MQA 02ST00202 TABLE 3 SUMMARY OF INFORMATION ON EACH

MQA 02ST00202 TABLE 3 SUMMARY OF INFORMATION ON EACH






Name of Course: Specialised Financial Accounting

MQA 02-ST00202

Table 3: Summary of information on each course ST00202

Name of Course: Basic Statistic

Course Code: ST00202

Name(s) of academic staff: Norlita Ismail

Rationale for the inclusion of the course/module in the programme


Enable students to have enough basic knowledge in statistics to continue to other advance courses.


Semester and Year offered: 1st and 2nd semester, 1st Year

Total Student Learning Time (SLT)

Face to Face

Total Guided and Independent Learning

L = Lecture

T = Tutorial

P = Practical

O= Others

L

T

P

O

Refer To Appendix A ST00202

Credit Value: 2

Prerequisite (if any): -

Learning outcomes:

  1. Student will able to state the fundamental concepts of statistics.

  2. Student will understand the concept of probability, random variable, discrete probability distributions, continuous probability distributions, parameter estimations, hypothesis testing, linear regression and correlation.

  3. Student will able to practice the taught concepts in real-life application


Transferable Skills:


Teaching-learning and assessment strategy


Knowlegde of Discipline in mathematics with economics

Practical Skills / Practical / psychomotor in mathematics with economics

Problem solving and scientifics skills in mathematics with economics

Communication Skills

Sosial and team Skills and Responsibilities

Value, Attitude, Ethic and professionalisme

Information management and Longlife learning Skills

Managerial and Entrepreneurial Skills

Leadership Skills


Assessments

%

P1

P2

P3

P4

P5

P6

P7

P8

P9


Individual

100










a.

Group Assignment

30

/



/





/

b.

Mid-Term

20

/


/







c.

Final Exam

50

/


/








Synopsis:


This course covers basic statistics which comprises of topics such as: probability, random variable, discrete probability distributions, continuous probability distributions, parameter estimations, hypothesis testing, linear regression and correlation.



Mode of Delivery:

Lecture

Assessment Methods and Types:

The assessment for this course will be based on the following:

Component

Weight

Quiz

Mid Term Exam

Group Assignment

10%

20%

20%

Final Exam

50%

Total

100%


Mapping of the course/module to the Programme Aims

Mapping of the course/module to the Programme Learning Outcomes



Scientific and Technical

Knowledge


Specialization


Design Skills

Professional Skills


Life Long Learning



PEO1

PEO2

PEO3

PEO4

PEO5

1. To state the fundamental concepts of statistic

/

/




2. To understand the concept of probability, random variable, discrete probability distributions, continuous probability distributions, parameter estimations, hypothesis testing, linear regression and correlation

/

/

/

/

/

7. To practice the taught concepts in real-life application.

/


/





Mapping of the course/module to the Programme Learning Outcomes



Knowlegde of Discipline Area in mathematics with economics

Practical Skills / Practical / psychomotor in mathematics with economics

Problem solving and scientifics skills in mathematics with economics

Communication Skills

Sosial and team Skills and Responsibilities

Value, Attitude and professionalisme

Information management and Longlife learning Skills

Managerial and Entrepreneurial Skills

Leadership and Team Skills


P1

P2

P3

P4

P5

P6

P7

P8

P9

1. To state the fundamental concepts of statistic

/


/







2. To understand the concept of probability, random variable, discrete probability distributions, continuous probability distributions, parameter estimations, hypothesis testing, linear regression and correlation

/


/







3. To practice the taught concepts in real-life application.

/


/









Content outline of the course/module and the SLT per topic (Please Refer to Appendix A SM20103)


Chapter 1: PROBABILITY

Basic probability concepts, probability law, joint & marginal probability

Chapter 2: RANDOM VARIABLE

Random variable concepts, discrete univariate distributions, continuous univariate distributions, joint probability distributions for discrete variables, joint probability distributions for continuous variables, covariance, correlation and expectations.

Chapter 3: DISCRETE PROBABILITY DISTRIBUTIONS

Uniform, Binomial, Poisson, Geometric, Multinomial, Negative Binomial and Hypergeometric

Chapter 4: CONTINUOUS PROBABILITY DISTRIBUTIONS

Normal distribution, t-distribution, Chi-square distribution and F distribution.

Chapter 5: PARAMETER ESTIMATIONS

Point estimation, properties of estimators, method of moments, method of maximum likelihood and sampling distribution of means.

Chapter 6: ONE SAMPLE CONFIDENCE INTERVALS

Confidence intervals for the mean based on the normal distribution, confidence interval for the mean based on the t distribution, confidence interval for the proportion based on the normal distribution and confidence interval for variance.

Chapter 7: ONE SAMPLE TEST OF HYPOTHESIS

Tests of hypothesis for the mean based on the normal distribution, test of hypothesis for the mean based on the t distribution, test of hypothesis for the proportion based on the normal distribution and test of hypothesis for variance.

Chapter 8: TWO SAMPLE CONFIDENCE INTERVALS

Confidence intervals for the difference between two population means based on the normal distribution and t distribution, confidence interval for the difference between two population proportions based on the normal distribution and confidence interval for the ratio between two population variances.

Chapter 9: TWO SAMPLE TESTS OF HYPOTHESIS

Tests of hypothesis for the difference between two population means based on the normal distribution and t distribution, tests of hypothesis for the difference between two population proportions based on the normal distribution and tests of hypothesis for the ratio between two population variances.

Chapter 10: LINEAR REGRESSION AND CORRELATION

The simple linear regression model, residual analysis and correlation.

  • Main references supporting the course

1. Bluman, A.G. 2009. Elementary Statistics A Step by Step Approach.7th ed. Mc Graw Hill. New York

2. Ahmad Syukri Y., Amran A., Darmesah G and Chin Su Na. Problems & Solutions in Statistics for Engineers & Scientists. 2008. Prentice Hall.

3. Wackerly, D.D., Mendenhall III, W., and Scheaffer, R.L. 2002. Mathematical Statistics with Applications, 6th Edition. Thomson Learning:South Western Ohio.

4. Walpole and Myers. 2001. Probability and Statistics (6th edition). Prentice Hall. New Jersey.

5. Triola M.F. 2001. Essentials of Statistics. Addison-Wesley Publishing Company. USA.

6. Ajit C. Tamhane and Dorothy D. Dunlop. 2005. Statistics and Data Analysis

from Elementary to Intermediate. Prentice Hall. USA


Other additional information







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