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Author: Mohammad Mahbobi, Thompson Rivers University, Thomas K. Tiemann, Elon University

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Review this book

#### Reviews for ''

##### Number of reviews: 2
###### Average Rating: 3.45 out of 5

1. Reviewed by: Liliane Tremblay
• Institution:
• Title/Position: Instructor
• Overall Rating: 2.9 out of 5
• Date:

#### Q: The text covers all areas and ideas of the subject appropriately and provides an effective index and/or glossary

The text covers some areas and ideas of the subject appropriately and provides an effective index but no glossary. Other areas not covered might include Probability Concepts, Index Numbers, Quality Control, and Decision Theory.

Comprehensiveness Rating: 3 out of 5

#### Q: Content is accurate, error-free and unbiased

Ch 4 Ho: π decorated socks ≤ .35
Ha: π decorated socks > .35 “the data support the alternative only
if his z-score is in the upper tail. ”
.95 of all z-scores associated with the proportion are less than -1.645 (lower tail? I would have instead stated that 0.05 are greater than +1.645)
If his sample z is > -1.645 (should have been > +1.645 for upper tail)
computes his sample z-statistic as -1.0811 (typo should be -1.8113)
Because his sample calculated z-score is larger than -1.645, it is unlikely that his sample z came from the sampling distribution of z’s drawn from a population where π< .35
(using a rejection region to reject H0…I would have NOT rejected H0 and concluded decorated socks ≤ .35)

– Ch 5 LaTonya computes her sample t-score
(10.83-11.71)/(0.749/√7) = 1.48 (should be – 3.108…I realized that her mean of 10.83 was wrong : it is 12.27 and the S.D. should be 0.998 which gives t as 1.48)
LaTonya used an α = .025 and decided that the data supported Ho
the p-value of .094 means that Ho would be supported for any α less than .094. Since LaTonya had used α = .025, this p-value means she does not find support for Ho (totally confusing …should not have the word NOT)
– Ch 8 If the t-score is large,either negative or positive… and Ha should be accepted. Substitute zero for b into the t-score equation, and if the t-score is small, b is close enough to zero to accept Ha (totally confusing explanation)
The hypotheses are:
H0: price ≠ f(distance, area)
Ha: price = f(distance, area)
Because the F-score from the regression, 6.812, is greater than the critical F-score, 4.26, we decide that the data support Ho (should support Ha)and conclude that the model helps us predict price of apartments. Alternatively, we say there is such a functional relationship in the population.
Figure 8.9 All these calculated values can be substituted back into the formula for the S.E. of the prediction: (uses formula for C.I.)

Content Accuracy Rating: 3 out of 5

#### Q: Content is up-to-date, but not in a way that will quickly make the text obsolete within a short period of time. The text is written and/or arranged in such a way that necessary updates will be relatively easy and straightforward to implement

I agree that the content is up-to-date, but not in a way that will quickly make the text obsolete within a short period of time. The text is written and/or arranged in such a way that necessary updates will be relatively easy and straightforward to implement. The material is presented in a concise manner with the focus on student understanding versus computing.

Relevance Rating: 4 out of 5

#### Q: The text is written in lucid, accessible prose, and provides adequate context for any jargon/technical terminology used

The first 3 chapters are written in lucid, accessible prose, and provides adequate context for any jargon/technical terminology used. However, I found the last 5 chapters to be very wordy and vague adding some confusion. As I elaborated in 2 Content Accuracy and 9 Grammatical Errors: these contributed greatly to my lowered trustworthiness of the content. I have never used a Normal Table that included the mirror image results of the negative Z-values. I would stick to the “normal” Normal Table with only the positive Z-values given. I did not find the Interactive Spreadsheets would be very helpful from a student’s standpoint in understanding “how” answers are calculated. They do allow students to play around with different numbers but I feel that students would not take the time to do this. They would benefit from seeing how the formulas work. The formulas I explored had a very convoluted path and I lost the trail fairly quickly.

Clarity Rating: 2 out of 5

#### Q: The text is internally consistent in terms of terminology and framework

I agree that the text is internally consistent in terms of terminology and framework.

