COURSE OUTLINE
OPTION: All
COURSE TITLE: Statistics for Economics and Business
COURSE CODE: ECOM2013
OBJECTIVE:
COURSE CONTENTS
CHAPTER 1:
INTRODUCTION TO STATISTICS (DATA AND STATISTICS)
CHAPTER 2:
DESCRIPTIVE STATISTICS: TABULAR AND GRAPHICAL PRESENTATIONS
CHAPTER 3:
DESCRIPTIVE STATISTICS: NUMERICAL MEASURES
CHAPTER 4:
INTRODUCTION TO PROBABILITIES
CHAPTER 5:
CORRELATION ANALYSIS AND REGRESSION ANALYSIS
DETAILED COURSE CONTENTS
CHAPTER 1:
INTRODUCTION TO STATISTICS (DATA AND STATISTICS)
1.1. Introduction
1.2. Data
1.2.1. Elements, variables and observations
1.2.2. Scales of measurement
1.2.3. Categorical and quantitative data
1.2.4. Cross-sectional and time series data
1.3. Data Sources
1.3.1. Existing sources
1.3.2. Statistical studies
1.3.3. Data acquisition errors
1.4. Descriptive Statistics
1.5. Statistical Inference
1.6. Ethical Guidelines for Statistical Practice
1
,1.7. Exercises
CHAPTER 2:
DESCRIPTIVE STATISTICS: TABULAR AND GRAPHICAL PRESENTATIONS
Introduction
2.1. Summarizing Categorical Data
2.1.1. Frequency distribution
2.1.2. Relative frequency and percent frequency distributions
2.1.3. Bar charts and pie charts
2.2. Summarizing Quantitative Data
2.2.1. Frequency distribution
2.2.2. Relative frequency and percent frequency distributions
2.2.3. Dot plot
2.2.4. Histogram
2.2.5. Cumulative distributions
2.2.6. Ogive
2.3. Cross tabulations and Scatter Diagrams
2.3.1. Cross tabulation
2.3.2. Simpson’s paradox
2.3.3. Scatter diagram and trendline
2.4. Exercises
CHAPTER 3:
DESCRIPTIVE STATISTICS: NUMERICAL MEASURES
Introduction
3.1. Measures of Location
3.1.1. Mean
3.1.2. Median
3.1.3. Mode
2
,3.1.4. Percentiles
3.1.5. Quartiles
3.2. Measures of Variability
3.2.1. Range
3.2.2. Interquartile range
3.2.3. Variance
3.2.4. Standard deviation
3.2.5. Coefficient of variation
3.3. Measures of Association between two Variables
3.3.1. Covariance
3.3.2. Interpretation of the covariance
3.3.3. Correlation coefficient
3.3.4. Interpretation of the correlation coefficient
3.4. Exercises
CHAPTER 5:
CORRELATION ANALYSIS AND REGRESSION ANALYSIS
CHAPTER 1:
INTRODUCTION TO STATISTICS (DATA AND STATISTICS)
1.1. Introduction
Frequently, we see the following types of statements in newspapers and magazines:
- The National Association of Realtors reported that the median price paid by first-time home
buyers is $165,000 (The Wall Street Journal, February 11, 2009).
- NCAA president Myles Brand reported that college athletes are earning degrees at record rates.
Latest figures show that 79% of all men and women student-athletes graduate (Associated
Press, October 15, 2008).
- The average one-way travel time to work is 25.3 minutes (U.S. Census Bureau, March 2009).
- A record high 11% of U.S. homes are vacant, a glut created by the housing boom and
subsequent collapse (USA Today, February 13, 2009).
3
, - The national average price for regular gasoline reached $4.00 per gallon for the first time in
history (Cable News Network website, June 8, 2008).
- The New York Yankees have the highest salaries in major league baseball. The total payroll is
$201,449,289 with a median salary of $5,000,000 (USA Today Salary Data Base, April 2009).
- The Dow Jones Industrial Average closed at 8721 (The Wall Street Journal, June 2, 2009).
