STATISTICAL APPLICATIONS FOR SOCIAL SCIENCES

Course Description

The course aims to instruct students to use word, excel and statistical packages in an integrated approach at an advanced level. In this course students will be presenting their statistical applications on Power Point in a professional manner; using statistical capabilities to get simple percentages to complex analyses of variance, multiple regressions, and general linear models as well as to generate tabulated reports, charts and plots of distributions and trends. The course makes statistical analysis more accessible fort he beginner and more convenient for the experienced user.It offers a simple and efficient spreadsheet-like facility for entering data and browsing the workingdata file.

STATISTICAL APPLICATIONS FOR SOCIAL SCIENCES

Evaluation Tools (Active Term)

No evaluation items have been defined.

Course outcomes

1. 01 Learning and applying the system of ideas regarding the economic thought and decision making
2. 02 Comprehending and being able to apply the cost-benefit principle,
3. 03 Having a clear idea about factors of production and production costs,
4. 04 Ability to apply opportunity cost, economic profit and production possibilities frontier concepts in problem solving
5. 05 Understanding and interpreting the demand and supply concepts in the market
6. 06 Ability to understand and evaluate the total utility and marginal utility concepts,
7. 07 Learning elasticity concept and being able to define the factors which affects the elasticity of demand and elasticity of supply.

Course Syllabus

Reference Books & Course Materials

1. 01 Mario F. Triola, (2015) Essentials of Statistics, Global Edition, 5th Edition Pearson

Learning Outcomes

1. L01 To assess the standard deviation and other measures of dispersion SOLO 5
2. L02 To predict the chances of happening and the elementary concept of probability theory SOLO 5
3. L03 To develop an understanding of the frequency distribution. SOLO 4
4. L04 To calculate the measurement of central tendency SOLO 2
5. L05 To summarise the data using graphical presentations and tables such as bar chart, pie charts, stem - leaf and frequency table SOLO 4
6. L06 To count the observation proportion under the normal curve, changes of scale, percentile and quartile. SOLO 2
7. L07 To define statistical applications for business and economics SOLO 2
8. L08 To classify grouped data with their interval classes SOLO 3
9. L09 By the end of the semester, students will be able to distinguish between the types of data in terms of the scales and the level of measurements, population, and sampling. To learn to calculate the central tendency, deviation and distribution of the observations and approximate the position of the values. In addition, the probability and chances that an event may happen will be theorized. SOLO 0
10. L10 To describe basic definitions about statistics SOLO 3
11. L11 To interpret the linear relationship between two interval scale variables by correlation coefficient 3 SOLO 3
12. L12 To formulate and interpret the regression equation and its coefficients SOLO 3
13. L13 Define statistical applications for business and economics. SOLO 3
14. L14 Develop an understanding on frequency distribution. SOLO 5
15. L15 Calcuate the measurement of central tendency SOLO 2
16. L16 Assess standarad deviation and other measures of dispersion SOLO 5
17. L17 Compute correlation coefficient and covarinace SOLO 3
18. L18 Discuss the chances that an event may happen or not. SOLO 5
19. L19 Define Basic rules such as addition rule, multiplication rules, conditional probabilities. SOLO 3

Program Outcomes

1. P01 Knowledge of mathematics, natural sciences, basic engineering, computer-based computation, and topics specific to the relevant engineering discipline.
2. P02 Ability to apply knowledge of mathematics, natural sciences, basic engineering, computer-based computation, and topics specific to the relevant engineering discipline to the solution of complex engineering problems.
3. P03 Ability to define complex engineering problems by using knowledge of basic sciences, mathematics, and engineering, while considering the relevant United Nations Sustainable Development Goals (SDGs) related to the problem addressed.
4. P04 Ability to formulate complex engineering problems using knowledge of basic sciences, mathematics, and engineering, while considering the relevant United Nations Sustainable Development Goals (SDGs) associated with the problem addressed.
5. P05 Ability to analyse and solve complex engineering problems using knowledge of basic sciences, mathematics, and engineering, while considering the relevant United Nations Sustainable Development Goals (SDGs) associated with the problem addressed.
6. P06 Ability to design creative solutions to complex engineering problems.
7. P07 Ability to design complex systems, processes, devices, or products in a way that meets present and future needs while considering realistic constraints and conditions.
8. P08 Ability to select and use appropriate techniques and resources—including estimation and modelling—for the analysis and solution of complex engineering problems, while being aware of their limitations.
9. P09 Ability to select and use modern engineering and computational tools—including estimation and modelling—for the analysis and solution of complex engineering problems, while being aware of their limitations.
10. P10 Ability to conduct literature research and use appropriate research methods for the investigation of complex engineering problems.
11. P11 Ability to design experiments for the investigation of complex engineering problems.
12. P12 Ability to conduct experiments, collect data, analyse results, and interpret findings for the investigation of complex engineering problems.
13. P13 Knowledge of the impacts of engineering practices on society, health and safety, the economy, sustainability, and the environment within the framework of the United Nations Sustainable Development Goals (SDGs).
14. P14 Awareness of the legal implications of engineering solutions within the framework of the United Nations Sustainable Development Goals (SDGs).
15. P15 Knowledge of ethical responsibility and adherence to the principles of professional engineering conduct.
16. P16 Awareness of acting impartially without discrimination in any matter and of being inclusive of diversity.
17. P17 Ability to work effectively as an individual.
18. P18 Ability to work effectively as a team member or leader in intra-disciplinary teams (face-to-face, remote, or hybrid).
19. P19 Ability to work effectively as a team member or leader in multidisciplinary teams (face-to-face, remote, or hybrid).
20. P20 Ability to communicate effectively in spoken form on technical matters, taking into account the diverse characteristics of the target audience (such as education, language, and profession).
21. P21 Ability to communicate effectively in written form on technical matters, taking into account the diverse characteristics of the target audience (such as education, language, and profession).
22. P22 Knowledge of professional practices such as project management and economic feasibility analysis.
23. P23 Awareness of entrepreneurship and innovation.
24. P24 Ability for independent and lifelong learning.
25. P25 Ability to adapt to new and emerging technologies.
26. P26 Lifelong learning ability that includes the capacity to think critically about technological changes.

Po-Lo Matrix