Consistency Rating: 4 out of 5

#### Q: The text is easily and readily divisible into smaller reading sections that can be assigned at different points within the course (i.e., enormous blocks of text without subheadings should be avoided). The text should not be overly self-referential, and should be easily reorganized and realigned with various subunits of a course without presenting much disruption to the reader.

The text is easily and readily divisible into smaller reading sections that can be assigned at different points within the course (there is no enormous blocks of text without subheadings). The text does self-refer to the Interactive Spreadsheets a lot. It could be easily reorganized and realigned with various subunits of a course without presenting much disruption to the reader.

Modularity Rating: 3 out of 5

#### Q: The topics in the text are presented in a logical, clear fashion

I agree that the topics in the text are presented in a logical fashion. The structure is all prose other than the 15 Interactive Spreadsheets. There are very little diagrams, graphs, etc. to accommodate the visual learners.

Organization Rating: 3 out of 5

#### Q: The text is free of significant interface issues, including navigation problems, distortion of images/charts, and any other display features that may distract or confuse the reader

I read the text in iBooks and I found significant interface issues when accessing the Interactive Spreadsheets as none of the Interactive Figures worked (I had to open the Editable version and save them on my computer).

Interface Rating: 2 out of 5

#### Q: The text contains no grammatical errors

There are several errors and I will list a few (with my thought of what it should be) Ch 1 estimate of m. (μ) Ch 2 variance of population sx (σx) Ch 3 population mean m (μ) Ch 4 sample z-statistic as -1.0811 (-1.8113) Ch 5 (10.83-11.71)/(0.749/√7) = 1.48 (should be – 3.108 …I realized that her mean of 10.83 was wrong : it is 12.27 and the S.D. should be 0.998 which gives t as 1.48 …later it states Her arithmetic is the same, her sample t-score is still 1.41 (should be 1.48)
α = .05$(remove$ happens again)
Ch 7 Then she uses the formula from above to find her Spearman rank correlation coefficient: 1-[6/(9)(92-1)][38] = 1-0.3166=0.6834 (92-1 should be 81-1… maybe it means 92 and not 92)
Ch 8 There can be functions where one variable depends on the values values of two or more other variables (remove the second values)
If the t-score is large (either negative or positive)… and Ha should be accepted. Substitute zero for b into the t-score equation, and if the t-score is small, b is close enough to zero to accept Ha (totally confusing explanation
The hypotheses are:
H0: price ≠ f(distance, area)
Ha: price = f(distance, area)
Because the F-score from the regression, 6.812, is greater than the critical F-score, 4.26, we decide that the data support Ho (should support Ha)and conclude that the model helps us predict price of apartments. Alternatively, we say there is such a functional relationship in the population.
Figure 8.9 All these calculated values can be substituted back into the formula for the S.E. of the prediction: (uses formula for C.I.)

Grammar Rating: 2 out of 5

#### Q: The text is not culturally insensitive or offensive in any way. It should make use of examples that are inclusive of a variety of races, ethnicities, and backgrounds

I agree that the text is not culturally insensitive or offensive in any way. The use of female and male managers as well as various Canadian Cities in example problems was good. Also, touching on current immigration made it real-world.

Cultural Relevance Rating: 3 out of 5

I found that the formulas were all in a linear format which can be confusing to students, especially when variables are squared 9 squared looks like 92 . I would prefer using an Equation Editor.

Some reasoning was different from other texts. Rejection regions are never used and I found that odd. For example : using α = 0.05 then states that 0.95 of Z-values are below – 1.645 had me completely confused and I still am…see example below:
Ho: π decorated socks < .35
Ha: π decorated socks > .35
the data support the alternative only if his z-score is in the upper tail
Kevin will accept Ha only if his z is large and positive
Checking the bottom line of the t-table, Kevin sees that .95 of all z-scores associated with the proportion are less than -1.645. His rule is therefore to conclude that his sample data support the null hypothesis that 35 per cent or less of children’s socks are decorated if his sample (calculated) z is less than -1.645. If his sample z is greater than -1.645, he will conclude that more than 35 per cent of children’s socks are decorated and that Foothill Hosiery should invest in the machinery needed to sew embroidered patches on socks

2. Reviewed by: Peter Dalley
• Institution:
• Title/Position: Lecturer
• Overall Rating: 4 out of 5
• Date:

#### Q: The text covers all areas and ideas of the subject appropriately and provides an effective index and/or glossary

This textbook is an extremely concise and abbreviated statistics text. It is very practical and to the point. It omits a significant amount of detail that might be a problem for those interested in learning the subject in depth. However, its brevity may be beneficial for those who are not interested in the details, but simply want to know how to perform basic tests. There is very little instruction on how to interpret results, merely obtain them.

