Groebner, PhD, is Professor Emeritus of Production Management in the College of Business and Economics at Boise State University. Shannon, PhD, is Professor Emeritus of Supply Chain Operations Management in the College of Business and Economics at Boise State University.
CHAPTERS 1–3 SPECIAL REVIEW SECTION 146
- CHAPTER 4 Introduction to Probability 152
- CHAPTER 5 Discrete Probability Distributions 196
- CHAPTER 6 Introduction to Continuous Probability Distributions 236
- CHAPTER 7 Introduction to Sampling Distributions 263
- CHAPTER 8 Estimating Single Population Parameters 301
- CHAPTER 9 Introduction to Hypothesis Testing 340
- CHAPTER 10 Estimation and Hypothesis Testing for Two Population Parameters 387
- CHAPTER 11 Hypothesis Tests and Estimation for Population Variances 434
- CHAPTER 12 Analysis of Variance 458
Confidence Interval Estimate for the Population Mean, S Known 303 Confidence Interval Estimate for the Population Mean, . Confidence Interval Estimate for a Population Proportion 326 Determining the Required Sample Size for Estimating a Population Proportion 328 .
CHAPTERS 8–12 SPECIAL REVIEW SECTION 505
- CHAPTER 13 Goodness-of-Fit Tests and Contingency Analysis 521
- CHAPTER 14 Introduction to Linear Regression and Correlation Analysis 550
- CHAPTER 15 Multiple Regression Analysis and Model Building 597
- CHAPTER 16 Analyzing and Forecasting Time-Series Data 660
- CHAPTER 17 Introduction to Nonparametric Statistics 711
- CHAPTER 18 Introducing Business Analytics 742
- CHAPTER 19 Introduction to Decision Analysis
- Decision-Making Environments and Decision Criteria Certainty
- CHAPTER 20 Introduction to Quality and Statistical Process Control
- Introduction to Statistical Process Control Charts The Existence of Variation
N Critical values dL and du of the Durbin-Watson statistic D (Critical values are one-sided) 806. We believe that effective decision making depends on an understanding of the different types of data and the different data collection options that exist.
New to This Edition
We are well aware of how computer software is revolutionizing the field of business statistics. Excel 2016 Tutorials: The new Excel 2016 Tutorials guide students step-by-step on how to use Excel to perform the statistical analyzes introduced throughout the text.
Key Pedagogical Features
Pearson MyLab Statistics: The latest version of this proven student learning tool provides text-specific online homework and assessment options and offers a broad set of course materials with free-response exercises algorithmically generated for unlimited practice and mastery. Instructors can use Pearson MyLab Statistics' homework and test manager to select and assign their own online exercises and can import Test-Gen tests for added flexibility.
Student Resources Pearson MyLab
Course (access code required)
Resources for Success
In addition, Pearson MyLab Statistics includes access to www.statcrunch.com, a vibrant online community where users can access tens of thousands of shared data sets, create and run online surveys, perform complex analyzes using the powerful statistical software, and generate compelling reports. Statistical Software, Support, and Integration: Students can access a variety of support tools (Technology Instructional Videos, Technology Study Cards, and Technology Manuals for select titles) to learn how to effectively use statistical software.
Pearson MyLab
Statistics Accessibility
Student Online Resources
Instructor Resources
Instructor’s Solutions Manual
Test Item File
TestGen ®
Acknowledgments
Global Edition Acknowledgments
Recall any recent experiences you have had where you were asked to complete a written survey or answer a telephone survey.
WHY YOU NEED TO KNOW
Turning data into information is where business statistics come in—the statistical procedures presented in this text are those used to help turn data into information. You should gain an understanding of the where, why, and how of data and data collection, as the remaining chapters deal with techniques for turning data into useful information.
What Is Business Statistics?
Walmart collects and manages massive amounts of data about the operation of its stores around the world. Because data is the starting point for any statistical analysis, Chapter 1 is devoted to discussing various aspects of data, from how to collect data to the different types of data you will analyze.
Descriptive Statistics
Charts and Graphs Chapter 2 will discuss many different charts and graphs – such as the one shown in Figure 1.2, called a histogram. The bar graph shown in figure 1.3 shows the total number of textbooks sold divided into the two markets, business and social sciences.
Inferential Procedures
Skill Development
Business Applications
EXERCISES
Procedures for Collecting Data
Primary Data Collection Methods
The initial section of the survey should contain questions related to the central issue of the survey. Be sure to pretest the survey and spend extra time on the format and appearance of the survey instrument.
Other Data Collection Methods
Do you think this is the right or wrong thing for the government to do?”. Regardless of the procedure used for data collection, care must be taken to ensure that the data collected is accurate and reliable, and that it is the right data for the purpose at hand.
Data Collection Issues
EXERCISES
Populations, Samples, and Sampling Techniques Populations and Samples
For example, she can calculate the average waiting time for the sample of cars and then use that to infer what the average waiting time is for the population. However, if she selected a sample of cars from the population, the average waiting time for the sampled cars would be a statistic.
