Module of Statistics for Economics
1. Module Code: ECON 226 Faculty: Education
2. Module Title: Statistics for Economics
3. Level: 2 Semester: I Credits:15
4. First Year of Presentation: 2018-2019. Administering Faculty: Education
5. Pre-Requisite: Descriptive Statistics (STAT 121)
Course Instructor: Dr.Rosa Padilla de Casamayor
Course Website: https://sites.google.com/a/upeu.edu.pe/rosa-padilla/ Course Venue/Time: A-106/Thursday, 8:00 - 10:50
Consultation Time: Monday 8:00 – 11.50, 3:00 – 6:00. At professor’s office
6. ALLOCATION OF STUDY AND TEACHING HOURS:
No
Criteria
Student
hours
Lecture
hours
1
Lectures
25
50
2
Seminar /workshops
10
10
3
Practical
classes/Laboratory(computer
LAB for statics software)
20
40
4
Structured exercises
25
10
5
Set reading
20
5
6
Self directed study
25
2
7
Assignments-preparation and
writing
20
8
8
Examination & participation
5
15
Total student hours
150
140
7. DESCRIPTION OF AIMS AND CONTENT
Course of theoretical-practical, belongs to the area of science. This module prepares students to describe, gather and shows how economic data can be described and analyzed and using statistical tools to make it. This course aims to introduce students to statistical concepts, tools and procedures involved in the collection, presentation, analysis and interpretation of numerical data using basic statistical techniques so as to enable them make effective business decisions in the context of economics applications. Graphical and numerical methods of description statistic, measures of central tendency,variability, shape and position. Probability and probability distributions are dealt with properties of mathematical binominal, poisson, normal, exponential and chi-square. Sampling methods, parameter estimation, confidence intervals and hypothesis tests. Ordinary least squares regression and Time-series Analysis.
The statistical analysis components of the SPSS software package will be used extensively in this course.
8. Learning Outcomes
At the end of the course, the student will be able to perform the following actions:
8.1 Knowledge and understanding:
Acquire knowledge of how to apply statistics in the economic context.
Have basic theoretical knowledge in probability theory and inference that is the foundation for statistical methods
Analyze real world scenarios and determine the appropriate type of analytical problem solving techniques to utilize.
8.2 Cognitive-intellectual-application of knowledge:
Critically analyze data sets and apply the tools of statistics to data in order to improve decision making.
Apply your knowledge of the basic concepts used in statistics in the context of economic applications Be able to review research reports and conclusions critically based on statistical data
8.3 Communication-ICT-Analytic Techniques-Practical Skills:
Students learn how to use a statistical calculator, Window Excel and statistical software to do their own quantitative research.
Demonstrate your familiarity with interpreting the output of the statistical software package.
Sample exams are posted in course website (https://sites.google.com/a/upeu.edu.pe/rosa-padilla/) I highly recommend that you work on the sample exams and discuss the answers with your
groupmates/classmates.
8.4 General Transferable Skills:
At the end of the course, the student will be able to
1. Understand and interpret the results of different statistical analyzes reported in the published reports of research.
2. Develop and refine decision-making skills by basing decision upon the outcome of statistical tests. 3. Analyze real world scenarios and determine the appropriate type of analytical problem solving
techniques to utilize.
4. Set up data, from a suitable quantitative study, for data analysis using Window Excel or SPSS statistical software.
5. Understand randomness, sampling techniques, and experiments.
6. The students will be able to read research papers that describe experimental and non-experimental studies with understanding. They will learn how to conduct several kinds of inferential tests, and will practice conducting them in order to gain hands on experience.
7. Strengthens Christian worldview through various curricular, co-curricular and social projection developed during the semester.
9. INDICATIVE CONTENT
Unit 1. Overview of statistics, data collection, describing data trough graphs and descriptive statistics
Session Date Objectives [LearningCapabilities] Contents to study in classroom classroom (Assignments)Learning outside the
1. 09/09
Define statistics and explain some of its uses in the economic context.
Review of Syllabus and course requirements. Why study Statistics? Course projects: these is an important part of the overall course, it is designed to replicate the application of statistics in the real-world.
List reasons for an educational student to study statistics.
Download Chapter 1 of the lecture notes (posted on the course web site). Work the project in groups of three; the project will be submitted on the 15th week
2. 15/09
Use basic terminology for describing data and samples. Recognize levels of measurement. Find print or electronic data sources.
Data collection: Definition, level of measurement, time series data, sampling concepts, data sources.
Solving Quiz one, is on the course website. Visit the web page of
3. 22/09
Describe basic elements
of survey design Basic elements of survey design, survey types. Design a data collection instrument (questionnaire)
Construct a
questionnaire with at least 3 general questions (demographic data), and five specific questions on any topic concerning Economy in Rwanda
4 29/09
Distinguish characteristics of univariate data.
Use an appropriate type of chart according the data.
