Course Name Code Semester T+U Hours Credit ECTS
Statistic For Managers MYU 510 0 3 + 0 3 6
Precondition Courses
Recommended Optional Courses
Course Language Turkish
Course Level yuksek_lisans
Course Type Optional
Course Coordinator Dr.Öğr.Üyesi UFUK KULA
Course Lecturers
Course Assistants Res. Assist. E.Elçin Günay
Course Category
Course Objective Introduction to the probability and basic statistical sampling methods
Course Content Statistical distributions, Point and interval estimations, One sample hypothesis tests, Two sample hypothesis tests, Reression analysis
# Course Learning Outcomes Teaching Methods Assessment Methods
1 Student will be able to construct visual data displays including the histogram and box plot according to central location and variability measurements, and interpret frequency distribution of data Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
2 Student will be able to determine probabilities from (discrete/continuous) probability mass functions and the reverse Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
3 Student will be able to calculate means, variances covariances and correlations for discrete/continuous random variables Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
4 Student will be able to use the concepts of sample mean, sample variance, population mean, population variance and Central Limit Theorem Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Simulation, Testing, Homework,
5 Student will be able to construct confidence intervals on the mean of a normal distribution, using appropriate distribution method Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
6 Student will be able to construct confidence intervals on a population proportion Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
7 Student will be able to structure engineering decision-making problems as hypothesis tests Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
8 Student will be able to test hypotheses on the mean and variance of a normal distribution using appropriate test procedure Lecture, Question-Answer, Discussion, Drilland Practice, Testing, Homework,
9 Student will be able to test hypotheses on a population proportion Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
10 Student will be able to test hypotheses on the difference in means of two normal distributions using appropriate test procedure Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
11 Student will be able to test hypotheses on the ratio of the variances of two normal distributions Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
12 Student will be able to test hypotheses on the difference in two population proportions Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
13 Student will be able to use the P-value approach for making decisions in hypotheses tests Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
14 Student will be able to test and construct the coefficients of the regression model. Lecture, Question-Answer, Discussion, Drilland Practice, Demonstration, Testing, Homework,
Week Course Topics Preliminary Preparation
1 Expected value variance of random variables
2 Some discrete probability distributions-I
3 Some discrete probability distributions-II
4 Some continuous probability distributions-I
5 Sampling distributions and Estimation-I
6 Sampling distributions and Estimation-II
7 Sampling distributions and Estimation-III
8 Hypothesis tests: one sample-I
9 Hypothesis tests: one sample-II
10 Hypothesis tests: two sample-I
11 Chi-square tests
12 Regression Analysis
13 ANOVA
14 ANOVA
Resources
Course Notes
Course Resources
Order Program Outcomes Level of Contribution
1 2 3 4 5
1
2
3
4
5
6
7
8
9
10
11
12
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 25
1. Ödev 37
2. Ödev 38
Total 100
1. Yıl İçinin Başarıya 20
1. Final 80
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 3 48
Hours for off-the-classroom study (Pre-study, practice) 16 3 48
Mid-terms 1 20 20
Assignment 1 25 25
Final examination 1 20 20
Total Workload 161
Total Workload / 25 (Hours) 6.44
dersAKTSKredisi 6