Every MBA, CPA, and CFA student will learn statistics in their program in their first or second semesters. Understanding statistics is vital for business students because it makes you a better decision-maker whether you are an investor, owner, operator, or executive. Many statistics classes use the textbook ‘Statistics for Business: Decision Making and Analysis’ by Robert Stine and Dean Foster as the recommended or reference textbook. Our graduate level statistics tutors offer tutoring for Stine and Foster’s ‘Statistics for Business: Decision Making and Analysis’ textbook. Here is our review.
- Introduction: ‘Statistics for Business: Decision Making and Analysis’
- Strengths: Why We Like the Textbook by Robert Stine and Dean Foster
- Weaknesses: Statistics for Business: Decision Making and Analysis
- Why Statistics Is Important For Business Students?
- Other Courses That Use the textbook Statistics for Business: Decision Making and Analysis
- Why is Statistics for Business by Stine and Foster so Popular?
- Statistics Topics / Teaching Plan / Structure of the Textbook
- Different Editions of Statistics for Business: Decision Making and Analysis
- Authors of ‘Statistics for Business: Decision Making and Analysis’
- Statistics Tutoring for ‘Statistics for Business: Decision Making and Analysis & Other Data Analysis Textbooks
Introduction: ‘Statistics for Business: Decision Making and Analysis’ by Robert Stine and Dean Foster
“Statistics for Business: Decision Making and Analysis” is used in introductory business statistics courses. It is a comprehensive statistics textbook. starts with the foundations of data and data gathering including basic survey techniques.
Authors Robert Stine and Dean Foster emphasize the application of statistical theory and methods with plenty of business examples in their statistics textbook, “Statistics for Business: Decision Making and Analysis.”
Authors Robert Stine and Dean Foster cover descriptive statistics, probability, confidence intervals, hypothesis testing, analysis of variance, regression analysis, and time series analysis in their statistics textbook. The textbook ‘Statistics for Business: Decision Making and Analysis’ by Robert Stine and Dean Foster is published by Pearson and is available in both print and online formats.
Strengths: Why We Like Statistics for Business: Decision Making and Analysis by Robert Stine and Dean Foster
The textbook ‘Statistics for Business: Decision Making and Analysis’ by Robert Stine and Dean Foster has many strengths.
- Clear and Concise Writing Style: The authors, Robert Stine and Dean Foster, explain statistical concepts clearly and concisely. This makes the textbook Statistics for Business: Decision Making and Analysis easy to read and understand, even if you are new to the world of statistics.
- Focus on applications: In the textbook Statistics for Business: Decision Making and Analysis, the authors Robert Stine and Dean Foster use many real-world business examples. In addition, the authors provide many case studies for students to apply statistical methods and statistical tools in business contexts. Application of statistical methods and statistical tools to solve problems and generate insight in business contexts helps students gain confidence in using statistics.
- 4M Analytics framework: The textbook Statistics for Business: Decision Making and Analysis by Robert Stine and Dean Foster uses a 4M Analytics framework to explain statistical concepts. The 4M analytics framework consists of four distinct components: Motivation, Method, Mechanics, and Message. Each statistical concept and statistics tool is viewed from each of these four parts so students can see and understand the process of problem-solving and decision making using statistics.
- Many Statistical Software Programs to Choose from: Statistics for Business: Decision Making and Analysis by Robert Stine and Dean Foster teaches statistics using Excel, Minitab Express, and JMP. This gives professors and students a wide range of statistical software to learn from.
- Statistics Resources: The textbook Statistics for Business: Decision Making and Analysis has a dedicated website providing many additional resources including practice problems, data sets, solved examples, statictics case studies and video tutorials.
Weaknesses: Statistics for Business: Decision Making and Analysis by Robert Stine and Dean Foster
Some of the drawbacks of the textbook ‘Statistics for Business: Decision Making and Analysis’ by Robert Stine and Dean Foster are:
- Length: The book Statistics for Business: Decision Making and Analysis by Robert Stine and Dean Foster is over 900 pages. Students are already pressed for time and so are put off by such a large textbook.
- Price: Like most textbooks, Statistics for Business: Decision Making and Analysis by Robert Stine and Dean Foster is expensive.
