EBK BUSINESS ANALYTICS
3rd Edition
ISBN: 9780135231906
Author: Evans
Publisher: VST
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Chapter 1, Problem 11PE
In this chapter, we noted the importance of defining and analyzing a problem prior to attempting to find a solution. Consider this example: One of the earliest operations research groups during World War II was conducting a study on the optimum utilization of Spitfire and Hurricane aircraft during the Battle of Britain. Whenever one of these planes returned from battle, the locations of the bullet holes on it were carefully plotted. By repeatedly recording these data over time, and studying the clusters of data, the group was able to estimate the regions of the aircraft most likely to be hit by enemy gunfire, with the objective of reinforcing these regions with special armor. What difficulties do you see here?
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Unit 5 Lab
Background: Between the years of 1997 and 2003, the World Health Organization collected data on head circumference, arm circumference, and other body measurements for 8440 children from Brazil, Ghana, India, Norway, Oman and the USA. All of the children were healthy and breastfed by mothers who did not smoke. Children in the sample lived in socioeconomic conditions favorable to normal physical growth. Variables such as parental education level and income level were used to exclude children whose growth was “environmentally constrained”; however, low-weight full term babies were included if their mothers met socioeconomic and nutritional criteria. In short, the study design attempted to include healthy children from a wide range of ethnic and cultural groups whose home environments reasonably assured the conditions for healthy physical growth.
This data was used to produce growth charts that are part of every pediatrician’s toolkit for monitoring a child’s overall…
Question 1
Stopping Distances
In a study on speed control, it was found that the main reasons for regulations were to make traffic flow more efficient and to minimize the risk of danger. An area that was focused on in the study was the distance required to completely stop a vehicle at various speeds. Use the following tables to answer the questions.
MPH
BRAKING DISTANCES (FEET)
20
20
30
45
40
81
50
133
60
205
80
411
Assume MPH is going to be used to predict stopping distance.
Develop the regression equation for the sample.
Can braking distance be accurately predicted from MPH?
Estimate the breaking distance if a motor vehicle is travelling at 35 MPH and 76 MPH.
Question 1
Stopping Distances
In a study on speed control, it was found that the main reasons for regulations were to make traffic flow more efficient and to minimize the risk of danger. An area that was focused on in the study was the distance required to completely stop a vehicle at various speeds. Use the following tables to answer the questions.
MPH
BRAKING DISTANCES (FEET)
20
20
30
45
40
81
50
133
60
205
80
411
Assume MPH is going to be used to predict stopping distance.
Calculate the correlation coefficient ‘r’ for these values.
What does a correlation coefficient tell about the relationship between two variables? Within what range can a correlation coefficient assume a value.
Will you expect a positive, negative or zero correlation between the two variables for each of the following examples
Variables
Type of Correlation
Grade of a student and hours spent studying
Incomes and entertainment expenditures of…
Chapter 1 Solutions
EBK BUSINESS ANALYTICS
Ch. 1 - Discuss how you might use business analytics in...Ch. 1 - How might analytics be used in the following...Ch. 1 - A supermarket has been experiencing long lines...Ch. 1 - For each of the following scenarios, state whether...Ch. 1 - Suppose that a manufacturer can produce a part for...Ch. 1 - A bank developed a model for predicting the...Ch. 1 - Four key marketing decision options are price P,...Ch. 1 - Total marketing effort is a term used to describe...Ch. 1 - A manufacturer of headphones is preparing to set...Ch. 1 - In this chapter, we noted the importance of...
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- Drop-off points (points de collecte in French), where residents can dispose of their organic waste for composting, were established in each of the five targeted neighborhoods of PROBLEM 1. Camille wants to see whether or not there exists a relationship between the average weekly amount of non-disposed food waste per household and the availability of drop-off points in the neighborhood, expressed as the number of households per drop-off point (considered fixed). Her data and some of her preliminary calculations are presented below: Camille also calculated the slope of the fitted regression line: estimated slope = 0.008. Test whether or not the availability of drop-off points in the neighborhood has a linear effect on the amount of non-disposed food waste per household. Use α = 0.10.arrow_forwardDrop-off points (points de collecte in French), where residents can dispose of their organic waste for composting, were established in each of the five targeted neighborhoods of PROBLEM 1. Camille wants to see whether or not there exists a relationship between the average weekly amount of non-disposed food waste per household and the availability of drop-off points in the neighborhood, expressed as the number of households per drop-off point (considered fixed). Her data and some of her preliminary calculations are presented below: Number of Amount of non- (x, – x)* (Y, -Y) (x; - x)(Y, – Y) households per drop-off point disposed food waste per household (kg/week) Yi Xi 387.5 4.0 7656.25 0.25 43.75 337.5 3.2 1406.25 0.09 -11.25 187.5 2.5 12656.25 1.00 112.50 412.5 5.0 12656.25 2.25 168.75 175.0 2.8 15625 0.49 87.50 E; = 1500 Σ 17.5 E; = 50000 Σ -4.08 Ej = 401.25 2) Camille also calculated the slope of the fitted regression line: estimated slope = 0.008. Test whether or not the…arrow_forwardA quality control engineer studied the relationship between years of experience as a system control engineer and the capacity of the engineer to complete within a given time a complex control design including the debugging of all computer programs and control devices. A group of 25 engineers having widely differing amounts of experience (measured in months of experience) was given the same control design project. The results of the study are given in the following table with y = 1 if the project was successfully completed in the allocated time and y = 0 if the project was not successfully completed. a. Determine whether experience is associated with the probability of completingthe task. b. Compute the probability of successfully completing the task for an engineer having 24 months of experience. Place a 95% confidence interval on your estimate.arrow_forward
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