The numerical facts in the preceding statements ($165,000, 79%, 25.3, 11%, $4.00, $201,449,289,
$5,000,000 and 8721) are called statistics. In this usage, the term statistics refers to numerical facts
such as averages, medians, percents, and index numbers that help us understand a variety of business
and economic situations. However, as you will see, the field, or subject, of statistics involves much
more than numerical facts. In a broader sense, statistics is defined as the art and science of collecting,
analyzing, presenting, and interpreting data. Particularly in business and economics, the information
provided by collecting, analyzing, presenting, and interpreting data gives managers and decision
makers a better understanding of the business and economic environment and thus enables them to
make more informed and better decisions. In this course, we emphasize the use of statistics for
business and economic decision making.
In today’s global business and economic environment, anyone can access vast amounts of statistical
information. The most successful managers and decision makers understand the information and know
how to use it effectively. In this section, we provide examples that illustrate some of the uses of
statistics in business and economics.
Accounting
Public accounting firms use statistical sampling procedures when conducting audits for their clients.
For instance, suppose an accounting firm wants to determine whether the amount of accounts
receivable shown on a client’s balance sheet fairly represents the actual amount of accounts receivable.
Usually the large number of individual accounts receivable makes reviewing and validating every
account too time-consuming and expensive. As common practice in such situations, the audit staff
selects a subset of the accounts called a sample. After reviewing the accuracy of the sampled accounts,
the auditors draw a conclusion as to whether the accounts receivable amount shown on the client’s
balance sheet is acceptable.
Finance
Financial analysts use a variety of statistical information to guide their investment recommendations.
In the case of stocks, the analysts review a variety of financial data including price/earnings ratios and
dividend yields. By comparing the information for an individual stock with information about the
stock market averages, a financial analyst can begin to draw a conclusion as to whether an individual
stock is over- or underpriced.
Marketing
Electronic scanners at retail checkout counters collect data for a variety of marketing research
applications.
Production
4
OPTION: All
COURSE TITLE: Statistics for Economics and Business
COURSE CODE: ECOM2013
OBJECTIVE:
COURSE CONTENTS
CHAPTER 1:
INTRODUCTION TO STATISTICS (DATA AND STATISTICS)
CHAPTER 2:
DESCRIPTIVE STATISTICS: TABULAR AND GRAPHICAL PRESENTATIONS
CHAPTER 3:
DESCRIPTIVE STATISTICS: NUMERICAL MEASURES
CHAPTER 4:
INTRODUCTION TO PROBABILITIES
CHAPTER 5:
CORRELATION ANALYSIS AND REGRESSION ANALYSIS
DETAILED COURSE CONTENTS
CHAPTER 1:
INTRODUCTION TO STATISTICS (DATA AND STATISTICS)
1.1. Introduction
1.2. Data
1.2.1. Elements, variables and observations
1.2.2. Scales of measurement
1.2.3. Categorical and quantitative data
1.2.4. Cross-sectional and time series data
1.3. Data Sources
1.3.1. Existing sources
1.3.2. Statistical studies
1.3.3. Data acquisition errors
1.4. Descriptive Statistics
1.5. Statistical Inference
1.6. Ethical Guidelines for Statistical Practice
1
,1.7. Exercises
CHAPTER 2:
DESCRIPTIVE STATISTICS: TABULAR AND GRAPHICAL PRESENTATIONS
Introduction
2.1. Summarizing Categorical Data
2.1.1. Frequency distribution
2.1.2. Relative frequency and percent frequency distributions
2.1.3. Bar charts and pie charts
2.2. Summarizing Quantitative Data
2.2.1. Frequency distribution
2.2.2. Relative frequency and percent frequency distributions
2.2.3. Dot plot
2.2.4. Histogram
2.2.5. Cumulative distributions
2.2.6. Ogive
2.3. Cross tabulations and Scatter Diagrams
2.3.1. Cross tabulation
2.3.2. Simpson’s paradox
2.3.3. Scatter diagram and trendline
2.4. Exercises
CHAPTER 3:
DESCRIPTIVE STATISTICS: NUMERICAL MEASURES
Introduction
3.1. Measures of Location
3.1.1. Mean
3.1.2. Median
3.1.3. Mode
2