- Advanced topics: The textbook Statistics for Business: Decision Making and Analysisis meant for introductory level courses. So it does not cover advanced statistical topics.
In summary, “Statistics for Business: Decision Making and Analysis” is a wonderful book for those starting out on statistics and data analysis.
Why Statistics Is Important For Business Students?
Statistics is important for a business student for many reasons.
Evaluation of Business Situations. Understanding statistics allows for better data analysis which helps students better evaluate a business, customers, operations, etc.
Identification of trends and patterns. Statistical analysis and data analysis tools help investors, owners, and managers identify trends and patterns.
Decision-making based on data analysis. Business decisions involve uncertainty, and statistics provides the tools to quantify and manage that uncertainty.
Additional Resources for Statistics for Business: Decision Making and Analysis
The book is part of the Pearson MyLab Statistics program, which provides additional online resources for students.
Other Courses That Use the textbook Statistics for Business: Decision Making and Analysis
Because this textbook is about decision making, it is used in courses that teach these statistics concepts but branded with other names, such as decision-making for managers, management data analysis, understanding data for decision-making, big data analytics, ML, etc. These types of statistics based courses are introduced early in the program, as many other courses, such as finance, operations management, economics, etc., use elements of statistics theory and practice. Understanding data and statistics helps business students evaluate business situations better. Students solve real-world business problems using statistical tools and statistical methods in these other courses, such as finance, operations management, economics, etc.,
For example the Columbia Business School’s B5100 and B6100 Managerial Statistics are mandatory statistics and data analysis course. At Columbia, B6101 is referred to as Business Analytics but one feels this textbook can be used as a reference textbook for B6101 too.
Why is Statistics for Business by Stine and Foster so Popular?
We discussed why we like the textbook Statistics for Business: Decision Making and Analysis by Robert Stine and Dean Foster. However, I believe its decision-making focus is why this textbook is popular among business school faculty.
Statistics Topics Teaching Plan / Structure of the Textbook
The textbook ‘Statistics for Business: Decision Making and Analysis’ by Robert Stine and Dean Foster is divided into four key sections, each designed to build upon the previous one, creating a logical progression of statistical concepts:
Part 1: Introduction to Statistics: Variation and Variability in Data
The first part of the textbook ‘Statistics for Business: Decision Making and Analysis’ by Robert Stine and Dean Foster lays out the foundational concepts in statistics. Chapter 1 covers data visualizations, and descriptive statistics. In the introductory chapters, authors Stine and Foster helps students understand and quantify variation in data. Chapter 2 covers data types. Data consists of numerical or categorical values collected from observations, experiments, or surveys.
Robert Stine and Dean Foster describe categorical data, which is summarized using frequency tables, bar charts, and pie charts to reveal patterns and distributions in chapter 3. It also describes numerical data, which is described through measures of central tendency (mean, median, and mode) and dispersion (range, variance, standard deviation).
Chapters 4 and 5 of the textbook ‘Statistics for Business: Decision Making and Analysis’ by Robert Stine and Dean Foster deal with the association between variables. Chapter 4 deals with the association between categorical variables. Here, relationships between categorical variables are analyzed using contingency tables and measures like Chi-square statistics. Stine and foster cover the association between quantitative variables in chapter 5. Quantitative relationships are assessed through correlation and scatterplots, identifying linear or nonlinear trends.
Part 2: Probability – Dealing with Uncertainty in Business
Chapters 7-12 of the textbook ‘Statistics for Business: Decision Making and Analysis’ by Robert Stine and Dean Foster deal with various aspects of probability. Probability measures the likelihood of events. Conditional Probability – The probability of an event occurring, given another event has happened, is calculated using Bayes’ theorem and conditional probability formulas. Random Variables – A random variable represents numerical outcomes of random processes and can be discrete or continuous.
Association Between Random Variables – Random variables can be dependent or independent, and their relationship is measured using covariance and correlation. Probability Models for Counts – Count data is modeled using discrete probability distributions, such as the Poisson and binomial distributions. Stine and Foster introduce the Normal Probability Model in chapter 12– The normal distribution is a fundamental probability model characterized by its bell shape and role in the Central Limit Theorem.
