# Principles of Business Statistics

Mihai Nica

Copyright Year: 2013

Publisher: OpenStax CNX

Language: English

## Formats Available

## Conditions of Use

Attribution

CC BY

## Reviews

This book lacks a few of the chapters covered in a traditional statistics book. For example, a chapter introducing probability and a chapter covering discrete probability. read more

This book lacks a few of the chapters covered in a traditional statistics book. For example, a chapter introducing probability and a chapter covering discrete probability.

Content appears to be accurate, error-free and unbiased, but that is to be somewhat expected for a statistics book.

Considering its a statistics book, the equations/formulas don't change so they will stay relevant. Also, examples are written in a generic form so they will not become obsolete or need updated frequently.

Text does a good job explaining the technical terminology in an easy to understand context.

Chapters are set up in a similar format explaining each new concept with examples/practice problems built in where necessary. Also, a glossary is provided at bottom of pages.

Content areas are broken down such that it should be easy for students to navigate to the section they need and students should be able to find the information based on section headings.

The book is organized in a clear, logical fashion, just as most traditional introductory statistics would be.

I did not notice any interface issues.

The book appeared to not have any major or noticeable grammatical errors.

The text is not culturally insensitive or offensive. However, it should be noted that a statistics books is more of a technical book.

I would definitely use this for a shortened semester class or in conjunction with another textbook depending on the needs of the class.

I enjoyed how the book started out with vocabulary associated with statistics and mixing in descriptive statistics at the same time. Most books tend to separate these two, and students have hard time connecting them. The students actually "get to... read more

I enjoyed how the book started out with vocabulary associated with statistics and mixing in descriptive statistics at the same time. Most books tend to separate these two, and students have hard time connecting them. The students actually "get to start" statistics from day one, instead of just learning vocabulary.

However, in Chapter 1, it states, "After you have studied probability and probability distributions, you will learn formal methods for drawing conclusions from 'good' data." (page 2). However, there is no formal discussion on Probability in the textbook. The first encounter students have with probability is in Chapter 3 on the Normal Distribution. On page 39, it states, "Shade the approximate area that represents the probability that one randomly chose male is taller than 72 inches". There is no discussion of probability between page 2 and page 39 for students to have a grasp of the concept of probability prior to this question.

Imbedded in the textbook are statements of “other” distributions besides the Normal Distribution., however, there is no in depth look into uniform, discrete, binomial and gamma distributions.

In fact, the Binomial Distribution is "assumed" to be known. For example, page 54, the statement "Recall, that if x is the binomial random variable, then X~B(n,p)". However, the binomial random variable is never mentioned prior to this paragraph, so how can a student "recall" it?

I did look for any indication in the book of what previous knowledge students should have prior to entering this class. I see that this book relies on the TI-83/84 Calculator Families for their calculations, in addition, students need a knowledge of linear equations and graphing. Finally, students will need to feel comfortable working with variables and using statistical symbols. This level use of statistical symbols is too much for my Business Students who are only earning an Associates Degree and have had equivalent of one term of Beginning Algebra as their pre-requisite.

As mentioned in the reply above, the book "assumes" students know topics coming in. It assumes a student knows probability and a binomial distribution. Since the book compares a binomial to a normal distribution, it must also assume the student knows the difference between a continuous and a discrete random variable and which distribution is which.

On Page 59, i says to, "See Discrete Random Variables for help with calculator instruction for the binomial". However, it does not give a page number, and when I Search for "Discrete Random Variables", I cannot find any link to binomial distribution and help with calculator.

The examples are great examples. The problems are great problems. I enjoyed reading through the Collaborative Classroom Activities. However, there are too many topics either "missing" or "assumed".

I am also concerned about the "Note: If you are being asked to find the probability of an individual value, do not use the Central Limit Theorem. Use the distribution of its random variable". (page 48). H however, "other" distributions are not discussed in this book. Right after this statement, the book does give one (and only one) example of a Uniform Distribution, and in the Glossary, it gives the definition and formulas for finding its probability, but there was no formal discussion. In the example itself, it does not even say "what" a uniform distribution is... Just gave the students a random distribution and assumed they know what it is?

I am impressed that most the examples in the book have longevity. Most math books try to find "current and trendy" data, but their longevity is 3-6 years maximum.

There are also many times when the data collected is from the students, using "real-time" data: weight or color of backpacks, hours of sleep, number of shoes one owns, etc. This inclusion of the student in the data collection (especially when there is a data point that is "them") gives the student ownership to the work.

Some examples do need to be updated. It would be nice if there was a link to where the data were collected. This way, an instructor can update what they feel necessary. Some data is dated "Fall Term 2007". (Ethnicity of College Students). With a link to how to find up-to-date data would also allow students to do the "upgrading" themselves.

I do like the chose of data for analysis in this book.

As mentioned above, it is hard to look at a book without knowing the pre-requisites. Our college offers three statistics classes ranging from students who only have one term of algebra, to students having a term of college algebra, to students who have taken a year of calculus. The terminology is appropriate for all levels mentioned, however, the students who only had one term of algebra will be overwhelmed with the heavy reliance of variables in this course.

I do appreciate the book using variables, formulas and technical aspects found in higher level statistical courses. This is a bonus for students continuing onto degree programs relying on more in-depth knowledge of statistics.