Characteristics of univariate data through frequency distribution and graphs (box and whisker plot, stem-and-leaf, histograms, line, bar, pie)
Solving assignment one. Use excel to prepare an appropriate type of chart according the data.
5 06/10
Explain the concepts of center, variability, and shape.
Measures of: central tendency and variability.
Continue solving
assignment one. Use excel and SPSS to analyze and interpret the data.
6 13/10
Use Excel and SPSS to obtain descriptive statistics and visual and interpret the output.
Measures of shape: skewness and kurtosis, measures of position: percentiles, quartiles and box plots. What to do about outliers?
Continue solving
assignment one. Use excel and SPSS to analyze and interpret the data
Unit 2. Probability
Session Date Objectives [LearningCapabilities] Contents to study in classroom Learning outside theclassroom (Assignments)
1. 20/10
Describe the sample space of a random experiment.
Random experiments, Outcomes, Events. Definition of classical probability, Relative Frequency, Subjective Probability
Solving assignment two about probability.
2. 27/10
Apply the definitions and rules of probability. Calculate odds from given probabilities.
Used Bayes’ Theorem to calculated revised probabilities
Rules of probability complement of an event, union of two events, intersection of two events, general law of addition. Conditional probability, Independent events. Bivariate Probabilities, Odds, Bayes Theorem
Construct Mind map for the probability topic
3.
31/10 – 06/11
Evidence knowledge of the subject and Applies to real life problems. Exam answers individually With honesty and criterion.
Mid-Semester examination. Covers all material covered to date. Bring your student ID, a pencil, an eraser, a pen, a ruler with a centimeter scale, calculator.
The feedback is very important in the process of teaching and
learning, it is why the student has the opportunity to review their examination after being evaluated.
Unit 3. Parameter Estimation, Sample Designs and Sample size, Parametric Hypothesis Testing
Session Date Objectives [LearningCapabilities] Contents to study in classroom Learning outside theclassroom (Assignments)
1. 10/11
Comprehend the basic concepts used in estimating population parameters.
Introduction to Parameter
Estimation. Confidence intervals for the population mean and population proportion
Review and examples for chapter three
2. 17/11
Understand the concept of sampling distributions and know the sampling distributions of common statistics computed from a random sample.
Sample Designs, Estimating Sample Size and the Central Limit Theorem
Solving assignment three.
concepts used in testing
statistical hypotheses and Proportions with a single Population. interpret t tests for a single population.
4 01/12
Conduct tests of
hypotheses and interpret the results of the
significance of the Difference Between Two Sample Means
Statistical Inference about Means and Proportions with a two
Populations. Paired samples t-test.
Conduct and correctly interpret t tests for independent and related test.
Unit 4. Association between Variables Measured at the interval-Ratio Level and the Ordinal Level
Session Date Objectives [LearningCapabilities] Contents to study in classroom Learning outside theclassroom (Assignments)
1. 08/12
Be acquainted with simple tools used to study the relationship between two variables
Scattergrams, The Correlation Coefficient Pearson, Testing Pearson’s for significance, interpreting Coefficient of Determination
Conduct and correctly interpret correlation analysis. Solving assignment four.
2. 15/12
Estimate the regression coefficients of the simple linear regression model using the method of least squares; be aware of the basic principles or assumptions.
Estimation using the method of least squares and prediction, assumptions underlying linear regression, inference about the slope. testing the null hypothesis of “no association” with Gamma and Spearman’s Rho
Conduct and correctly interpret regression analysis.
Continue solving assignment four
Unit 5. Time-Series Analysis
Session Date Objectives [LearningCapabilities] Contents to study in classroom Learning outside theclassroom (Assignments)
1. 22/12
Define time-series data and their components, interpret a linear, exponential, or quadratic trend model
Time-Series Components. Trend Forecasting. Exponential Smoothing and Seasonality
Discuss the role of forecasting in the economy of the country.
Review and examples for chapter five
2.
09/01 – 17/01,
2017
The purpose of taking the final exam is that the students demonstrate their knowledge of the subject matter and as applied and evaluates the results.
Final Exam. Covers all material since the beginning of the course. Bring your student ID, pencil, an eraser, a pen, a ruler with a centimeter scale, the calculator.
The feedback is very important in the process of teaching and learning, it is why the student has the opportunity to review their examination after being evaluated.
10. LEARNING AND TEACHING STRATEGY
In the development of the subject will use the following methodology:
Theoretical class: Exhibition will include a first stage, and then develop constructive learning
with student participation, to strengthen cognitive contents.
Group dynamics: Students form groups to solve exercises and problems programmed for this
purpose. After submitting their report, will be the exposure of results obtained, so that reinforce
cognitive content, procedural and attitudinal also the respective feedback.
Consulting teacher:Guidance and counseling teacher for clarification of doubts and assistance
in carrying out their assignments.
