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    Regression Analysis

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    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

    Multiple regression: Antique collector

    An antique collector believes that the price received for a particular item increases with its age and with the number of bidders. The attached file contains data on these three variables for 32 recently auctioned comparable items. a) Formulate and estimate a multiple regression model using the given data. Interpret each of t

    Statistical Analysis for a Regression Equation

    In the following regression, X = monthly maintenance spending (dollars), Y = monthly machine downtime (hours), and n = 15 copy machines. Please view the attached file for the required data. (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

    Regression Equation

    Compute the intercept of the regression line for the data below. X values -5 1 4 Y values 7 6 -2 A) 3.46 B) 3.67 C) 7.06 D) -1.55

    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

    Linear Regression Analysis for Hypothesis Tests

    Please perform a 5 step Regression hypothesis test on the baseball data attached. Graph(s) need to be included with the interpretation of the results. Please provide as much detail as possible. The hypothesis statement is: H0:There is no relationship between salary and number of wins H1: There is a relationship betwe

    Trend Analysis for U. S. General Aviation Shipments

    14.16 (a) Plot the data on U.S. general aviation shipments. (b) Describe the pattern and discuss possible causes. (c) Would a fitted trend be helpful? Explain. (d) Make a similar graph for 1992-2003 only. Would a fitted trend be helpful in making a prediction for 2004? (e) Fit a trend model of your choice to the 1992-

    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

    Quantitative Methods - Pilot Farm Project

    See the attached file. Pilot Farm Project Probability Weather Peas Corn Tobacco Beets 0.3 Dry 20 15 30 40 0.5 Moderate 35 20 25 40 0.2 Damp 40 30 25 40 Net Income $1.00 $1.50 $1.00 $0.50 per bushel a. Create a treeplan for the project b. What is the expected outcome? c. If the weather

    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 and Correlation

    Given your newfound knowledge about Regression and Correlation, apply it now to the real world and give me an example using my work experience; I work as an enrollment counselor registration students. I register anywhere from 5 to 10 students a month into associates programs. In addition, I have about 4 hours talk time a day.

    Correlation and regression

    In your own words, tell me what is the major difference between correlation and regression. There are a couple of differences, but one really stands out however, there are some concepts which could use clarification.

    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

    What are the requirements that must be met for a regression analysis? What happens if these requirements are violated? Why is analysis of residuals important? Examples would be great.

    Correlation and Regression Analysis for Cigarettes

    Below is a section of output which used data collected on different brands of cigarettes. Past studies have shown that increases in the amount of Nicotine content of a cigarette are accompanied by an increase in the amount of Carbon. Please see the attached file.

    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

    Regression

    Please see the attached file. Don't use Excel.

    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

    Sample regression coefficients

    Find the following: (a) Compute the sample regression coefficients bo and b1. (b) Compute the estimated variance of the regression. (c) Compute the standard error of the regression. (d) Compute the estimated variance of b1. (e) Compute the standard error of b1. Year y = book value per share x = earning per share 1980

    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.

    Regression

    The manager of the purchasing department of a large banking organization would like to develop a model to predict the amount of the time it takes to process invoices. Data are collected from a sample of 30 days, and the number of invoices processed and completion time, in hours,is stored in the file INVOICE.xls(see attachment).