Sampling Techniques
EXERCISES
Computer Applications
Data Types and Data Measurement Levels
Quantitative and Qualitative Data
Time-Series Data and Cross-Sectional Data
Data Measurement Levels
EXERCISES
As part of an economic investigation, an analyst accessed data collected by the US. Examine the data in columns A-L and identify the level of data represented by the variables in each column.
A Brief Introduction to Data Mining Data Mining—Finding the Important,
All this data – referred to as big data – has created a need not only for highly skilled data scientists who can mine and analyze it, but also for managers who can make decisions using it. McKinsey reports that the use of big data "will become a key basis of competition and growth for individual firms." This will create a need for highly trained data scientists and managers who can use data to support their decision making.
Summary
Inferential statistics allow decision makers to draw conclusions about a large amount of data by examining a smaller subset of that data. It is important to know what type of data you have because the data type affects the kind of statistical procedures you can use.
Key Terms
Because electronic data storage is so inexpensive, organizations are collecting and storing larger volumes of data than ever before. Data mining involves the art and science of digging into data to identify patterns and conclusions that are not immediately apparent in the data.
Chapter Exercises Conceptual Questions
When you graduate, you'll find yourself on both ends of the data analytics spectrum. Throughout your business career, you will be both a producer and a consumer of descriptive statistical techniques known as charts, graphs, and tables.
Frequency Distributions and Histograms
On the other hand, you will also find yourself reading reports or listening to presentations made by others. You will create a competitive advantage for yourself throughout your career if you gain a solid understanding of the techniques introduced in Chapter 2.
Frequency Distributions
The level of education of the workforce in both cities is a key factor in the decision to move. Count the number of occurrences of each value of the variable and enter that value in the column labeled "Frequency."
Grouped Data Frequency Distributions
Largest value- Smallest value Number of classes Round the class width to a more convenient value. The number of classes is arbitrary, but will typically be between 5 and 20, depending on the volume of data.
Histograms
On the Insert tab, in the Charts group, click the Insert Statistic Chart arrow and click Histogram. On the Insert tab in the Charts group, select the Insert Statistic Chart option arrow, and then click Histogram.
Relative Frequency Histograms and Ogives
Place the quantitative variable on the horizontal axis and the relative frequencies on the vertical axis. Note that the relative frequency histogram has exactly the same shape as the frequency histogram.
Joint Frequency Distributions
EXERCISES
Construct a joint relative frequency distribution for these two variables and write a short report on the distribution. Develop a relative frequency and a cumulative relative frequency distribution for the weights using the same five classes created in part b.
Computer Software Exercises
Bar Charts, Pie Charts, and Stem and Leaf Diagrams Bar Charts
The PE ratio is calculated by dividing a share's price by the earnings of the company. A bar chart is developed by placing the seven years on the horizontal axis and constructing bars whose heights correspond to the values of the S&P PE ratio.
Pie Charts
The sum of the four dollar amounts on the pie chart was a meaningless number. In this case, a bar graph like in Figure 2.11 would have been more appropriate.
Stem and Leaf Diagrams
EXERCISES
Display data for each country as a percentage of the countries total population. Create a pie chart showing the percentage of total seat capacity for the five major airlines.
Line Charts
Line Charts, Scatter Diagrams, and Pareto Charts2.3
Use the Design tab in the chart tools to change the chart title, add the axis titles, and remove the grid lines. Construct the vertical axis with a scale appropriate for the range of values of the time series variable.
Scatter Diagrams
- EXERCISES
The data in the file called Gasoline Prices reflects the average price of regular unleaded gasoline in the state of California for 36 consecutive years. Describe the type of relationship between the year and the amount of federal flood insurance.
Equations
Server Downtime
The file titled Diesel$ contains the average on-highway diesel prices for the last Friday of the month in the years 2013–2015. The file Home-Prices contains information on single-family housing prices in 100 metropolitan areas in the United States.
Hudson Valley Apples, Inc
Pine River Lumber Company—Part 1
You must use statistical procedures to determine the validity of any claims you may wish to make about your prizes. To complete your descriptive toolkit, you need to be familiar with the key descriptive measures that are widely used to fully describe data.
Measures of Center and Location
You will need to combine the graphical tools discussed in Chapter 2 with the numerical measures presented in this chapter.
Parameters and Statistics
Population Mean
Thus, the average number of rooms rented on Sunday for the last eight weeks is 15,125. Collect data on the variable of interest for all items in the population.
Sample Mean
In addition to collecting data on the number of rooms rented on Sunday evenings, the manager of the San Carlo Hotel also collected data on room rental income generated and the number of complaints on Sunday evenings. Now the manager can report to the hotel owner for these eight Sunday evenings that the average number of rooms rented is 15.13 (rounded from 15,125).
