Part 1. Online Session: Math Review and Math Preparation for Course 5 minutes Introduction 45 minutes Reading and Practice Problem Assignment

Transcription

1 Course Schedule PREREQUISITE (Pre-Class) Advanced Education Diagnostic Test 10 minutes Excel 2007 Exercise SECTION 1. (Completed before face-to-face sections begin) (2 hours) Part 1. Online Session: Math Review and Math Preparation for Course 5 minutes Introduction 45 minutes Reading and Practice Problem Assignment Part 2. Online Session: Introduction to the Analysis ToolPak and Excel Data Analysis Demonstration 10 minutes Introduction 10 minutes Activating the Analysis ToolPak in Excel Exercise; 2.2 Exercise 40 minutes Running a Regression in Excel 2.3 Exercise; 2.4 Exercise; 2.5 Exercise SECTION 2. (Day 1 Morning) 8:00 8:30 30 minutes Sign-in 8:30 9:00 30 minutes Orientation (Classroom Rules and Procedures) Part 3. Introduction: Why Should Real Estate Appraisers Care about Statistics? 9:00 9:05 5 minutes Course Introduction 9:05 9:20 15 minutes Multiple Regression Model 3.1 Exercise 9:20 9:40 20 minutes Developing an Opinion of Value 3.2 Exercise 9:40 9:45 5 minutes How Could the Information We Developed in These Exercises Augment the Valuation Process? 9:45 9:55 10 minutes How and Why Might Clients Value Statistical Analyses by Appraisers? 3.3 Exercise 9:55 10:00 5 minutes Why Should Real Estate Appraisers Care about Statistics? 10:00 10:10 10 minutes MORNING BREAK xiii

2 SECTION 2. (Day 1 Morning, cont.) Part 4. Basic Measures: Central Tendency, Dispersion, and Symmetry 10:10 10:15 5 minutes Central Tendency 10:15 11:00 45 minutes Three Basic Measures of Central Tendency (3 Kinds of Averages) 4.1 Exercise; 4.2 Exercise; 4.3 Exercise; 4.4 Exercise; 4.5 Exercise 11:00 11:10 10 minutes MORNING BREAK 11:10 11:20 10 minutes Simple Mean v. Weighted Means 4.6 Exercise 11:20 11:25 5 minutes Samples and Populations 11:25 11:45 20 minutes The Standard Deviation 4.7 Exercise; 4.8 Exercise 11:45 11:50 5 minutes The Coefficient of Variation (COV) 4.9 Exercise 11:50 11:55 5 minutes Range and Interquartile Range 4.10 Exercise; 4.11 Exercise 11:55 12:10 15 minutes Box and Whisker Plots 4.1 Example; 4.12 Exercise 12:10 12:15 5 minutes Analyzing Shape 4.13 Exercise 12:15 1:15 60 minutes LUNCH SECTION 3. (Day 1 Afternoon) Part 5. Data Distributions 1:15 1:20 5 minutes Probability 5.1 Example, 5.2 Example 1:20 1:30 10 minutes Conditional Probability 5.1 Exercise 1:30 1:50 20 minutes Subjective Probability 5.2 Exercise 1:50 2:00 10 minutes Probability Density Functions 2:00 2:20 20 minutes The Uniform Probability Density Function 5.3 Example 2:20 2:30 10 minutes The Normal Probability Density Function 5.3 Exercise 2:30 2:40 10 minutes Assessing Normality 5.4 Exercise; 5.5 Exercise 2:40 2:55 15 minutes The Central Limit Theorem 5.6 Exercise 2:55 3:00 5 minutes Nonparametric Statistics 3:00 3:10 10 minutes AFTERNOON BREAK xiv

3 SECTION 3. (Day 1 Afternoon, cont.) Part 6. Research Design 3:10 3:15 5 minutes The Statistical Research Design Process 6.1 Exercise 3:15 3:20 5 minutes Construct a Research Hypothesis and Related Pair of Statistical Hypotheses 6.2 Exercise 3:20 3:30 10 minutes Research Validity 6.3 Exercise 3:30 3:35 5 minutes Reliability 3:35 3:45 10 minutes Credibility 6.4 Exercise 3:45 3:55 10 minutes AFTERNOON BREAK 3:55 4:15 20 minutes Sampling Error 6.1 Example 4:15 4:25 10 minutes Probability (Scientific) and Nonprobability Samples 6.5 Exercise 4:25 4:35 10 minutes Probability Sampling Methods 6.2 Example 4:35 4:50 15 minutes Controlling Sampling Error 4:50 5:00 10 minutes Begin Practice Test Sections 2 and 3 SECTION 4. (Day 2 Morning) Part 7. Charting Basics: Trendlines and Charts 8:30 9:15 45 minutes Review Section 3 (Practice Test Sections 2 and 3) 9:15 9:30 15 minutes Ordered Arrays, Frequency Distributions, and Charts 7.1 Example 9:30 9:40 10 minutes MORNING BREAK 9:40 10:00 20 minutes Converting a Frequency Distribution Table into a Percentage Distribution Table and Creating a Percentage Histogram 10:00 10:15 15 minutes Using Polygons to Compare Multiple Percentage Distributions 7.2 Example 10:15 10:35 20 minutes Summary Tables, Contingent Summary Tables, Bar Charts, and Pie Charts 7.1 Exercise 10:35 10:45 10 minutes MORNING BREAK 10:45 11:20 35 minutes Charting Time Series Data 7.2 Exercise; 7.3 Example; 7.3 Exercise 11:20 11:40 20 minutes Using Scatter Plots to Illustrate Correlation and to Plot a Trendline 7.4 Exercise 11:40 12:00 20 minutes Charting Ideals and Ethical Issues in Charting 7.5 Exercise 12:00 1:00 60 minutes LUNCH xv

