Explore BrainMass

Regression Analysis

Completing Regression Analysis Questions

Using the data from the excel spreadsheet I have attached, I need assistance answering the following questions: - When performing a regression analysis, it is important to first identify your independent/predictor variable versus your dependent/response variable, or simply put, your x versus y variables. How do you decide which

Statistics: Box Office Gross and Video Units Sold

Consider the data below, where data are available for 30 movies that indicate the box office gross (in millions of dollars) and the number of units sold (in thousands) of home videos. Use EXCEL/PHStat to produce the print-out to answer the problems 5 to 9. 1. Find the SSE: a) 171499 b) 64154 c) 235654 2. Compute t

Regression Equation Problems

In a regression analysis involving 27 observations, the following estimated regression equation was developed. y = 25.2 + 5.5x1 For this estimated regression equation SST = 1550 and SSE = 520 a. At a = .05, test whether x1 is significant. Suppose that variables x2 and x3 are added to the model and the following regression

Contingecy Table and Logistic Regression

Based on the attached contingency table and the logistic regression determine whether there is a significant association between treatment (tx) and current anxiety disorder (anxiety) by interpreting the logistic regression results. State the statistical findings from the logistic regression that support your conclusion. Inclu

T Test, Linear Equations and linear regression

See the attached file. A statistics student used a computer program to test the null hypothesis H_0: p = .5 against the one-tailed alternative, H_a: p > .5. A sample of 500 observations are input into SPSS, which returns the following results: z = .44, two-tailed p-value = .33. a) The student concludes, based on the p-valu

Regression Table

Please view the attached data table and answer the following: 1) The value of R-Square is? 2) The observed or computed F-value is? 3) The estimate of the coefficient b1 is? 4) What is the P-Value?

Using MINITAB, Perform the Regression and Correlation Analysis

Using MINITAB perform the regression and correlation analysis for the data on CREDIT BALANCE (Y) and SIZE (X) by answering the following. 1. Generate a scatterplot for CREDIT BALANCE vs. SIZE, including the graph of the "best fit" line. Interpret. 2. Determine the equation of the "best fit" line, which describes the relationsh

Multiple Regression Statistics Question

A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures. y = 25 + 10x1 + 8x2 Where x1 = inventory investment ($1000s) X2 = advertising expenditures ($1000s) Y = sales ($1000s) a. Estimated sales resulting from a $15,000 investment in

Multiple Regression: Forecasting the Price of Single Family Homes

Purpose of the Project: Forecasting the price of single family homes in the Bowie area, using multiple regression model. Regression Variables: Write the linear multiple regression equation clearly identifying the independent and. dependent variables. HMPRICE= home price-dependent variable NUBEBRM= Number of Bedroom LI

Statistics Problem Set: Multiple Regression Model

14.2 Develop a multiple regression model of the form y = b0 + b^x1E. Using the following data to predict y from x. From a scatter plot and Tukey's ladder of transformation, explore ways to recode the data and develop an alternative regression model. Compare the results. 14.

Statistics Problem Set: U.S. Energy Information

See the attachment. 14.6 What follows is Excel out put from a regression model to predict y using x1, x2, x1^2, x2^2, and the interaction term, x1,x2. Comment on the overall strength of the model and the significance of each predictor. The data follow the Excel output. Develop a regression model with the same independent vari

Multiple Regression Analysis: Average Miles Per Gallon

How does car mileage vary for various car models? Variation in gasoline mileage among makes and models of automobiles is influenced substantially be the weight and horsepower of the vehicle. The date you will analyze is provided by the U.S. Environmental Protection Agency. The variables are: VOL: Cubic feet of cab space H

Minitab Output for a Multiple Regression Analysis

13.6 Jesen, Solberg, and Zorn investigated the relationship of insider ownership, debt, and dividend policies in companies. One of their findings was that firms with high insider ownership choose lower levels of both debt and dividends. Shown here is a sample of data of these three variables for 11 different industries. Use the

Linear Regression and R-Squared Analysis

1. A random sample of size 36 from a normal population yields mean X-bar = 32.8 and standard deviation s = 4.51. Construct a 95 percent confidence interval for μ. (Ch9) 2. Test at α = 0.05, the hypotheses H0: µ= 0.33 versus HA: µ < 0.33 with p = 0.23 and n=100 (Ch10) (show the calculated and critical values of the test stat

