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# Regression Analysis

### Problem analysis--time series

1. Corporate triple A bond interest rates for 12 consecutive months are given below. Month Interest rate 1 9.5 2 9.3 3 9.4 4 9.6 5 9.8 6 9.7 7 9.8 8 10.5. 9 9.9 10 9.7 11 9.6 12

### Regression Analysis of Operating Expense and Staff Size

In this study we will consider the current issues of operational expenses in relation to the number of staff and number of branches being experienced by 123 Finance Inc. With current company staff being split between eight separate branches located across the United States, it has been suggested that a means of reducing daily op

### regression

See attached file for full problem description. Question 2) If you are given that the dependent variable (y) is Annual Sales, and x1 is the number of jobs held by each member of the sales staff within the past 5 year period, x2 is the years of experience of each staff member and x3 is the number of glasses of wine each staff

### Scatter diagram and regression equation

Draw a scatter diagram. Determine the regression equation. Earth Engineering is in the process of trying to locate office space to accommodate employee growth. Over the last five years, the office has grown from 25 to 54 employees. Within less than a two-year period, the office has had to move to two new buildings - one was

### Statistics

If I tell you that the coefficient for X1 is .35, and the coefficient for X2 is -1.6, what does that mean with respect to the y variable?

### Interpretation of Regression Coefficients, R Square

What is the interpretation of the coefficients that emerge from the regression equation. Can you predict a change in the y variable given knowledge of the x variable? How much change would you predict in y for a one unit change in x?

### Statistics

14. Mr. James McWhinney, president of Daniel-James Financial Services, believes there is a relationship between the number of client contacts and the dollar amount of sales. To document this assertion, Mr. McWhinney gathered the following sample information. The X column indicates the number of client contacts last month, and th

### Regression and correlation

1) When is regression used? What are the assumptions of Linear Regression? 2) What is correlation? How does it differ from regression? What is the interpretation of the correlation coefficient?

### Multiple choice question from time series analysis

1. Time series methods a. discover a pattern in historical data and project it into the future. b. include cause-effect relationships. c. are useful when historical information is not available. d. All of the alternatives are true. 2. Gradual shifting of a time series over a long period of time is called a. periodic

### Statistical problem - coefficient of multiple correlation

Suppose a large consumer product company wants to measure the effectiveness of different types of advertising media in the promotion of its products. Specifically, two types of advertising media are to be considered: (1) radio and TV advertising, and (2) newspaper advertising including the cost of discount coupons. A sample of 2

### Hypothesis Test on Correlation and Regression Analysis

Palmdale Permits Population 2003 946 127,585 2004 1366 131,295 2005 1536 134,570 2006 1190 141,012 Total Permits: 5,038 Ho: p=0: The amount of permits is dependent upon population. H1: p is not equal to 0: The amount of permits is not dependent upon population. In

### Regression analysis of depression data

A University Counseling Clinic is interested in predicting the levels of depression from the number of social events attended per week by a sample of their clients. The data are below: a. Conduct and interpret the appropriate analysis to determine if there is a relationship between number of social events attended and depress

### Correlation and Regression Analysis: Opinion of Lab and Grades

The same students from the above scenario who are in the General Psychology class with the Virtual Lab exercises are asked to rate their opinion of the lab experiences. Virtual Lab Opinion 70 84 75 80 94 87 90 75 92 90 15 18 12 17 20 18 15 17 16 10 a. Conduct and interpret the appropriate statistical a

### Regression Analysis of Real Estate Sale Price Appraised Value

4) Real estate investors, home buyers, and home owners often use the appraised value of a property as a basis for predicting sale price. Data on sale prices and total appraised values of 92 residential properties sold in 1999 in an upscale Tampa, Florida neighborhood named Tampa Palms. The first five and last five observations o

### This posting looks at a regression analysis.

This solution offers a regression analysis with research citations.

### Regression analysis for age and blood alcohol concentration data

1. A study was conducted to investigate the relationship between age (in years) and BAC (blood alcohol concentration) measured when convicted DWI (driving while intoxicated) jail inmates were first arrested. Sample data are given below for randomly selected subjects. Age 17.2 43.5 30.7 53.1 37.2 21.0 27.6 46.3 BAC 0.19 0.20

### Tech's admission objective is a class of 5,000 entering freshmen and it wants to forecast the percentage of offers it will likely have to make in order to achieve this objective.

