Statistics for Business and Economics Revised 12th Edition Anderson Solutions Manual
Contents
Chapter
- Data and Statistics
2. Descriptive Statistics: Tabular and Graphical Presentations
3. Descriptive Statistics: Numerical Measures
- Introduction to Probability
- Discrete Probability Distributions
- Continuous Probability Distributions
- Sampling and Sampling Distributions
- Interval Estimation
- Hypothesis Tests
- Statistical Inference about Means and Proportions with Two Populations
- Inferences about Population Variances
- Comparing Multiple Proportions, Test of Independence and Goodness of Fit
- Experimental Design and Analysis of Variance
- Simple Linear Regression
- Multiple Regression
16. Regression Analysis: Model Building
- Time Series Analysis and Forecasting
- Nonparametric Methods
- Statistical Methods for Quality Control
- Index Numbers
- Decision Analysis
- Sample Survey 1 / 4
Preface
The purpose of Statistics for Business and Economics is to provide students, primarily in the fields of business administration and economics, with a sound conceptual introduction to the field of statistics and its many applications. The text is applications-oriented and has been written with the needs of the nonmathematician in mind.
The solutions manual furnishes assistance by identifying learning objectives and providing detailed solutions for all exercises in the text.
Note: The solutions to the case problems are included in a separate manual.
Acknowledgements We would like to provide special recognition to Catherine J. Williams for her efforts in preparing the solutions manual.
David R. Anderson Dennis J. Sweeney Thomas A. Williams Jeffrey D. Camm James J. Cochran 2 / 4
Chapter 1 Data and Statistics
Learning Objectives
- Obtain an appreciation for the breadth of statistical applications in business and economics.
- Understand the meaning of the terms elements, variables, and observations as they are used in
statistics.
- Obtain an understanding of the difference between categorical, quantitative, crossectional and time
series data.
- Learn about the sources of data for statistical analysis both internal and external to the firm.
- Be aware of how errors can arise in data.
- Know the meaning of descriptive statistics and statistical inference.
- Be able to distinguish between a population and a sample.
- Understand the role a sample plays in making statistical inferences about the population.
- Know the meaning of the term data mining.
- Be aware of ethical guidelines for statistical practice. 3 / 4
Chapter 1
Solutions:
- Statistics can be referred to as numerical facts. In a broader sense, statistics is the field of study
dealing with the collection, analysis, presentation and interpretation of data.
- The ten elements are the ten cars
b. 5 variables: Size, Cylinders, City MPG, Highway MPG, and Fuel
c. Categorical variables: Size and Fuel
Quantitative variables: Cylinders, City MPG, and Highway MPG
d.Variable Measurement Scale
Size Ordinal Cylinders Ratio City MPG Ratio Highway MPG Ratio Fuel Nominal
- Average mpg for city driving = 182/10 = 18.2 mpg
- Average mpg for highway driving = 261/10 = 26.1 mpg
On average, the miles per gallon for highway driving is 26.1 – 18.2 = 7.9 mpg greater compared to city driving.
- 3 of 10 or 30% have four cylinder engines
- 6 of 10 or 60% use regular fuel
- The seven elements are the seven schools shown
- 5 variables: State, Campus Setting, Endowment, Applicants Admitted, and NCAA Division
c. Categorical variables: State, Campus Setting, and NCAA Division
Quantitative variables: Endowment and Applicants Admitted
- Average endowment = 74.6/7 = $10.657 billion
- Average percentage admitted = 111/7 = 15.86%
- 3 of 7 or 42.9% have NCAA Division III varsity teams
d. 3 of 7 or 42.9% have a City: Midsize campus setting
- Quantitative
- Categorical
- Categorical
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