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Linear Regression

Standard Error of Estimate and Predictions Regarding Sales

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),

3 Regression/Testing Questions

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


(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

Theory, analysis and interpretation of regression

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

Linear regression

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.

Linear Regression and Correlation

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

Linear Regression

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

Calculating Simple Linear Regression

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.

Linear programming - daily production totals of a certain product

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

Linear Regression Lines

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

The answer to Correlation Analysis

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

Regression Relationship Question

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

Linear regression questions modelled

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

Managerial Economics and Business Strategy - 2 Regression Questions

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

Overview Linear Regression

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...

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

T-Value of a Regional Chain Sporting Goods Store

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

Regression Equation Function

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

Linear Regression in a Marketing Department

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