Forecasting a time series

In forecasting a monthly time series over a five-year period from January 2005 to December 2009, the exponential trend forecasting equation for January is log Yi = 2.0 + 0.01 Xi + 0.10 (January) Take the anti-log of the appropriate coefficient from this equation and interpret the: (a) Y intercept, b0 (b) Monthly compound

Least Squares Regression Line and Correlation

Refer to the list below to answer the questions. X 0 -1 1 1 2 y 2 -2 5 4 6 1. Find an equation of the least squares regression line. Please show your work. 2. Is there a linear correlation between "x" and "y" at the 0.01 significance level? Please just

Using Regression Equation

MONTH NUMBER OF MOVES NUMBER OF LBS. MATERIAL HANDLING COST January $100 6,000 $2,000 February $125 15,000 $3,090 March $175 7,800

Using a Regression Equation

Question: Find (a) explained variation, (b) unexplained variation, (c) total variation, (d) coefficient of determination, (e) standard error of estimate Se. In each case, there is sufficient evidence to support a claim of a linear correlation so that it is reasonable to use the regression equation when making predictions. Sce

Finding a regression equation

In each case, find the regression equation, letting the first variable be the predictor (x) variable. Find the indicated predicted value by following the prediction procedure. Height of Presidents and Runners-up Find the best predicted heights of runner-up Goldwater, given that the height of the winning presidential candidat

Regression Analysis using Standby Hours

Question: The business problem facing the director of broadcasting operations for a television station was the issue of standby hours (i.e hours in which unionized graphic artists at the station are paid but are not actually involved in any activity) and what factors were related to standby hours. The study included the followin

Pearson Correlation Analysis

Interpret and summarize the Pearson r, coefficient of determination, and p-value from the Pearson correlation analysis attached. Describe the direction and strength of the relationship, and whether you think this is a clinically significant relationship and why. For this question, work on the premise that the assumptions of the

Standardized Regression Coefficients

See the attached file. Describe the direction of the relationship between AGE and CDRS based on the regression coefficients. Be sure to explain how the standardized (beta) regression coefficients for AGE is used to determine the direction and magnitude of the association between AGE and CDRS, and how it may be used to determine

Multiple Regression: Predicting CDRS Scores

See the attached file. Examine the multiple regression results in the attached document. Determine whether RADS significantly predicts CDRS scores after adjusting for the effects of the other predictors in the model. Determine whether AGE significantly predicts CDRS scores after adjusting for the effects of the other predicto

Bivariate Regression: Identify the Unstandardized Regression Coefficient

Using the bivariate regression table attached, determine what the predicted CDRS score would be if the adolescent's RADS score was 70. Provide the (a) bivariate regression equation; (b) identify the intercept and unstandardized regression coefficient, and (c) show how you calculated the predicted Y. - Assume RADS is an X (pre

Pearson Correlation and Regression Analysis

1. Compute the Pearson correlation for the following data. X Y 7 3 3 1 6 5 4 4 5 2 2. Find the regression equation for predicting X from Y for the following set of scores. X Y 0 9 1 7 2 11

Analyzing forecasting data

Stanly Smith is in the market for a used car so that he can get to Cascade College to take advanced financial accounting. Based on eye appeal only, he has narrowed his choice to the Smogger, an import from Lapland. The Community Times want ads section lists the following used Smoggers for sale: Smogger Age Price (Years) ($1

ANOVA and Regression Analysis Example

1. Describe what an ANOVA test does. When would you use it and give an example. 2. Regression analysis works with the basic formula of a line, which is Y = mX + b. We can use it to look at causation. Think about the Lemonade Stand Game. Give an example of how you might use Regression Analysis, and include how you would "s

Sign of the slope of the regression line

Answer the following: - If the correlation coefficient is 0.41, what is the sign of the slope of the regression line? - As the correlation coefficient increases from 0.85 to 0.88, do the points of the scatter plot move toward the regression line, or away from it?

Correlation Coefficients and Regressions

Use the following information to answer questions 1-3: Row 1 | 5 6 5 8 5 3 9 11 10 9 Row 2 | -5.0 -4.0 -3.5 -4.1 -2.4 -2.0 -5.0 -7.2 -5.6 -6.4 1. Using row 1 of the table above for the x-values and row 2 for the y-values, find the value of the correlation coefficient, r. 2. Using row 2 of the table above for the x-values an