The admission data for freshmen at Tech during the past 10 years is as follows. Year Applicants Offers % Offers Acceptances % Acceptances 1 13,876 11,200 80.7 4,112 36.7 2 14,993

### Regression analysis for baseball data

The manager of the Ramona Inn Hotel near Cloverleaf Stadium believes that how well the local Blue Sox professional baseball team is playing has an impact on the occupancy rate at the hotel during the summer months. Following are the number of victories for the Blue Sox ( in a 162 game schedule) for the past eight years and the h

### Forecasting

Metro Food Vending operates vending machines in office buildings, the airport, bus stations, colleges, and other businesses and agencies around town and operates vending trucks for building and construction sites. The company believes its sandwich sales follow a seasonal pattern. It has accumulated the following data for sandwic

### Time series analysis of historical population of London

Given the historical population of London: Year Population 2000 7150000 1950 8300000 1900 2362000 1850 1000000 1800 700000 1750 600000 1700 350000 1650 200000 A. Estimate the population in 1600 B. Graph the

### Regression Analysis

Using Excel as your processing tool, work through three simple regression analyses. First run a regression analysis using the BENEFITS column of 288 data points in the AIU data set as the independent variable and the INTRINSIC job satisfaction column of 288 data points in the AIU data set as the dependent variable. Create a

### Regression analysis, Time series analysis, Chi square

Exercise 1 Calculate a four-quarter weighted moving average for the number of America Online (AOL) subscribers for the nine quarters of data. The data are reported in thousands. Apply weights of .1, .2, .3 and .4, respectively, for the quarters. In a few words, describe the trend in the number of subscribers. 31-Mar-01

### Regression analysis for mutual fund data

Linear regression analysis; construct confidence intervals for regression parameters; correlation coefficient . We can use two products at my work, which are mutual funds and see if there is a correlation between the two. The two different funds are: a domestic stock mutual fund, which only invests in large organizations (lar

### Quantitative analysis questions a - l

The director of graduate studies at a large college of business would like to be able to predict the grade point index (GPI) of students in an MBA program based on Graduate Management Aptitude Test (GMAT) score. A sample of 20 students who had completed 2 years in the program is selected; the results are as follows: [see the

### Correlation Matrix/Regression Equation

See the attached file for full problem description. 18. Fran's Convenience Marts are located throughout metropolitan Erie, Pennsylvania. Fran, the owner, would like to expand into other communities in northwestern Pennsylvania and southwestern New York, such as Jamestown, Corry, Meadville, and Warren. As part of her presentat

### Regression and Automated Testing Plan

Please prepare a Regression and Automated Testing Plan for a Course Project Think about including the following: A business letter to the Jonesville Library introducing the contents of the document A regression and automated testing plan that includes the following: - the phases targeted by the plan - how regress

### Describe the economic meaning and statistical significance of each individual independent variable included in the San Francisco demand equation.

Interpret the coefficient of determination (R2) for the San Francisco demand equation. What are expected unit sales and sales revenue in a typical market? Qi = b0 + b1Pi + b2Pxi + b3Adi + b4Ii + uit To illustrate use of the standard error of the estimate statistic, derive the 95 percent confidence interval for expe

### Economics and Management

The following questions refer to this regression equation. (Standard errors in parentheses.) QD = 15,000 - 10 P + 1500 A + 4 PX + 2 I, (5,234) (2.29) (525) (1.75) (1.5) R2 = 0.65 N = 120 F = 35.25 Standard error of Y estimate = 565 Q = Quantity demanded P = Price = 7,000 A = Advertising expense, in thousands = 54 PX =

### TOM (Operations Management)

The Manager of a seafood restaurant was asked to establish a pricing policy on lobster dinners. Experimenting with prices produced the following data: Avg # Sold per Day (y) Price (x) Avg # Sold per Day (y) Price (x) 200 \$6.00 155

### Regression Equation for Males Eating Junk Food

1. Figure out the regression equation for males based on what they spend on junk food and their weight. The weight is the independent variable. Do we have a correlation? 2. Figure out the regression equation for females based on what they spend on junk food and their weight. Do we have a correlation? Note: For the first part