4 SECTION 5. (Day 2 Afternoon) Part 8. Simple Linear Regression 1:00 1:15 15 minutes Simple Linear Equations 1:15 1:45 30 minutes How Does a Regression Model Think? 8.1 Exercise 1:45 2:05 20 minutes Assumptions Underlying Simple Linear Regression and How They Relate to Inference 8.2 Exercise 2:05 2:35 30 minutes Interpreting Regression Model t Statistics 8.3 Exercise 2:35 2:45 10 minutes AFTERNOON BREAK 2:45 2:50 5 minutes Sample Size Issues Related to Simple Linear Regression 2:50 3:30 40 minutes Predicting with a Simple Linear Regression Model and Development of Confidence Intervals 8.1 Example; 8.2 Example 3:30 3:40 10 minutes AFTERNOON BREAK 3:40 4:05 25 minutes Regression Error Patterns Indicating Violations of the Assumptions Underlying a Linear Regression Model 8.4 Exercise 4:05 5:00 55 minutes Practice Test, Review, Recap SECTION 6. (Day 3 Morning) Part 9. Trends and Forecasts 8:30 8:35 5 minutes Time-Series Data 8:35 8:45 10 minutes Approaches to Modeling Time-Series Data 8:45 9:15 30 minutes Simple Linear Time-Series Model 9.1 Example; 9.1 Exercise 9:15 10:15 60 minutes Curvilinear Time Series 9.2 Exercise; 9.2 Example; 9.3 Exercise 10:15 10:25 10 minutes MORNING BREAK 10:25 11:10 45 minutes Distance (Proximity) Effects 9.4 Exercise; 9.5 Exercise 11:10 11:20 10 minutes MORNING BREAK 11:20 12:00 40 minutes Causal Time-Series 9.3 Example 12:00 1:00 60 minutes LUNCH xvi

5 SECTION 7. (Day 3 Afternoon) Part 10. Multiple Linear Regression: Part I 1:00 1:10 10 minutes Multiple Linear Equations 1:10 1:50 40 minutes Underlying Assumptions and tests of Significance 10.1 Exercise; 10.1 Example: Modeling a Curvilinear Response Surface 1:50 2:10 20 minutes Curves in Multiple Linear Regression 10.1 Example 2:10 2;20 10 minutes AFTERNOON BREAK 2:20 3:20 60 minutes Some Model Building Issues 10.2 Example; 10.2 Exercise; 10.3 Exercise 3:20 3:35 15 minutes Overfitting and Omitted Variables 10.3 Example 3:35 3:45 10 minutes AFTERNOON BREAK 3:45 4:15 30 minutes Practice Test 4:15 5:00 45 minutes Review Test, Recap SECTION 8. (Day 4 Morning) Part 11. Multiple Linear Regression: Part II 8:30 9:15 45 minutes Indicator Variables 11.1 Exercise 9:15-9:25 10 minutes MORNING BREAK 9:25 9:45 20 minutes Indicator Variables 11.1 Exercise, cont. 9:45 10:45 60 minutes Interaction Variables 11.1 Example; 11.2 Exercise 10:45 10:55 10 minutes MORNING BREAK 10:55 12:00 65 minutes Using Dummy Variables to Account for Market Conditions in Panel Data 11.3 Exercise 12:00 1:00 60 minutes LUNCH xvii

6 SECTION 9. (Day 4 Afternoon) Part 12. Multiple Linear Regression Case Study 1:00 1:15 15 minutes Practice Test 1:15 1:25 10 minutes Case Introduction; Assignment; Suggested Ways to Deal with Data Limitations of Excel 1:25 1:35 10 minutes AFTERNOON BREAK 1:35 2:35 60 minutes Step-by-Step Instructions; Group Work on Model Building 2:35 2:45 10 minutes Presentation Development by Groups 2:45 3:00 15 minutes Group Presentations 3:10 3:10 10 minutes Wrap-up by Instructor 3:10 3:20 10 minutes AFTERNOON BREAK Part 13. Exam Content Review 3:20 3:35 15 minutes Basic Information for the Exam Guidance on Studying for the Final Exam Guidance on Taking the Final Exam Test-Taking Strategies 3:35 4:05 30 minutes Content Review: Course Objectives and Terms and Concepts to Remember Review Quiz 4:05 5:00 55 minutes Self-Study (Day 5 Morning) Exam 8:30 11:30 3-Hour Exam xviii