Introductory Statistics for Business and Economics: Theory, Exercises and Solutions – Jan Ubøe – 1st Edition

1 Descriptive Statistics
1.1 Population and Samples
1.2 The Median
1.3 Quartiles and Mode
1.4 Relative Frequency and Histograms
1.5 The Mean
1.6 Sample Variance and Sample Standard Deviation
1.7 Sample Covariance and Coefficient of Variation
1.8 Using Excel
1.9 Summary of Chap. 1
1.10 Problems for Chap. 1

2 Probability
2.1 Sample Space
2.2 Probability
2.2.1 Events
2.2.2 Uniform Probability
2.2.3 Set Theory
2.2.4 Computing Probabilities
2.2.5 The Negation Principle
2.3 Summary of Chap. 2
2.4 Problems for Chap. 2

3 Combinatorics
3.1 Counting Combinations
3.1.1 Ordered Selections
3.1.2 Unordered Choices Without Replacement
3.1.3 Combinatorial Probabilities
3.2 Summary of Chap. 3
3.3 Problems for Chap. 3

4 Conditional Probability
4.1 Conditional Probability
4.1.1 Computing Conditional Probabilities
4.1.2 Splitting the Sample Space
4.1.3 Probability Trees
4.2 Subjective Probabilities
4.3 Independence
4.4 Summary of Chap. 4
4.5 Problems for Chap. 4

5 Random Variables, Mean, and Variance
5.1 Random Variables
5.2 Expectation
5.2.1 Computing Expectations
5.2.2 General Expectations and Variance
5.3 Some Simple Facts About Option Pricing
5.3.1 Hedging Portfolios
5.4 Summary of Chap. 5
5.5 Problems for Chap. 5

6 Joint Distributions
6.1 Simultaneous Distributions
6.2 Covariance
6.2.1 An Alternative Formula for the Covariance
6.2.2 Sums of Random Variables
6.3 Summary of Chap. 6
6.4 Problems for Chap. 6

7 Basic Probability Distributions
7.1 The Indicator Distribution
7.2 The Binomial Distribution
7.3 The Hypergeometric Distribution
7.4 The Poisson Distribution
7.5 The Normal Distribution
7.5.1 The General Normal Distribution
7.5.2 Standardizing Random Variables
7.5.3 The Central Limit Theorem
7.5.4 Integer Correction
7.5.5 Normal Approximation of Hypergeometric
and Poisson Distributions
7.5.6 Summing Normal Distributions
7.5.7 Applications to Option Pricing
7.6 Summary of Chap. 7
7.7 Problems for Chap. 7

8 Estimation
8.1 Estimation
8.1.1 Estimators
8.1.2 Reporting Estimates
8.1.3 The Measurement Model
8.2 Confidence Intervals
8.2.1 Constructing Confidence Intervals
8.2.2 The t-Distribution
8.3 The Lottery Model
8.4 Summary of Chap. 8
8.5 Problems for Chap. 8

9 Hypothesis Testing
9.1 Basic Ideas
9.2 Motivation
9.3 General Principles for Hypothesis Testing
9.4 Designing Statistical Tests
9.4.1 One-Sided and Two-Sided Tests
9.4.2 Confidence Intervals and Hypothesis Testing
9.4.3 P-Value
9.5 Summary of Chap. 9
9.6 Problems for Chap. 9

10 Commonly Used Tests
10.1 Testing Binomial Distributions
10.2 t-Test for Expected Value
10.3 Comparing Two Groups
10.3.1 t-Test for Comparison of Expectation in Two Groups
10.3.2 t-Test Executed in Excel
10.3.3 t-Test for Comparison of Expectation in Two Groups, Paired Observations
10.3.4 t-Test with Paired Observations Executed in Excel
10.4 Wilcoxon’s Distribution Free Tests
10.4.1 The Wilcoxon Signed-Rank Test
10.4.2 Comparison of t-Tests and Wilcoxon Test
10.5 The U-Test for Comparison of Success Probabilities
10.6 Chi-Square Test for Goodness-of-Fit
10.6.1 The Chi-Square Test Executed in Excel
10.7 The Chi-Square Test for Independence
10.7.1 The Chi-Square Test for Independence Executed in Excel
10.8 Summary of Chap. 10
10.9 Problems for Chap. 10

11 Linear Regression
11.1 Linear Correspondence
11.2 Linear Regression
11.3 Residuals and Explanatory Power
11.3.1 Naming Variables
11.4 Hypothesis Testing in the Regression Model
11.5 Prediction/Estimation
11.6 Regression Using Excel
11.7 Multiple Regression
11.7.1 Explanatory Power
11.8 Causality
11.9 Multicollinearity
11.10 Dummy Variables
11.11 Analyzing Residuals
11.11.1 Histogram
11.11.2 Normal Score Plot
11.11.3 Residuals in Observed Order
11.11.4 Residuals Sorted with Respect to Size
11.12 Summary of Chap. 11
11.13 Problems for Chap. 11

Solutions
Index