I have always had a hard time reading such sterile OER textbooks like this one. In which a paragraph may have two or three definitions. It would be better if the sections were uniform. That when there is a definition, it is obvious it is a definition. There are many things that are bold to make certain concepts stand out. I understand that importance also. But when both the definitions and the important concepts are combined in a paragraph and both bold type, it is difficult to determine what is what.

I will admit, it is extremely consistent with the use of the notation of statistics. It would be nice to have a page of all the notation and their meaning instead of a student having to search for the first time it was used.

As I read the book more and more, I am finding there are lots of reference to "missing" content (or content that was to be known?) For instance, on page 81, there are two references to content that is available online. When I look at these pieces, they are consistent with the notation and feel of the book. However, I do not know why they are not included in the book.

Yes, you can take each section and use them on their own. The learning outcomes are specified for each section. This might be where the reference to content online might be helpful when using a section or two from this book.

I feel there are missing concepts (like Probability - there is no definition nor discussion on this concept, yet it is the foundation of Statistics). In addition, as mentioned in previous comments, there are references to topics that cannot be found in the book.

I am extremely impressed by the organization/ flow / structure of the first two chapters, but the next chapter after that, jumps into the Normal Distribution without a discussion on what a probability distribution is, much less the difference between a discrete and continuous distribution.

The hardest part for OER books is for a complete problem to be on one page, and not having to turn the pages to see the whole problem. But that is just formatting.

However, as mentioned earlier, there are so many BOLD words, including the word when it is first defined. If there was more consistency in the formatting of the pages of "when" a concept is defined vs. when a concept is to be brought to the student's attention, that would help with the flow of reading and comprehension.

From what I read, I did not find any grammatical errors.

Statistics is full of data analysis, and it is difficult not to use examples that could be inclusive or not inclusive. However, I believe the examples in this book were inclusive. Including, collecting data on the students themselves.

I still am trying to figure out the prerequisite knowledge needed to teach out of this textbook. However, there are modulars / sections I would use in my class. I would not be able to use the book as a stand alone book. Too many basic, foundational concepts missing.

I enjoy the examples and classroom activities to try on my students.

## Table of Contents

1 Sampling and Data

- 1.1 Sampling and Data: Introduction
- 1.2 Sampling and Data: Statistics
- 1.3 Sampling and Data: Key Terms
- 1.4 Sampling and Data: Data
- 1.5 Sampling and Data: Variation and Critical Evaluation
- 1.6 Sampling and Data: Frequency, Relative Frequency, and Cumulative Frequency

2 Descriptive Statistics

- 2.1 Descriptive Statistics: Introduction
- 2.2 Descriptive Statistics: Displaying Data
- 2.3 Descriptive Statistics: Histogram
- 2.4 Descriptive Statistics: Measuring the Center of the Data
- 2.5 Descriptive Statistics: Skewness and the Mean, Median, and Mode
- 2.6 Descriptive Statistics: Measuring the Spread of the Data

3 The Normal Distribution

- 3.1 Normal Distribution: Introduction
- 3.2 Normal Distribution: Standard Normal Distribution
- 3.3 Normal Distribution: Z-scores
- 3.4 Normal Distribution: Areas to the Left and Right of x
- 3.5 Normal Distribution: Calculations of Probabilities
- 3.6 Central Limit Theorem: Central Limit Theorem for Sample Means
- 3.7 Central Limit Theorem: Using the Central Limit Theorem

4 Confidence Interval

- 4.1 Confidence Intervals: Introduction
- 4.2 Confidence Intervals: Confidence Interval, Single Population Mean, Population Standard Deviation Known, Normal
- 4.3 Confidence Intervals: Confidence Interval, Single Population Mean, Standard Deviation Unknown, Student's-t
- 4.4 Confidence Intervals: Confidence Interval for a Population Proportion

5 Hypothesis Testing

- 5.1 Hypothesis Testing of Single Mean and Single Proportion: Introduction
- 5.2 Hypothesis Testing of Single Mean and Single Proportion: Null and Alternate Hypotheses
- 5.3 Hypothesis Testing of Single Mean and Single Proportion: Using the Sample to Test the Null Hypothesis
- 5.4 Hypothesis Testing of Single Mean and Single Proportion: Decision and Conclusion

6 Linear Regression and Correlation

- 6.1 Linear Regression and Correlation: Introduction
- 6.2 Linear Regression and Correlation: Linear Equations
- 6.3 Linear Regression and Correlation: Slope and Y-Intercept of a Linear Equation
- 6.4 Linear Regression and Correlation: Scatter Plots
- 6.5 Linear Regression and Correlation: The Regression Equation
- 6.6 Linear Regression and Correlation: Correlation Coefficient and Coefficient of Determination
- 6.7 Linear Regression and Correlation: Testing the Significance of the Correlation Coefficient
- 6.8 Linear Regression and Correlation: Prediction

## Ancillary Material

## About the Book

You are probably asking yourself the question, "When and where will I use statistics?". If you read any newspaper or watch television, or use the Internet, you will see statistical information. There are statistics about crime, sports, education, politics, and real estate. Typically, when you read a newspaper article or watch a news program on television, you are given sample information. With this information, you may make a decision about the correctness of a statement, claim, or "fact." Statistical methods can help you make the "best educated guess."

## About the Contributors

### Editor

**Mihai Nica**