Business Modeling

Topics: Regression analysis, Forecasting, Statistics Pages: 13 (2408 words) Published: October 11, 2014


Prepared by:

Date: June 6,2014

Nova Southeastern University
H. Wayne Huizenga School
of Business & Entrepreneurship
 
Assignment for Course:
QNT5040
Submitted to:
Dr. Yurova  
Submitted by:

Date of Submission:June 6, 2014
Title of Assignment: Auto Parts Sales Forecast

CERTIFICATION OF AUTHORSHIP: I certify that I am the author of this paper and that any assistance I received in its preparation is fully acknowledged and disclosed in the paper. I have also cited any sources from which I used data, ideas or words, either quoted directly or paraphrased. I also certify that this paper was prepared by me specifically for this course. Student's Signature: _______ _______________________

***************************************************************** Instructor's Grade on Assignment:
Instructor's Comments:

TITLE OF RUBRIC: Auto Parts Sales Forecast
Course: QNT 5040
LEARNING OUTCOME/S: (see syllabus)
Date: June 6, 2014
PURPOSE: To facilitate effective decision making under uncertain conditions by quantifying risk. Name of Student:
VALIDITY: Best practices in Forecasting
Name of Faculty: Dr. Yurova  
COMPANION DOCUMENTS: Email sent separately

Earning maximum points in each box in ‘PROFICIENT’ column and / or points in columns to the right of ‘PROFICIENT’ meets standard.

>

Performance Criteria

Basic

Developing

Proficient

Accomplished

Exemplary

Score

Identify the problem

Does not
identify the problem, or does not identify the right problem.

(0 pts)
Identifies symptoms

(5 pts)
Identifies some elements of the problem.

(10 pts)
Substantially
identifies the problem.

(12 pt)
Effectively and succinctly
identifies the problem.

(15 pts)

Describes assumptions and methods

Does not describe assumptions and methods used

(0 pts)
Does not precisely describe the
assumptions and methods used

(3 pts)
Somewhat describes assumptions and methods used

(7 pts)

Substantially
describes assumptions and methods used

(8 pts)
Effectively describes assumptions and methods used

(10 pts)

Calculate statistics using a spreadsheet

Does not calculate appropriate statistics using a spreadsheet and/or does not provide evidence of calculations
(0 pt)
Calculates appropriate statistics using a spreadsheet (most answers are not correct)

(13 pts)
Calculates appropriate statistics using a spreadsheet (not all answers are correct)

(21 pts)

Calculates appropriate statistics using a spreadsheet (most answers are correct)

(25 pts)

Effectively
calculates statistics using a spreadsheet (almost all answers are correct)

(30 pts)

Explain
implications of
output of statistical analysis

Does not explain
implications of
output of statistical analysis

(0 pt)
Partially
explains
implications of
output of statistical analysis

(3pts)
Somewhat explains
implications of
output of statistical analysis

(7 pts)

Substantially
explains
implications of
output of statistical analysis

(8 pts)
Effectively explains
implications of
output of statistical analysis
(10 pts)

. . . Continued …
TITLE OF RUBRIC: Report and Solution to Superior Grain Elevator, Inc. Cont. (Page 2 of 2) Course: QNT 5040
TITLE OF RUBRIC: Auto Parts Sales Forecast
Course: QNT 5040
LEARNING OUTCOME/S: (see syllabus)
Date: June 6, 2014
PURPOSE: To facilitate effective decision making under uncertain conditions by quantifying risk. Name of Student:
VALIDITY: Best practices in Forecasting

Earning maximum points in each box in ‘PROFICIENT’ column and / or points in columns to the right of ‘PROFICIENT’ meets standard.

>

Performance Criteria

Basic

Developing

Proficient

Accomplished

Exemplary

Score
Generates solutions based on analysis and context

Does not
generate...

Bibliography: Poane, D., & Seward, L. E. (2013). Business Modeling Customized Readings for QNT5040. : Mc Graw Hill Education.
Microsoft Office Excel. (2007). Redmond, WA: Microsoft Corporation.
Albright, Winston & Zappe (2010). Business Modeling, Selections from 4e – QNT 5040 (4th ed.). Mason: Cengage Learning.
Aczel,A & Sounderpandian,J (2009). Complete Business Statistics 7th edition (592). : Mc Graw Hill Education.
U.S. Automotive Parts Industry Annual Assessment. (2009, April 1). . Retrieved June 6, 2014, from http://trade.gov/mas/manufacturing/OAAI/build/groups/public/@tg_oaai/documents/webcontent/tg_oaai_003759.pdf
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