The Impact of Extreme Values on the Mean
Note that Equation 3.2 is the same as Equation 3.1, except that we sum the sample values, not the population values, and divide by the sample size, not the population size. With only one value in the sample changed, the average is now significantly higher than before.
Median
Rounding up, the median is the fourth value from either end of the data set. Note that if the number of data values in a sample or population is equal, the mean is the average of the two middle values.
Skewed and Symmetric Distributions
Thus, the median is particularly useful as a measure of center when the data are highly skewed.1. The average professor salary is $155,000, the same value as in Example 3.4, when the high salary was not included in the data.
Mode
A common mistake is to think that the mode is the frequency of the value that occurs most often. Because of this feature, you must be careful when using the mode as a measure of the mean.
Applying the Measures of Central Tendency
Note that the skewness statistic is a small, positive number indicating a slightly positive (rightward) skewness of the tuition data. The higher the absolute value of the skewness statistic, the greater the skewness in the data.
Other Measures of Location
The next integer greater than i corresponds to the position of the pth percentile in the data set. Half of the data values in the box will be on either side of the median.
Developing a Box and Whisker Plot in Excel 2016
Data-Level Issues
EXERCISES
Calculate and interpret the mean, median and mode for the number of books borrowed by students. For the sample data, calculate the mean and the median and construct a box and whisker plot.
Measures of Variation3.2
Range
First, because we only use the high and low values to calculate the range, it is very sensitive to extreme values in the data. Second, no matter how many values are in the sample or population, the range is calculated from only two of those values.
Interquartile Range
Note that the interquartile range would be unchanged even if the values at the high or low end of the distribution were even more extreme than those shown in this sample data.
Population Variance and Standard Deviation
The population standard deviation is a parameter and will not change unless the population values change. The variance is squared in units, so in this example the population variance is 2.4082 weeks squared.
Sample Variance and Standard Deviation
EXERCISES
He wants to calculate the mean and standard deviation of the phone purchase price for each customer group. Again, he wants to calculate the mean and standard deviation of the phone purchase price for each customer group.
Using the Mean and Standard Deviation Together
Coefficient of Variation
So if we only know the mean and standard deviation for a set of data, the empirical rule gives us a tool to describe how the data is distributed if the distribution is bell-shaped. Eddey's Burgers Standard deviation can be thought of as a measure of distance from the mean.
Tchebysheff’s Theorem
Standardized Data Values
- EXERCISES
- SDW—Human Resources
- National Call Center
- Pine River Lumber Company—Part 2
- AJ’s Fitness Center
Calculate the mean and standard deviation of the amount of time a customer is served by each salesperson. Standard deviation is a measure of the average deviation of individual data elements about the mean;.
Chapters 1–3
However, you can use this review material to increase your understanding of the individual topics in the chapters. The method of descriptive statistical analysis that can be performed depends on the type of data and the level of data measurement for the variables in the data set.
A Typical Application Sequence
If the data is a ratio or an interval, you have the widest range of numerical tools at your disposal.
Integrative Application Exercises
EXERCISES
A lumber grader determined the resulting values for each of the 100 boards assuming that the rips determined by the scanner were made. The resulting data, in the Woodmill file, consists of manual tear values and scanner tear values for each of the 100 boards.
Review Case 1 State Department of Insurance
A sheet entitled "Description" contains an explanation of the data set and variables. As Herb's Chief Analyst, your job is to perform comprehensive data analysis and prepare a report for Herb to submit to the legislature.
Term Project Assignments
The Basics of Probability
On the night of the drawing, five balls are randomly selected and then placed in numerical order. A food processor manufacturer recognizes that there is a chance that one or more of its products will be substandard and leave the customer dissatisfied.
Important Probability Terms
EXERCISES
Based on the relative frequency assessment method, what is the probability that a randomly selected employee will be a woman. Based on the relative frequency assessment method, what is the probability that a mountain bike is brown.
The Rules of Probability Measuring Probabilities
Note that based on Equation 4.4 (Probability Rule 2), the sum of the probabilities of the individual possible outcomes is 1.0. The probability of overlapping results is represented by P1E4 and E62 and must be subtracted.
Conditional Probability
The conditional probability that someone aged at least 65 will have 50% or more of their pension assets in the stock market is therefore 0.061. You can also apply Probability Rule 6 to determine the probability that someone has 50% or more of their retirement assets in the stock market, given that he or she is at least 65 years old.
Multiplication Rule
The two branches that come from each of the first branches show the possible material options for the second product. The joint probability of two independent events is simply the product of the probabilities of the two events.
Bayes’ Theorem
- EXERCISES
- The Rules of Probability (pg. 165–188)
- Great Air Commuter Service
- Pittsburg Lighting
- Introduction to Discrete Probability Distributions Random Variables
What is the probability that at least one of the products will require service before the warranty expires? What is the probability that none of the four will need service before the warranty expires?
Mean and Standard Deviation of Discrete Distributions
