Course Title Code Semester L+P Hour Credits ECTS
Probability And Statistics II * ENM   240 4 3 3 5

Prerequisites and co-requisites
Recommended Optional Programme Components None

Language of Instruction Turkish
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Prof.Dr. Rızvan EROL
To compass some of the discrete and continuous distributions,to do sampling distributions and to estimate interval and to test hypothesis,
Discrete random variables, Continuous random variables, Sampling distributions and estimation, Confidence intervals

Learning Outcomes

Course's Contribution To Program
NoProgram Learning OutcomesContribution
Has sufficient background on topics related to mathematics, physical sciences and industrial engineering.
Gains ability to use the acquired theoretical knowledge on basic sciences and industrial engineering for describing, formulating and solving an industrial engineering problem, and to choose appropriate analytical and modeling methods.
Gains ability to analyze a service and/or manufacturing system or a process and describes, formulates and solves its problems .
Gains ability to choose and apply methods and tools for industrial engineering applications.
Can collect and analyze data required for industrial engineering problems ,develops and evaluates alternative solutions.
Works efficiently and takes responsibility both individually and as a member of a multi-disciplinary team.
Can access information and to search/use databases and other sources for information gathering.
Appreciates life time learning; follows scientific and technological developments and renews himself/herself continuously.
Can use computer software in industrial engineering along with information and communication technologies.
Can use oral and written communication efficiently.
Uses English skills to follow developments in industrial engineering and to communicate with people in his/her profession.
Has a conscious understanding of professional and ethical responsibilities.
Has a necessary consciousness on issues related to job safety and health, legal aspects of environment and engineering practice.
Becomes competent on matters related to project management, entrepreneurship, innovation and has knowledge about current matters in industrial engineering.

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 Bernouli, binomial and multinomial distribution Source reading
2 Geometric, Negative binomial and Hypergeometric distribution Source reading
3 Poisson and discrete uniform distribution Source reading
4 Normal distribution, standart normal distribution Source reading
5 Normal approximation to binomial distribution, Continuos uniform and gamma distribution Source reading
6 Sampling distribution, Point estimation, Confidence interval on the population mean of normal distribution with a known variance Source reading
7 Chebyshev inequality, chi-square and F distribution Source reading
8 Midterm exam Source reading
9 Confidence interval on the mean of a population with normal distribution with unknown variance, Confidence interval on the variance of a population Source reading
10 Confidence interval on the difference in means of two populations with normal distribution, Source reading
11 Confidence interval on the ratio of variances of two normal distribution, Confidence interval on p, Confidence interval onthe difference of binomial parameters Source reading
12 Hypothesis test on the mean of a normal distribution Source reading
13 Hypothesis test on the variance of a normal distribution Source reading
14 Hypothesis test on the equivalence of variance of two normal distribution, Source reading
15 Hypothesis test on the binomial parameter and the difference of two binomial parameters Source reading
16-17 Final Exam Source reading

Recommended or Required Reading
Additional Resources