| INDUSTRIAL PRODUCTS DESIGN | |||||
| Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 | ||
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| BME3005 | Biostatistics | Spring | 2 | 2 | 3 | 6 |
| This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
| Language of instruction: | English |
| Type of course: | Non-Departmental Elective |
| Course Level: | Bachelor’s Degree (First Cycle) |
| Mode of Delivery: | Face to face |
| Course Coordinator : | Dr. Öğr. Üyesi BURCU TUNÇ ÇAMLIBEL |
| Course Lecturer(s): |
Dr. Öğr. Üyesi BURCU TUNÇ ÇAMLIBEL |
| Recommended Optional Program Components: | None |
| Course Objectives: | - The course provides an introduction to selected important topics in biostatistical concepts and reasoning. This course represents an introduction to the field and provides a survey of data and data types. Specific topics include tools for describing central tendency and variability in data; methods for performing inference on population means and proportions via sample data; statistical hypothesis testing and its application to group comparisons; issues of power and sample size in study designs; and random sample and other study types; regression analysis, confidence intervals, correlations |
|
The students who have succeeded in this course; - The students who have succeeded in this course; I. Interpret statistical results correctly, effectively, and in context. II. Select an appropriate test for comparing two or more populations, and interpret and explain a p-value III. Understand the concept of the power of data. IV. Calculate and interpret confidence intervals for population means and proportions V. Understand regression analysis and correlation of variables. |
| Design of Experiments, Statistical programming: , Exploratory Data Analysis and Descriptive Statistics, Probability Theory, Sampling Distributions and the Central Limit Theorem, Estimation, Statistical Inference, Contingency tables, Nonparametric Tests, Power and sample size, ANOVA, Correlation and Regression, Logistic regression, Survival Analysis, applications on biological datasets. |
| Week | Subject | Related Preparation |
| 1) | Introduction to biostatistics | |
| 2) | Descriptive Statistics | |
| 3) | Probability Theory | |
| 4) | Sampling Distributions and the Central Limit Theorem | |
| 5) | ANOVA | |
| 6) | The Special Case of Two Groups: the t test | |
| 7) | Contingency tables, Chi Square Test, z-test | |
| 8) | Fisher Exact Test, Relative Risk, Odds Ratio | |
| 9) | Power and Sample size | |
| 10) | Paired t-test, Repeated Measures of Analysis of Variance, McNemar's Test | |
| 11) | Nonparametric Tests: Mann-Whitney Rank-Sum Test, Wilcoxon Signed-Rank Test | |
| 12) | Nonparametric Tests: Kruskal-Wallis Test, Friedman Test | |
| 13) | Confidence Intervals | |
| 14) | Correlation and Regression |
| Course Notes / Textbooks: | Primer of Biostatistics, Stanton A. Glantz, McGraw-Hill, 7th Edition Fundamental of Biostatistics, Bernard Rosner, Cengage Learning, 8th Edition |
| References: |
| Semester Requirements | Number of Activities | Level of Contribution |
| Quizzes | 5 | % 30 |
| Midterms | 1 | % 30 |
| Final | 1 | % 40 |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 60 | |
| PERCENTAGE OF FINAL WORK | % 40 | |
| Total | % 100 | |
| Activities | Number of Activities | Duration (Hours) | Workload |
| Course Hours | 14 | 3 | 42 |
| Study Hours Out of Class | 14 | 7 | 98 |
| Quizzes | 5 | 1 | 5 |
| Midterms | 1 | 3 | 3 |
| Final | 1 | 3 | 3 |
| Total Workload | 151 | ||
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | Having the theoretical and practical knowledge proficiency in the discipline of industrial product design | |
| 2) | Applying professional knowledge to the fields of product, service and experience design development | |
| 3) | Understanding, using, interpreting and evaluating the design concepts, knowledge and language | |
| 4) | Knowing the research methods in the discipline of industrial product design, collecting information with these methods, interpreting and applying the collected knowledge | |
| 5) | Identifying the problems of industrial product design, evaluating the conditions and requirements of problems, producing proposals of solutions to them | |
| 6) | Developing the solutions with the consideration of social, cultural, environmental, economic and humanistic values; being sensitive to personal differences and ability levels | |
| 7) | Having the ability of communicating the knowledge about design concepts and solutions through written, oral and visual methods | |
| 8) | To identify and apply the relation among material, form giving, detailing, maintenance and manufacturing methods of design solutions | |
| 9) | Using the computer aided information and communication technologies for the expression of industrial product design solutions and applications | |
| 10) | Having the knowledge and methods in disciplines like management, engineering, psychology, ergonomics, visual communication which support the solutions of industrial product design; having the ability of searching, acquiring and using the knowledge that belong these disciplines when necessary. | |
| 11) | Using a foreign language to command the jargon of industrial product design and communicate with the colleagues from different cultures | |
| 12) | Following and evaluating the new topics and trends that industrial product design needs to integrate according to technological and scientific developments |