If the disturbance are not conditionally homoskedastic.....
A: What is the significance of the error term in the regression equation? B: What does zero correlation tell you? C: How would you use a histogram to chart residuals? What would this tell you? D: How do you identify outliers in your data? How do they impact your regression equation?
1. A radio disc jockey track of the number of request for songs by a certain artist and the time of day the request calls were made. The data is displayed. Request: 9 0 10 0 5 0 9 5 Time of day: 2p.m. 3p.m. 4p.m.
I have a simple question, I think, I just cant remember my stats classes: I need to know which tests to use for the analysis of the following data I have a graph with species of malaria contracted along the x-axis. The y-axis is patient frequency (ie number of patients who contracted that particular species). The patient popu
4.6 Air Conditioning Repairs. Richard's Heating and Cooling in Prescott, Arizona, charges $55 per hour plus a $30 service charge. Let x denote the number of hours required for a job and let y denote the total cost to customer. a) Obtain the equation that express y in terms of x b) Find b0 and b. c) Construct a table for the
Our analysis reviews faculty salaries to see if there is in fact a substantial salary difference based upon gender. We have collected data from 1,446 random institutions across the United States. We have obtained salary information for both men and women faculty members, separately, within public, private and church-related in
U.S. Virgin Islands is a popular tourist destination, particularly during winter months. Tourists come from all over the world. Majority of these tourists typically stay 3- 5 nights in hotels, and spend significant amount of money on a variety of activities including playing golf, scuba diving, snorkeling, and just enjoying th
A) What is the least square of y on x and interpret the slope of the fitted regression. b) Find and interpret the coefficient of determination for the fitted regression c) What is the 95% confidence interval for the slope of the population line. d) Find the point forcast of the rate of return on the stock of Ill. Power next month,if the rate of return on the market index is expected to be 0.04 e) Test at the 1% level against a two - sided alternative the null hypothesis that the intercept of the population regression line is zero and interpret your findings.
A) What is the least square of y on x and interpret the slope of the fitted regression b) Find and interpret the coefficient of determination for the fitted regression c) What is the 95% confidence interval for the slope of the population line. d) Find the point forcast of the rate of return on the stock of Ill. Power next mo
Problem: We are using a linear regression model (time series) to predict sales of our "WW" brand. Historically, sales of this product for the period 1982 to date (1982 through summer 2003; assume 1982 was year one) have been approximated by the following data (in thousdands of units): Y = 3.984X + 2.994 Sy = .677 r2 (R s
1. Given the number of contacts and sales made by a company over two months, compare the numbers each month and determine the regression equation and the estimated sales if 40 contacts are made. Also, determine the standard of error estimate ... *(Please see attachment for complete problem and problem #2)
Use the formulas for a regression line to solve the following: The following are times in minutes between the duration of an eruption and the length of time before the next eruption at Yellowstone. Predict the interval for the next eruption if the duration of the last one was 2.82 minutes; explain conclusion - Answer is 67.7 but
State the goal of two statistical methods to formulate hypotheses.
The following data has been collected for two variables, X and Y. X Y 5 30 10 41 15 53 20 62 25 67 A simple linear regression model has been constructed using the data in the table and is being used to predict values for the variably Y Of 3, 7, 18 and 35, how do I determine which for variable X would lead to
I need to figure out the regression equation, the value of Y when X is 7, the slope of the regression equation, the Y-intercept of the regression equation, the coefficient of correlation, and the coefficient of determination.
Applicants for a particular job that involves extensive travel in Spanish speaking countries, must take a proficiency test in Spanish. The sample data below was obtained in a study of the relationship between the numbers of years applicants have studies Spanish and their score on the test. # of Years (χ) 3 4 4 2 5 3
Manatees are large sea creatures that live in the shallow water alone the coast of Florida. Many manatees are injured or killed each year by powerboats. Here are the data on manatees killed and powerboat registration (in thousands of boats) in Florida for the period 1984 to 1990. Year Powerboats Manatees Killed γ
What is realtionship between the amt spent per wk on food and the size of the family? Do larger families spend more on food? A sample of 10 families in the chicago are revealed the following figures for family size and the amount spent on food per week. Chart attached
Following is a portion of the Excel output for a regression analysis relating maintenance expense (dollars per month) to usage (hours per week) for a particular brand of computer terminal. (see table in attachment) a. Write the estimated regression equation. b. Use a t test to determine whether monthly maintenance expens
The typical household income and typical home price for a sample of 18 cities follows (see attachment - data are in thousands of dollars). PART A: a. Use these data to develop an estimated regression equation that could be used to estimate the typical home price for a city given the typical household income. b. Compute r2 [
Develop a scatter diagram for this data. Develop the estimated regression equation by computing the values of b (0) and b (1). Use the estimated regression to predict the value of y when x = 4
Given are five observations for two variables x and y. (see attached for details) x y 1 3 2 7 3 5 4 11 5 14 A. Develop a scatter diagram for this data. B. What does the scatter diagram in part A indicate about the relationship between the two variables? C. Try to aproximate the relationship between x and y by drawin
Results of multiple regression for Defect Summary measures Multiple R 0.9383 R-Square 0.8803 Adj R-Square 0.8612 StErr of Est 7.2326 ANOVA Table Source df SS MS F p-value Explained 4 9621.5292 2405.3823 45.9828 0.0000 Unexplained 25 1307.7628 52.3105 Regre
This problem is identical to problem posting 22208 and I assume should be removed from the library.
I'm not certain what is being asked and I need help on where to start.
Assume a significance level of 5% 1. Everybody seems to disagree about why so many parts have to be fixed or thrown away after they are produced. Some say that it's the temperature of the production process, which needs to be held constant (within a reasonable range). Others claim that it's clearly the density of the product
5. A product manager at Proctor & Gamble seeks to determine whether her company should market a new brand of toothpaste, called Tim's of Massachusetts. If the new brand succeeds, then P&G estimates that it would earn $2,000,000 in NPV. If Tim's fails, then the company expects to lose approximately $800,000 in NPV. If P&G decides
I need help interpreting what is being asked and how to solve problems.
See attachment it is in jpeg format.Please show how you devrived at solutions.
See Jpeg attachments. One attachment is a printout from minitab, the other attachment is the questions.
Regression Models: a) The owner has an 82-year-old building with 5 apartments but no parking spots. The lot is 7500 square feet and the gross building area is 9542 square feet. What sales price is predicted by MODEL I ? b) State why you know that all three models are significant for predicting the sales price. Since this is the case, why would a statistician prefer MODEL III to MODEL II ? c) Fill the missing numbers in the analysis-of-variance table for MODEL III. d) From MODEL II to MODEL III the proportion of explained variation in sales price reduces from 98% to 97.7%. Give precisely the reason you know that this is not a significant reduction in R2. e) Use MODEL III to answer this part. On the average, what does an extra apartment add to the sales price? Give a 95% confidence interval for the marginal contribution of the 'apts' variable.
1. The owner of an apartment building in Eurelia believes that her property tax bill is too high because of an overassessment of the property value by the city tax assessor. The owner has hired an independent real-estate appraiser to investigate the appropriateness of the city assessment. The appraiser used regression analysis
Please see attached there are 3 problems. I have added the instructions for #3