1. If the correlation coefficient between the variables is 0, it means that the two variables aren’t related. – TRUE 2. In a simple regression analysis the error terms are assumed to be independent and normally distributed with zero mean and constant variance. – TRUE 3. The difference between the actual Y-value and the predicted Y-value found using a regression equation is called the residual (ε) – TRUE 4. In a multiple regression analysis with N observations and k independent variables, the degrees of freedom for the residual error is given by (N-k). – FALSE (correct answer N-k-1) 5. From the following scatter plot, we can say that between y & x there is _______. – Negative correlation

6. According to the graph, X & Y have ________. – Virtually no correlation

7. A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a function of batch size (the number of boards produced in one lot or batch.) The explanatory variable is called the _______. – Coefficient of determination 8. In the regression equation, y = 75.65 + 0.50x, the intercept is ______. – 75.65 9. The assumptions underlying simple regression analysis include ______. – The error terms are independent 10. The proportion of variability of the dependent variable accounted for or explained by the independent variable is called the _______. – coefficient of determination 11. A manager wishes to predict the annual cost(y) of an automobile based on the number of miles(x) driven. The following model was developed, y = 1550 + 0.36x -- If a car is driven 30,000 miles, the predicted cost is _______. – 12,350 12. A cost accountant is developing a regression model to predict the total cost as a linear function of batch size (the number of boards produced in ne lot or batch) and production shift (day and evening). The dependent variable in this model is ________. –total cost 13. The...

...RegressionAnalysis (Tom’s Used Mustangs)
Irving Campus
GM 533: Applied Managerial Statistics
04/19/2012
Memo
To:
From:
Date: April 19st, 2012
Re: Statistic Analysis on price settings
Various hypothesis tests were compared as well as several multipleregressions in order to identify the factors that would manipulate the selling price of Ford Mustangs. The data being used contains observations on 35...

...32.11 |
2010 | 4284 | 3.28 | 31.23 |
2011 | 3674 | 2.65 | 24.16 |
Using regressionanalysis we want to determine the relationship between ROA, ROE and stock price of PT BCA Tbk. In this case, ROA and ROE are the independent or explanatory variable (X), while stock price is the dependent variable that we want to explain (Y).
RegressionAnalysis
SUMMARY OUTPUT |
| |
Regression Statistics |...

...RegressionAnalysis: A Complete Example
This section works out an example that includes all the topics we have discussed so far in this chapter.
A complete example of regressionanalysis.
PhotoDisc, Inc./Getty Images
A random sample of eight drivers insured with a company and having similar auto insurance policies was selected. The following table lists their driving experiences (in years) and monthly auto insurance premiums.
Driving...

...Quick Stab Collection Agency: A RegressionAnalysis
Gerald P. Ifurung
04/11/2011
Keller School of Management
Executive Summary
Every portfolio has a set of delinquent customers who do not make their payments on time.
The financial institution has to undertake collection activities on these customers to recover the
amounts due. A lot of collection resources are wasted on customers who are difficult or
impossible to recover. Predictive analytics can...

...been retrieved from the case study titled “Housing Price” (Case #27 - Practical Data Analysis: Case Studies in Business Statistics- Marlene A. Smith & Peter G. Bryant)
The most important factor in determining the selling prices ofhouses is to know the features that drive the selling prices of the house. People tend to have more interest in houses with multiple bed rooms/bathrooms, fireplace, garage for multiple cars and location while choosing a...

...140
13 MultipleregressionMultipleregression
In this chapter I will briefly outline how to use SPSS for Windows to run multipleregression analyses. This is a very simplified outline. It is important that you do
more reading on multipleregression before using it in your own research. A good
reference is Chapter 5 in Tabachanick and Fiddell (2001), which covers the
underlying...

...Multipleregression: OLS method
(Mostly from Maddala)
The Ordinary Least Squares method of estimation can easily be extended to models involving two or more explanatory variables, though the algebra becomes progressively more complex. In fact, when dealing with the general regression problem with a large number of variables, we use matrix algebra, but that is beyond the scope of this course.
We illustrate the case of two explanatory...

...
Mortality Rates
RegressionAnalysis of Multiple Variables
Neil Bhatt
993569302
Sta 108 P. Burman
11 total pages
The question being posed in this experiment is to understand whether or not pollution has an impact on the mortality rate. Taking data from 60 cities (n=60) where the responsive variable Y = mortality rate per population of 100,000, whose variables include Education, Percent of the...