,3.1.4. Percentiles
3.1.5. Quartiles
3.2. Measures of Variability
3.2.1. Range
3.2.2. Interquartile range
3.2.3. Variance
3.2.4. Standard deviation
3.2.5. Coefficient of variation
3.3. Measures of Association between two Variables
3.3.1. Covariance
3.3.2. Interpretation of the covariance
3.3.3. Correlation coefficient
3.3.4. Interpretation of the correlation coefficient
3.4. Exercises
CHAPTER 5:
CORRELATION ANALYSIS AND REGRESSION ANALYSIS
CHAPTER 1:
INTRODUCTION TO STATISTICS (DATA AND STATISTICS)
1.1. Introduction
Frequently, we see the following types of statements in newspapers and magazines:
- The National Association of Realtors reported that the median price paid by first-time home
buyers is $165,000 (The Wall Street Journal, February 11, 2009).
- NCAA president Myles Brand reported that college athletes are earning degrees at record rates.
Latest figures show that 79% of all men and women student-athletes graduate (Associated
Press, October 15, 2008).
- The average one-way travel time to work is 25.3 minutes (U.S. Census Bureau, March 2009).
- A record high 11% of U.S. homes are vacant, a glut created by the housing boom and
subsequent collapse (USA Today, February 13, 2009).
3
, - The national average price for regular gasoline reached $4.00 per gallon for the first time in
history (Cable News Network website, June 8, 2008).
- The New York Yankees have the highest salaries in major league baseball. The total payroll is
$201,449,289 with a median salary of $5,000,000 (USA Today Salary Data Base, April 2009).
- The Dow Jones Industrial Average closed at 8721 (The Wall Street Journal, June 2, 2009).
The numerical facts in the preceding statements ($165,000, 79%, 25.3, 11%, $4.00, $201,449,289,
$5,000,000 and 8721) are called statistics. In this usage, the term statistics refers to numerical facts
such as averages, medians, percents, and index numbers that help us understand a variety of business
and economic situations. However, as you will see, the field, or subject, of statistics involves much
more than numerical facts. In a broader sense, statistics is defined as the art and science of collecting,
analyzing, presenting, and interpreting data. Particularly in business and economics, the information
provided by collecting, analyzing, presenting, and interpreting data gives managers and decision
makers a better understanding of the business and economic environment and thus enables them to
make more informed and better decisions. In this course, we emphasize the use of statistics for
business and economic decision making.
In today’s global business and economic environment, anyone can access vast amounts of statistical
information. The most successful managers and decision makers understand the information and know
how to use it effectively. In this section, we provide examples that illustrate some of the uses of
statistics in business and economics.
Accounting
Public accounting firms use statistical sampling procedures when conducting audits for their clients.
For instance, suppose an accounting firm wants to determine whether the amount of accounts
receivable shown on a client’s balance sheet fairly represents the actual amount of accounts receivable.
Usually the large number of individual accounts receivable makes reviewing and validating every
account too time-consuming and expensive. As common practice in such situations, the audit staff
selects a subset of the accounts called a sample. After reviewing the accuracy of the sampled accounts,
the auditors draw a conclusion as to whether the accounts receivable amount shown on the client’s
balance sheet is acceptable.
Finance
Financial analysts use a variety of statistical information to guide their investment recommendations.
In the case of stocks, the analysts review a variety of financial data including price/earnings ratios and
dividend yields. By comparing the information for an individual stock with information about the
stock market averages, a financial analyst can begin to draw a conclusion as to whether an individual
stock is over- or underpriced.
Marketing
Electronic scanners at retail checkout counters collect data for a variety of marketing research
applications.
Production
4