The Course Project: The student will analyze a data set, demonstrating mastery of the concepts
and techniques learned in the class. The data can come from a source available to the student or
may be obtained from the Instructor. In either case, the data must be pre-approved by the
Instructor. Details of the project will be given during the course.
Integration Activities
1. Making decisions based on Christian principles axiological.
2. Daily Bible Study (Sabbath School lesson)
3. Using biblical references in academic
4. Conservation and promotion of the environment, etc.
11. ASSESSMENT STRATEGY
Assessment is a necessity in teaching otherwise the learner cannot take this process as a serious thing.
According to AUCA internal regulations, Continuous Assessment Tests (CAT) is composed of four
parts, which composed of 70% of the grade and the Final Exams 30% as reflected in the assessment
pattern table.
12. ASSESSMENT PATTERN
Component
Weighting (%) Learning Objective Covered
CAT
Class active participation
10
All Objectives
Course project (analysis and
write up of a data set, must be
approved by lecturer)
10
Objectives 8.1; 8.2 ; 8.3.2; 8.4
Quizzes and assignments
20
Objectives 8.1.1; 8.1.2
Mid-semester exam
30
Objectives 8.1.2; 8.1.3; 8.1.1
Final examination
30
Objectives 8.1; 8.3
Total
100
13. STRATEGY FOR FEEDBACK AND STUDENT SUPPORT DURING THE MODULE
14. INDICATIVE RESOURCES
Core Texts (These are available at the reference section of AUCA library)
Textbooks
Dancey, C. & Reide, J. (2007). Statistics without Math for Psychology. England: Pearson/Prentice Hall. (150 O173 2007)
Derek, W. (2008). Statistics for Business. United States of America: Butterworth-Heinemann. (330 Wal). Doane, D. & Seward, L. (2013). Applied Statistics in Business and Economics. 4th Ed. New York:
McGraw-Hill Irwin
Groebner, D; Shannon, P. (1985). Business Statistics a Decision-Making Approach. 2nd Ed. United States of America: Merrill. (519.5 G874).
Healey, J. (2005). Statistics a Tool for Social Research. 7th Ed. United States of America: Thompson. (519.5 H 434)
Hinkle, D., Wiersma, W. & Jurs, S. (2003). Applied Statistics for the Behavioral Sciences. 5th Ed. USA: University of Toledo.
Howell, D. (2004). Fundamental Statistics for the Behavioral Sciences. 5th Ed. USA: Thompson High Education.
Howitt, D. & Cramer, D. (2008). Statistics in Psychology. 4th Ed. England: Prentice Hall Europe. (150 H863). Kaplan, R. & Saccuzzo, D. (2007). Psychological Testing. Principles, Application and Issues. 6th Ed. Indian:
Thomson. (155 283).
Keller, G. & Warrack, B. (2000). Statistics for Management and Economics. 5th Ed. Canada: Duxbury. Levine, D. & Stephan, D. (2010). Even You Can Learn Statistics. 2nd Ed. United States of America: Pearson
Education. (519.5 Lev)
Lind, D., Marchal, Wathen, S. (2013). Basic Statistics for Business and Economics, 8th Ed. New York: McGraw-Hill. (330 LIN. CP.04).
Lind, D., Marchal, Wathen, S. (2008). Statistical Techniques in Business and Economics, 13th Ed. New York: McGraw-Hill. (519.5/ LIN. CP.02).
Neter, J. & Wasserman, W. (1974). Applied Linear Statistical Models. Regression, Analysis of Variance and Experimenter Designs. Paris: Richard D. Irwin, INC.
Newbold, P; Carlson, W; & Thorne, B. (2010). Statistics for Business and Economics. 7th Ed. United States of America: Pearson. (330 N533).
Wiersma, W. & Jurs, S. (2005). Research and Methods in Education. 8th Ed. United State: Pearson (Library)
Internet Links
Padilla, R. (2011). Course website: Class, data sets, syllabus, handouts, etc. Retrieved from: https://sites.google.com/a/upeu.edu.pe/rosa-padilla/
Professor Serna. (2011). Introduction to Probability. Retrieved from: https://www.youtube.com/watch?v=-8eSOmTPUbk
Professor Serna. (2011). Conditional Probability. Retrieved from: https://www.youtube.com/watch? v=XYCCWrON7gQ
Patrick JMT.(2013). Bayes’ Theorem/Law. Retrieved from: https://www.youtube.com/watch?v=E4rlJ82CUZI
Jbstatistics. (2012). An Introduction to Continuous Random Variables. Retrieved from: https://www.youtube.com/watch?v=OWSOhpS00_s
RStatsInstitute. (2011). Excel and Economics Statistics. Retrieved from:
https://www.youtube.com/watch?v=QkG9K7BYz_c&index=1&list=PL09A6B27CDCD97205
Garson, D. (2012). Online Textbook - One of the most comprehensive statistics texts on the internet
presented with a social science orientation. Retrieved from:
http://www2.chass.ncsu.edu/garson/pa765/statnote.htm
