Statistics for Managers Using Microsoft Excel (7th Edition) [Print Replica] [Kindle Edition] Author: David M. Levine | Language: English | ISBN:
B00BBNC8IC | Format: PDF, EPUB
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Free download Statistics for Managers Using Microsoft Excel (7th Edition) [Print Replica] [Kindle Edition] Epub Free from mediafire, rapishare, and mirror link For undergraduate Business Statistics Courses.
Analyze the data, see the business relevance.¿
Reducing the emphasis on doing computations, this practical text thoroughly integrates Microsoft® Excel as a tool for analysis and presents statistical concepts in the context of the functional areas of business. Download latest books on mediafire and other links compilation Statistics for Managers Using Microsoft Excel (7th Edition) [Print Replica] [Kindle Edition] Epub Free
- File Size: 38206 KB
- Print Length: 792 pages
- Simultaneous Device Usage: Up to 2 simultaneous devices, per publisher limits
- Publisher: Pearson; 7 edition (May 8, 2013)
- Sold by: Amazon Digital Services, Inc.
- Language: English
- ASIN: B00BBNC8IC
- Text-to-Speech: Not enabled
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- Lending: Not Enabled
- Amazon Best Sellers Rank: #311,819 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
- #84
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- #84
in Kindle Store > Kindle eBooks > Business & Money > Economics > Statistics
I've used this text for two courses at my college: statistics and regression analysis; during my stats class the text was in edition 6 and during the latter class, edition 7.
There are MANY problems with this text; I found it difficult to follow, out of order and lacking in explanations as to why conclusions were drawn, 3 examples:
Normality assumptions--the text glosses over when an evaluation for normality should be used prior to using a particular equation and doesn't do a good job of defining how to evaluate normality when faced with a certain set of data. This is an important concept because in order to use a given equation you HAVE to satisfy the normality condition BEFORE executing the equation or your results will be bad!
Two-sample testing: jumping to a conclusion that the tstat or Zstat value leads to a particular conclusion w/o explaining HOW that conclusion was drawn (done twice in chapter 10 on pgs 347 & 365 respectively in edition 7).
Time-series forecasting: fig. 16.12 is an example of an excel spreadsheet with lagged predictor variables with zero explanation as to how the data was entered into the columns & why. Once you understand the concept of lagged variables, the way the values are entered makes sense, but for someone learning the subject matter, more detail is necessary.
If this is your required text, you better hope you have a good instructor (mine wasn't) to explain the mess that this book creates out of this subject.
By C. Hanson
The organization of this textbook is awful. It's very difficult to find the problems assigned because there's no discernible labeling standard. Also, there's very little content and poor explanations for the sections.
By Smith
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