A. Determine the standard error of estimate. B. Suppose a large sample is selected (instead of just 10). About 95 percent of the predictions regarding sales would occur between what two values? Exercise 14: Number of Sales Number of Sales Contacts, ($ thousands),
Question One. A researcher is interested in determining the effect of after-school programs on adolescent delinquency. He asks a small sample of students how many activities they participate in and he asks how many delinquent acts they have committed since the school year has begun. His data are below. Calculate the linear r
The following data come from statehelthfacts.org. The states were chosen somewhat randomly by me. State Percentage who smoke Cancer incidence per 100,000 (age-adjusted) Kentucky 27.4% 498.2 Pennsylvania 22.6%
With the information provided above please answer the followin questions: 1. Do the data suggest that size is useful as a predictor if price for custom homes in the Equestrain Estates? Perform the required hypothesis at the 0.01 level of significance. 2. a. Find a 99% confidence interval for the slope of the population regression line that relates price to size for custom homes in the Equestraion Estates. b. Interpret your answer to part (a). 3. a. Determine a point estimate for the mean price of all 2800-sq-ft Equestrain Estates home. b. Find 99% confidence interval for the mean price of all 2800-sq-ft Equestrain Estate. c. Find the predicted price of a 2800-sq-ft Equestrain Estate home. d. Determine a 99% prediction interval for the price of a 2800-sq-ft Equestrain Estate home. 4. At the 0.5% significance level, do the data provide sufficiant evidence to conclude that, for custom homes in the Equestrain Estates, size and price are positively linearly correlated?
Hanna Properties specializes in custom-home resales in the Equestrian Estates, an exclusive subdivision in Phoenix, Arizona. A random sample of nine custom homes currently listed for sale provided the following information on size and price. Here, x denotes size, in hundreds of square feet, rounded to the nearest hundred, and y
(See attached file for full problem description) An economist is interested to see how consumption for an economy (in billions) is influenced by gross domestic product (billions) and aggregate price (consumer price index). The Microsoft Excel output of this regression is partially reproduced below. SUMMARY OUTPUT Regre
Multiple choice question from regression analysis, analysis of variance, correlation and scatter diagram.
Choose the best answer. Highlight the cell of the correct answer using the yellow fill color. [like this] 1 A bar soap manufacturer is conducting an experiment to determine how people react to 3 different brand names. Each brand name represents a(n) ___________ of the experimental
Theory of regression: How does regression relate to linear algebra? Regression terms and symbols: What is the difference between strong negative and strong positive? Practical examples of regression analysis: When would you use regression correlation at a place of employment, or in education, or in politics? Interpre
Sales date for two years are as follows. Data are aggregated with two months of sales in each period. (see chart in attached file) a. Plot the data b. Fit a simple linear regression model to the sales data. c. Using the results from parts a and b, prepare a forecast for the next year.
Determine the values for S o and g for continuous compounding. (See attached file for full problem description)
The following data about share prices for companies of different sizes is given: Size X Price Share Y 1 9 10.8 2 94.4 11.3 3 27.3 11.2 4 179.2 11.1 5 71.9 11.1 6 97.9 11.2 7 93.5 11 8 70 10.7 9 160.7 11.3 10 96.5 10.6 11 83 10.5 12 23.5 10.3 13 58.7 10.7 14 93.8 11 15 34.4 10.8 a. Calculate the regressio
The data below record, for a sample of 10 firms, the number of staff employed in Research and Development (X), and annual profits in millions of pounds (Y). X: [0,16,10,1,5,7,11,13,9,4] Y: [12,60,30,11,15,18,32,45,25,14] (a) Perform a linear regression of profits on R&D staff, and hence predict (giving confidence interval
Linear Regression and Correlation Mr. William Profit is studying companies going public for the first time. He is particularly interested in the relationship between the size of the offering and the price per share. A sample of 15 companies that recently went public revealed the following information. (see the attached c
A study of average hourly earnings in manufacturing is made. The results are: Year Earnings 1976 5.22 1977 5.68 1978 6.17 1979 6.7 1980 7.27 1981 7.99 1982 8.49 1983 8.83 1984 9.23 a. Using the least squares coded method, determine the equation for the straight line going through the
In fitting a least squares line to n=15 data points, the following quantities were computed: SSxx=55, SSyy=198, SSxy=-88, x-bar=1.3, and y-bar=35. a.) Find the least squares line. b.) Describe the graph of the least squares line. c.) Calculate SSE d.) Calculate s^2.
As a supervisor of a production department, you must decide the daily production totals of a certain product that has 2 models, the deluxe and the special. The profit on the deluxe model is $12 per unit and the profit on the special model is $10 per unit. Each model goes through two phases in the production process, and th
Answer each question in order. Write the number of the question and answer all parts thoroughly. Use complete sentences and show all required work. Project for Unit 1 Infant Mortality Data - Linear Regression Lines Show All Work The following table shows the mortality rates (in deaths per 1000 live births) for male
A. How is correlation analysis used in a business decision? b. How can correlation analysis be misused to explain cause and effect relationship? c. How is coefficient of determination used to make decisions? d. What is the standard error of estimate? Describe with an example. e. What are the coefficients of the linea
A linear regression between Y and X produced the following equation for the least squares line: Y hat = 2.15 - 3.2x Which of the following statements concerning this relationship is true? a. For every one-unit increase in X, Y increases 3.2 units. b. For every one-unit increase in Y, X decreases 3.2 units. c. For e
This solution answers two questions about a given linear regression model along with detailed explanations.
Please use Excel when necessary: Management has collected data on the size of five work groups(X) and the number of complaints per month (Y) received by the organization from each group. A regression was run using as the independent variable the size of the work group(number of employees in the work group) to predict the numb
Problem # 10 You are the manager of a firm that sells a leading brand of alkaline batteries. The accompanying Excel file contains data on the demand for your product. Specifically, the file contains data on the natural logarithm of your quantity sold, price, and the average income of consumers in various regions around the worl
Linear Regression (example problem) Boeing and McDonnell Douglas from the United States, and Airbus Industrie, the European consortium, dominate the global aerospace industry. During the early 1990's, the end of the cold war with the Soviet Union led to a dramatic downshifting in orders for military related purchases at the
A movie studio wishes to determine the relationship between the revenue from the rental of comedies on DVD and videotape and the revenue generated from the theatrical release of such movies. The studio has bivariate data from a sample of comedies released over the past five years. These data give the revenue from theatrical re
Need to know how to solve these questions to Inferences in regression and correlation analysis chapter.
Sporty Inc., a regional chain of sporting goods stores, wants to investigate why some of their stores in university towns have higher sales than other stores. Accordingly, they randomly sampled stores nationwide and collected information on yearly sales ($1000s), yearly advertising expenditures ($1000s), number of students at t
The regression equation is number of invoices per month = 138 + 0.000087 amount of sales Predictor Coef SE Coef T P Constant 137.78 31.61 4.36 0.001 S= 10.7058 R-Sq=82.4% R-Sq(adj) = 80.7% Regression 1 5380.5 5380.5 46.95 0.000 Residual error 10 1146.1 114.6 Total 11 6526.7 AMOUNT OF SALES NUMBER OF I
The chairman of the marketing department at a large state university undertakes a study to relate starting salary after graduation for marketing majors to grade point average (GPA) in major courses. To do this, records of 7 recent marketing graduates are selected randomly and the results are shown in the table below. Market