Part 3: Inference: Driving Decision Making in Business
Statistics in business is all about making inferences. Chapters 13-18 of the textbook ‘Statistics for Business: Decision Making and Analysis’ by Robert Stine and Dean Foster deal with various aspects of making inferences. Chapter 13 starts with learning how to take samples and do surveys. Only proper sampling methods can ensure that the survey results are representative of a population and minimize bias. Sampling variation describes differences between samples and quality control methods help assess data reliability. Stine and Foster cover confidence intervals in chapter 15. Confidence intervals provide a range of values within which the true population parameter is likely to fall. Chapter 16 introduces the ubiquitous statistical test: Hypothesis tests. Hypothesis testing examines claims about populations using test statistics and significance levels from sample data. Comparison of data – Statistical comparisons involve comparing means, proportions, or distributions across groups using t-tests, ANOVA, or other methods. Authors Robert Stine and Dean Foster introduce inferences for counts using methods like the Chi-square test in chapter 18 of ‘Statistics for Business: Decision Making and Analysis’. Chi-square tests help draw conclusions about categorical data distributions.
Part 4: Advance Statistical Concepts – Regression Analysis
The fourth part of the textbook ‘Statistics for Business: Decision Making and Analysis’ by Robert Stine and Dean Foster deals with regression and time series analysis. It has nine chapters on various subtopics covering simple and multiple regression techniques and time series analysis.
Chapter 19 deals with Linear Patterns: Linear relationships between variables are examined using scatterplots, correlation, and regression analysis. In chapter 20, Robert Stine and Dean Foster deal with curved patterns. Nonlinear relationships require polynomial regression or transformations to model curved trends. Chapter 21 of ‘Statistics for Business: Decision Making and Analysis’ introduces the simple regression model. Simple linear regression estimates the relationship between one predictor and one response variable. Regression Diagnostics – Residual analysis and diagnostic plots help assess the validity of a regression model which is critical in interpreting regression analysis output. In chapter 23, authors Robert Stine and Dean Foster introduce Multiple Regression. Multiple regression extends simple regression by incorporating multiple explanatory variables. Building Regression Models – Model selection techniques, such as stepwise regression, help create effective predictive models. Categorical Explanatory Variables – Categorical variables in regression use dummy variables and interaction terms. Analysis of Variance – ANOVA compares means across multiple groups to determine statistical significance.
Finally, Chapter 27 walks students through a Time Series Analysis. Time series analysis examines trends, seasonality, and forecasting in sequential data. More advanced statistical classes get into ARIMA forecasting, K-means Clustering, PCA analysis, Discriminant Analysis, Simulation, etc. and are not covered in the textbook ‘Statistics for Business: Decision Making and Analysis’ by Robert Stine and Dean Foster.
Different Editions of Statistics for Business: Decision Making and Analysis
The first edition of Robert Stine and Dean Foster’s textbook Statistics for Business: Decision Making and Analysis was published in 2010. The second edition of Statistics for Business: Decision Making and Analysis, by Robert Stine and Dean Foster, was published in 2013/14 with many more examples. Currently, the third edition has multiple reprints of the textbook, which have hit a winning formula with many more data visualization tools and updated datasets.
Authors of ‘Statistics for Business: Decision Making and Analysis’
Professor Robert Stine
Robert Stine is a professor at the Wharton School, University of Pennsylvania, where he specializes in business statistics and data analysis. Known for his engaging teaching style, Stine has won numerous awards for his contributions to statistics education. His research focuses on credit scoring, model selection, pattern recognition and classification, statistical computing and graphics, time series analysis, and forecasting, including using tools like regression modeling, time series analysis, and predictive analytics. Professor Stine did his BS at the University of South Carolina in 1977 and his MA and PhD at Princeton University in 1979 and 1982, respectively.
Professor Dean Foster
Dean Foster was a professor at the Wharton School, University of Pennsylvania. He is an acclaimed statistician who has contributed extensively to the field of statistical learning and decision-making. His work spans topics like model selection, machine learning, statistical NLP, variable selection, and Bayesian analysis. Professor Dean Foster did his BSc and MSc at the University of Maryland in 1980 and 1982. He then moved to Rutgers University for his MSc, which he finished in 1984. Professor Dean Foster returned to the University of Maryland to finish his PhD in 1988.
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