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Regression Analysis

Sample Correlation, Intercepts, and the Coefficient of Determination

An analyst believe that the only important determinant of banks' return on assets (Y) is the ratio of loans to deposits (X). For a random sample of banks the sample regression line: Yhat = 0.97 + 0.57X 1.72 2.04 T statistics was obtained with the coefficient of determination 0.720. a. Find the sample correlat

Basic Linear Regression Model

Given Data: X Y 11 24 12 25 16 33 13 25 12 19 15 24 16 25 18 35 Use the given data (above) to answer the following questions: 1. Determine the regression equation relating X and Y? Use the formula to determine the value of and hence find . 2. State the models being compared to determine if the

Forecasting: The following table shows the past two years of quarterly sales information. Assume that there are both trend and seasonal factors and that the seasonal cycle is one year. Use time series decomposition to forecast quarterly sales for the next year.

The following table shows the past two years of quarterly sales information. Assume that there are both trend and seasonal factors and that the seasonal cycle is one year. Use time series decomposition to forecast quarterly sales for the next year. Quarter Sales Quarter Sales 1 160 5 215

Literacy and GDP to Life Expectancy

Do literacy and GDP explain life expectancy? Would you include any other independent variables? Explain the attached regression table and ANOVA table as a whole in detail as it correlates to the variables.

Beta Technologies, Inc. Employee Salary Structure: regression analysis

I need help with estimate simple linear regression model for the management of Beta Technologies, Inc. is trying to determine the variable that best explains the variation of employee salaries using a simple of 52 full time employees in the attached file. I need to identify which of the following has the strongest linear relatio

Consider the following data on 20 chemical reactions

I need to show a scatter diagram using the molecular weight as my x-axis. Consider the following data on 20 chemical reactions, with Y = chromatographic retention time (seconds) and X = molecular weight (gm/mole). (a) Make a scatter plot. (b) Use Excel to fit the regression, with fitted equation and R2. (c) In your own words,

Adding Two Sixth Order Polynomial Regression Equations

Please see the attached file. I have 2 data sets that determine a y-value based on known x-values (the x-values are given as temp degrees C) ---- each of those actual line graphs have been fitted with an approximate "best fit" line determined by Excel with 2 separate 6th order line equations. Our homework asks us to add th

Regression

Ho: Total home cost increases with additional square feet Ha: Total home cost does not increase with additional square feet Define bivariate regression, discuss fitted regression and using regression for prediction purposes. Please see attached data and help me to understand what each section means.

Regression

Is this regression significant? How do you know? Please see the attached file.

Regression Questions

Please see the attached file for complete questions. 1. The following results were obtained as part of a simple linear regression analysis. We wish to test Ho: β = 0. The computed value of the test statistics is ________ 2. The following results were obtained as part of a simple linear regression analysis. For

Regression analysis was applied between demand for a product

Regression analysis was applied between demand for a product (Y) and the price of the product (X), and the following estimated regression equation was obtained. Y = 130 - 20 X Based on the above estimated regression equation, if the price is increased by 2 units, then demand is expected to decrease by 90 units i

Scatterplot and Trendline

13. The following data are prices for custom homes comparing square feet (given in hundreds) and price (in thousands). Square Feet Price 26 259 27 274 32 315 29 296 29 325 34 380 32 359 40 523 22 215

Regression Model Relating

A regression model relating x, number of sales persons at a branch office, to y, annual sales at the office ($1000s), has been developed. The computer output from a regression analysis of the data follows. The regression equation is Y = 80.0 + 50.0X Predictor Coef Stdev t-ratio Constant 80.0 11.333 7.

Model to Predict the Assessed Value of Houses

Please see the attached file. You want to develop a model to predict the assessed value of houses, based on heating area. A sample of 15 single-family houses is selected in a city. The assessed value (in thousand of dollars) and the heating area of the houses (in thousands of square feet) are recorded, with the following res

Multiple regression analysis and hypothesis testing problems

1. Mr. James McWhinney, president of Daniel-James Financial Services, believes there is a relationship between the number of client contacts and the dollar amount of sales. To document this assertion, Mr. McWhinney gathered the following sample information. The X column indi-cates the number of client contacts last month, and th

Multiple Regression for DJIA

Consider the following regression model: ? D = percent change in DJIA (Dow Jones Ind. Avg.); ? O = per barrel price of oil; ? I = interest rates (in real number percentages: 6%, etc); ? E = corporate earnings growth rate; ? G = GDP growth rate. ? R2 = 0.8500 ? F = 24 ? F(Se) = 1.0 ? D = 2.0 - 3.0I + 1.5E - 1

You are the general marketing manager of Ford Motor company.

You are the general marketing manager of Ford Motor company. The CEO of the company asked you to assess the viability of producing alternative fuel automobiles (ex, ethanol). What types of forecasting techniques would you use to forecast sales? Should you determine that regression analysis may be beneficial in addressing this qu

Step by step method for regression analysis is discussed here. Regression coefficients, coefficient of determination, scatter diagram and significance of regression model are explained in the solution.

3. Bi-lo Appliance Stores has outlets in several large metropolitan areas. The general sales manager plans to air a commercial for a digital camera on selected local TV stations prior to a sale starting on Saturday and ending Sunday. She plans to get the information for Saturday-Sunday digital camera sales at the various outlets

Tree diagram: A. Perform a decision tree analysis of Steeley Associates' decision situation using expected value, and indicate the appropriate decision with these criteria. B. Indicate the decision you would make, and explain your reasons.

Case Problem #2 Steeley Associates, Inc. a property development firm, property development firm purchased an old house near the town square in Concord Falls, where State University is located. The old house was built in the mid-1800s, and Steeley Associates restored it. For almost a decade, Steeley has leased it to the univer

Scatterplot and regression

Please see attachment! Use the data from Exercise #12.3 below. (a) Plot a scatter diagram, (b) Show the equation on the plot using the trendline option of Excel, (c) State the value of the slope, and (d) State the value of the intercept. Use the data from Exercise #14.1 (see below) and (a) Plot a scatter dia

Regression analysis between work fatalities and unemployment

A highway employee performed a regression analysis of the relationship between the number of construction work-zone fatalities and the number of unemployed people in a state. The regression equation is Fatalities _ 12.7 _ 0.000114 (Unemp). Some additional output is: Predictor Coef SE Coef T P Constant 12.726 8.115 1.57 0.134

Statistics Questions

Please see the attached file. 15.2 Teenagers make up a large percentage of the market for clothing. Below are data on running shoe ownership in four world regions (excluding China). Research question: At α = .01, does this sample show that teenage running shoe ownership depends on world region? (See J. Paul Peter and Jer

Multiple regression analysis problems

3. The director of marketing at Reeves Wholesale Products is studying the monthly sales. Three independent variables were selected as estimators of sales: regional population, per-capita income and regional unemployment rate. The regression equation was computed to be (in pounds). Y' = 64,100 + 0.394X1 + 9.6X2 + 11,600X3

Bingo Hamburger Co has a chain of 12 stores in a large city.

Bingo Hamburger Co has a chain of 12 stores in a large city. Sales figures and profits for the stores are given in the following table. Obtain a regression line for the data & predict profit for a store assuming sales of $10 million. X Y SALES PROFITS $7 $.15 2 .10