Here are data on powerboat registrations (in thousands) and the number of manatees killed by boats in Florida in the years 1977 to 1987. (a) Which is the explanatory variable? Make a scatterplot of th

Predictions from Regression Equations

Use the following sets of data to calculate the coefficient of determination, the total variation, explained variation, and unexplained variation. x 6 2 3 1 4 y 12 6 9 1 10

Managerial Decision Making - Regression Analysis.

A consumer buying cooperative tested the effective heating area of 20 different electric space heaters with different wattages. Here are the results. Heater Wattage Area 1 1,500 205 2 750 70 3 1,500 199 4 1,250 151 5 1,250 181 6 1,250 217 7 1,000 94 8 2,000 298 9 1,000 135 10

Steps of analysis of CIA data using regression and correlation analysis.

Refer to the CIA data, which reports demographic and economic information on 46 countries. Let unemployment be the dependent variable and percent of the population over 65, life expectancy, and literacy be the independent variables. a. Determine the regression equation using a software package. Write out the regression equati

Independent Variables

See attached file for full problem description. Suppose that the sales manager of a company wishes to evaluate the performance of the company's sales representatives. Each sales representative is solely responsible for one sales territory, and the manager decides that it is reasonable to measure performance of a sales represe

Sensitivity Analysis/Bernoulli Process/Decision Trees

Our study group have various prospectives about the following questions. Please help us by answering based on your expertise. Many thanks. 1. Describe the use of sensitivity analysis and postoptimality analysis in analyzing the results. 2. Describe the characteristics of a Bernoulli process. How is a Bernoulli proce

Coefficient of determination and correlation

A sample of eight observations of variables x and y is shown below: [see attachment] The correlation of x and y is -0.991. 1) Calculate and interpret the coefficients of determination (R-squared xy and R-squared yx). 2) How is the value of the correlation coefficient affected in each of the following cases? a) each


5. For the following data: Case X Y 1 13 5 2 17 45 3 9 0 4 11 18 5 15 25 6 8 4 7 13 10 8 18 35 9 16 15 10 10 0 X-Bar = 13, SDx = 3.46; Y-Bar = 15.70, SDy = 15.28 a. Calculate slope a. b. Calculate y-intercept b. c. Write the regression equation including a and b below. Assume an unknown x. 6. Calculate

Prediction of SAT by regression approch

The correlation between IQ and the verbal SAT score among the seniors at GWB High School is .90; it is significant. The mean IQ is 100 with a standard deviation of 10. The mean SAT score is 500 with a standard deviation of 100. Predict SAT scores for seniors with the following IQs: 105,110,120

Simple Linear Regression

Simple Linear regression results: Dependant Variable : Stoppages Independent Variable : Temp Variability Stoppages = 5.740207 - 0.27559829 Temp Variability Sample Size: 16 R (correlation coefficient) - -0.04475 R-sq = 0.20022592 R-sq = 0.20022592 Estimate of Standard Deviation : 2.0759327 PARAMETER ESTIMATES: PARAM

Explaining the Multiple Regression Analysis

It is generally assumed that as world class runners speed up, their stride length increases. The average speed and stride length of world class runner was checked at 7 increments. You want to know if there is any relationship between speed and stride length. Do the following tasks and run a hypothesis test to see if there is any

Regression, ANOVA, chi square test and students t test

See attached file for full problem description. 1. A company has two different processes that make credit cards. Suspecting that machine B has a higher variability than machine A the manager orders a test to be run. The following data was collected: Machine A Machine B Sample size nA= 30 nB=40 Sample Standard Deviatio

Multiple Regression Analysis

My research is based on this topic below. The data is attached in the spreadsheet. This is a multiple regression analysis. I have attached a PDF file that explains the case and the spreadsheet version with all the data recorded from the PDF file. Pleas make sure you include all the graphs, plots and please use megastat software

Correlation Coefficient

A manager wishes to find out whether there is a relationship between the number of radio ads aired per week and the amount of sales of the product. # of Ads 2 5 8 8 10 12 Sales Y 2 4 7 6 9 10 Develop the estimated regression equation. Predict the amount of sales for 7 Ads per week Predict the amount of sales for 15

Statistical analysis case with regression data

Attached you will find an Excel file with two sets of data, and a Word Doc with explanation to the case at hand. This is a conclusions based case using regression analysis, variables, scatterplots etc. See attached files for a description of the case study and a full problem description. Report requirements: 1. Use

Business Statistics

Business Statistics See attached [same as priors] - Using PHSTAT - Send Excel + Paste into Word

Regression analysis: Unemployment problem

A study provided data on variables that may be related to the number of weeks a manufacturing worker has been jobless. The dependent variable in the study (weeks) was defined as the number of weeks a worker has been Jobless due to a layoff. The following independent variables were used in the study. Age, Educ, married, Head (

Calculating Sharpe's Ratio and Jensen's Alpha

Understanding how to measure between risk and return by calculating Sharpe's Ratio and Jensen's Alpha. See attached file for full problem description. I want you to consider the optimal way to combine the ranking of funds by returns and risk. Using the 10 years of data provided, you will calculate the Sharpe ratio for each