Comprehensiveness Rating: 2 out of 5

#### Q: Content is accurate, error-free and unbiased

The content is a very simplistic approach to statistical methods. There is often debate among statisticians as to the proper interpretation of some statistical tools, such as p-values, yet this textbook never gets into sufficient depth to risk making inaccurate statements. It is simple and only covers the surface of many more complex topics.

Content Accuracy Rating: 5 out of 5

#### Q: Content is up-to-date, but not in a way that will quickly make the text obsolete within a short period of time. The text is written and/or arranged in such a way that necessary updates will be relatively easy and straightforward to implement

The field of statistics is one that progresses at a snails pace. It is relatively easy to maintain a a statistics textbook up to date, as far as the theory goes. As time passes, the inclusion of more up to date examples will be a relatively simple task. The material is arranged in a way that it builds on itself in a very natural way. I suspects future updates, will contain small revisions in actual content, but will include the simple addition and alteration of examples.

Relevance Rating: 5 out of 5

#### Q: The text is written in lucid, accessible prose, and provides adequate context for any jargon/technical terminology used

The language used feels condescending. Although the topic can be complex, the language shouldn't speak to the reader as though they are a child. In many most cases, the jargon is excessively defined and explained. This makes the text wordy and tends to drag on without adding value.

Clarity Rating: 3 out of 5

#### Q: The text is internally consistent in terms of terminology and framework

The text is well laid out. Each topic flows to the next in a very logical way. Content builds on itself well. New concepts, terminology and methods are explained well the first time they are introduced. Because the book is extremely concise, new concepts are discussed frequently, but are always well explained. There is never an assumption of prior knowledge.

Consistency Rating: 4 out of 5

#### Q: The text is easily and readily divisible into smaller reading sections that can be assigned at different points within the course (i.e., enormous blocks of text without subheadings should be avoided). The text should not be overly self-referential, and should be easily reorganized and realigned with various subunits of a course without presenting much disruption to the reader.

The text is extremely concise. It would be difficult to remove any one section as a separate unit. Each chapter leads into the next. It would be I difficult to reorganize this text in any meaningful way. The text represents a condensed course in a very specific selection of statistical tool. An instructor would likely be required to follow the text as it is laid out. Individual chapters may work as review for students taking more advanced courses, but I wouldn't recommend using any one chapter on its own to learn from.

Modularity Rating: 3 out of 5

#### Q: The topics in the text are presented in a logical, clear fashion

Absolutely. There are very few topics in this concise textbook. Each chapter very quickly covers one specific tools with a handful of examples. Each chapter covers progressively more challenging material, and each is well based in previously covered material. With so little material in the textbook, it is easy to maintain a relatively linear path of information through the various topics.

Organization Rating: 5 out of 5

#### Q: The text is free of significant interface issues, including navigation problems, distortion of images/charts, and any other display features that may distract or confuse the reader

The PDF textbook worked fine. The graphics appear cheap and unprofessional. Perhaps similar in quality to ones produced by students taking the course. The charts, tables and graphs could be produced in a more professional manner. Some tables were split across pages which makes reading them difficult. Otherwise, everything was clear.

Interface Rating: 4 out of 5

#### Q: The text contains no grammatical errors

None that I noticed. It appears well written with correct spelling, proper grammar and punctuation.

Grammar Rating: 5 out of 5

#### Q: The text is not culturally insensitive or offensive in any way. It should make use of examples that are inclusive of a variety of races, ethnicities, and backgrounds

The content of the text is very neutral. Statistics is not a topic that is open to much variation in presentation. The examples and applications were all very canadian centric. As this is a Canadian edition of the textbook, this is to be expected. The diversity of the Canadian population seems to be well represented and numerous Canadian cities are used in the various examples.

Cultural Relevance Rating: 4 out of 5