Faculty Of Engıneerıng
Industrıal Engıneerıng (Englısh)
Course Information
FORECASTING METHODS | |||||
---|---|---|---|---|---|
Code | Semester | Theoretical | Practice | National Credit | ECTS Credit |
Hour / Week | |||||
INE308 | Spring | 3 | 0 | 3 | 4 |
Prerequisites and co-requisites | None |
---|---|
Language of instruction | English |
Type | Elective |
Level of Course | Bachelor's |
Lecturer | Assist.Prof. Dr. Türker ERTEM |
Mode of Delivery | Face to Face |
Suggested Subject | None |
Professional practise ( internship ) | None |
Objectives of the Course | This course is an introduction to the widely used and effective methods of forecasting and regression. The aim is to introduce students ways to aid managerial decision making by applying a statistical approach and quantitative analysis. The emphasis will be upon the use of mathematical methodology and the written communication of statistical results. |
Contents of the Course | An introduction to forecasting. Basic statistical concepts. Regression Analysis: Simple linear regression. Multiple linear regression. Least squares estimates of parameters. Hypothesis testing and confidence intervals in linear regression models. Testing of models. Data analysis and appropriateness of models. Linear time series models. Moving average. Autoregressive and/or ARIMA models. Estimation, data analysis, and forecasting with time series models. Forecasting errors and confidence intervals. |
Learning Outcomes of Course
# | Learning Outcomes |
---|---|
1 | Students shall collect data for forecasting processes and analyses |
2 | Students shall analyse the relationship between the variabes |
3 | Students shall forecast the future by evaluating current variables |
4 | Students shall identify the form and direction of the relationship between the variables |
5 | Students shall make forcasting hypothesis |
Course Syllabus
# | Subjects | Teaching Methods and Technics |
---|---|---|
1 | I. An Introduction to Forecasting 1.1 Forecasting and Data 1.2 Forecasting Methods 1.3 Errors in Forecasting | lecturing, problem solving, discussing |
2 | 1.4 Choosing a Forecasting Technique 1.5 An Overview of Quantitative Forecasting Techniques | lecturing, problem solving, discussing |
3 | II. Basic Statistical Concepts 2.1 Populations 2.2 Probability 2.3 Random Samples and Sample Statistics 2.4 Continuous Probability Distributions | lecturing, problem solving, discussing |
4 | 2.5 The Normal Probability Distribution 2.6 The t-Distribution, the F-Distribution, and the Chi-Square Distribution | lecturing, problem solving, discussing |
5 | 2.7 Confidence Intervals for a Population Mean 2.8 Hypothesis Testing for a Population Mean | lecturing, problem solving, discussing |
6 | III. Simple Linear Regression 3.1 The Simple Linear Regression Model 3.2 The Least Squares Point Estimates 3.3 Point Estimates and Point Predictions | lecturing, problem solving, discussing |
7 | 3.4 Model Assumptions and Standard Error 3.5 Testing the Significance of the Slope and -Intercept 3.6 Confidence and Prediction Intervals | lecturing, problem solving, discussing |
8 | 3.7 Simple Coefficients of Determination and Correlation 3.8 An F-Test for the Model 3.9 Some Shortcut Formulas | lecturing, problem solving, discussing |
9 | IV. Multiple Linear Regression 4.1 The Linear Regression Model 4.2 The Least Squares Estimates, Point Estimation, and Prediction 4.3 The Mean Square Error and The Standard Error | lecturing, problem solving, discussing |
10 | 4.4 Model Utility: R^2, Adjusted R^2, and the Overall F-Test 4.5 Testing the Significance of an Independent Variable 4.6 Confidence and Prediction Intervals | lecturing, problem solving, discussing |
11 | 4.7 The Quadratic Regression Model 4.8 Interaction | lecturing, problem solving, discussing |
12 | 4.9 Using Dummy Variables to Model Qualitative Independent Variables 4.10 The Partial F-Test: Testing the Significance of a Portion of a Regression Model | lecturing, problem solving, discussing |
13 | VI. Time Series Regression 6.1 Modeling Trend by Using Polynomial Functions 6.2 Detecting Autocorrelation | lecturing, problem solving, discussing |
14 | 6.3 Types of Seasonal Variation 6.4 Modeling Seasonal Variation by Using Dummy Variables and Trigonometric Functions | lecturing, problem solving, discussing |
15 | ||
16 | Final Exam |
Course Syllabus
# | Material / Resources | Information About Resources | Reference / Recommended Resources |
---|---|---|---|
1 | Bowerman, B. L., O'Connell, R. T., and Koehler, A. B. Forecasting, Time Series, and Regression | Thomson Brooks/Cole Publishing | |
2 | Gilchrist, W. Statistical Forecasting | John Wiley & Sons Ltd | |
3 | Hamilton, J. D., Time Series Analysis | Princeton University Press |
Method of Assessment
# | Weight | Work Type | Work Title |
---|---|---|---|
1 | 30% | Mid-Term Exam | Mid-Term Exam |
2 | 30% | Mid-Term Exam | Mid-Term Exam |
3 | 40% | Final Exam | Final Exam |
Relationship between Learning Outcomes of Course and Program Outcomes
# | Learning Outcomes | Program Outcomes | Method of Assessment |
---|---|---|---|
1 | Students shall collect data for forecasting processes and analyses | 1͵4͵11 | 1͵2͵3 |
2 | Students shall analyse the relationship between the variabes | 1͵4͵11 | 1͵2͵3 |
3 | Students shall forecast the future by evaluating current variables | 1͵4͵11 | 1͵2͵3 |
4 | Students shall identify the form and direction of the relationship between the variables | 1͵4͵11 | 1͵2͵3 |
5 | Students shall make forcasting hypothesis | 1͵4͵11 | 1͵2͵3 |
Work Load Details
# | Type of Work | Quantity | Time (Hour) | Work Load |
---|---|---|---|---|
1 | Course Duration | 14 | 3 | 42 |
2 | Course Duration Except Class (Preliminary Study, Enhancement) | 14 | 1 | 14 |
3 | Presentation and Seminar Preparation | 0 | 0 | 0 |
4 | Web Research, Library and Archival Work | 0 | 0 | 0 |
5 | Document/Information Listing | 0 | 0 | 0 |
6 | Workshop | 0 | 0 | 0 |
7 | Preparation for Midterm Exam | 2 | 8 | 16 |
8 | Midterm Exam | 2 | 2 | 4 |
9 | Quiz | 0 | 0 | 0 |
10 | Homework | 0 | 0 | 0 |
11 | Midterm Project | 0 | 0 | 0 |
12 | Midterm Exercise | 0 | 0 | 0 |
13 | Final Project | 0 | 0 | 0 |
14 | Final Exercise | 0 | 0 | 0 |
15 | Preparation for Final Exam | 1 | 12 | 12 |
16 | Final Exam | 1 | 2 | 2 |
90 |