# |
Learning Outcomes |
1 |
will be able to define data and summarize the relationship between datas |
2 |
will be able to create and use graphs for categorical and numerical data, and to describe relationships between variables |
3 |
will be able to use measures of central tendency, variation, and shape, and use population summary measures |
4 |
will be able to assess outcomes and events in a probability experiment, apply basic rules of probability |
5 |
will be able to apply the concept of statistical independence and use Bayes' Theorem |
6 |
will be able to use mean and standard deviation for discrete and continuous random variables |
7 |
will be able to use and apply some special probability distributions, and the normal approximation to the binomial distribution |
8 |
will be able to determine the skewness and curtosis of datas |
# |
Subjects |
Teaching Methods and Technics |
1 |
Basic Statistics Concepts |
Online |
2 |
Data analysis |
Online |
3 |
Data Summarization Methods (Frequency, Table, Graphic) |
Online |
4 |
Data Summarization Methods (Central Tendency Measures) |
Online |
5 |
Data Summarization Methods (Central Distribution Measures) |
Online |
6 |
Moments |
Online |
7 |
Stiffness and Skewness |
Online |
8 |
Mid-Term Exam. |
Online exam |
9 |
Probability Theory |
Online |
10 |
Probability Theory |
Online |
11 |
Discrete Probability Distributions (Binomial Probability Distribution) |
Online |
12 |
Discrete Probability Distributions (Poisson Probability Distribution) |
Online |
13 |
Discrete Probability Distributions (Hypergeometric Probability Distribution) |
Online |
14 |
Continuous Probability Distributions (Normal Probability Distribution) |
Online |
15 |
Continuous Probability Distributions (Normal Probability Distribution) |
Online |
16 |
Final Exam |
Written exam |
# |
Learning Outcomes |
Program Outcomes |
Method of Assessment |
1 |
will be able to define data and summarize the relationship between datas |
4 |
1͵2 |
2 |
will be able to create and use graphs for categorical and numerical data, and to describe relationships between variables |
4 |
1͵2 |
3 |
will be able to use measures of central tendency, variation, and shape, and use population summary measures |
4 |
1͵2 |
4 |
will be able to assess outcomes and events in a probability experiment, apply basic rules of probability |
4 |
1͵2 |
5 |
will be able to apply the concept of statistical independence and use Bayes' Theorem |
4 |
1͵2 |
6 |
will be able to use mean and standard deviation for discrete and continuous random variables |
4 |
1͵2 |
7 |
will be able to use and apply some special probability distributions, and the normal approximation to the binomial distribution |
4 |
1͵2 |
8 |
will be able to determine the skewness and curtosis of datas |
4 |
1͵2 |