BA-320 Applied Statistics for Business and Economics

GENERAL INFORMATION:

Course title: BA 320 Applied Statistics for Business and Economics
Campus: National	Initiator: Jean-Pierre Lukusa and George Mangonon	Date Initiated: June 1 2021
Course description: The course builds upon the fundamental concepts developed in the introductory statistics course and is motivated by problem-solving in diverse areas of business applications. Coverage spans from descriptive statistics, probability, hypothesis testing with emphasis on quality, productivity, and regression analysis. The student should be able to tackle basic applied statistics problems and possess fundamental knowledge needed to learn more in-depth statistical theory.

COURSE HOURS/CREDITS:

	Hours per Week		No. of Weeks		Total Hours		Semester Credits
Lecture	3	x	16	x	48	=	3
Laboratory		x		x		=
Workshop		x		x		=
			Total Semester Credits				3

PURPOSE OF COURSE:

[X] Degree requirement

[ ] Degree elective

[ ] Certificate

[ ] Other

PREREQUISITES:

MS150 Statistics

PSLOs OF OTHER PROGRAMS THIS COURSE MEETS:

PSLO#	Program
None

1) INSTITUTIONAL STUDENT LEARNING OUTCOMES (Check all that apply)

[ ]	1. Effective oral communication: capacity to deliver prepared, purposeful presentations designed to increase knowledge, to foster understanding, or to promote change in the listeners’ attitudes, values, beliefs, or behaviors.
[ ]	2. Effective written communication: development and expression of ideas in writing through work in many genres and styles, utilizing different writing technologies, and mixing texts, data, and images through iterative experiences across the curriculum.
[x]	3. Critical thinking: a habit of mind characterized by the comprehensive exploration of issues, ideas, artifacts, and events before accepting or formulating an opinion or conclusion.
[x]	4. Problem solving: capacity to design, evaluate, and implement a strategy to answer an open-ended question or achieve a desired goal.
[ ]	5. Intercultural knowledge and competence: a set of cognitive, affective, and behavioral skills and characteristics that support effective and appropriate interaction in a variety of cultural contexts.
[ ]	6. Information literacy: the ability to know when there is a need for information, to be able to identify, locate, evaluate, and effectively and responsibly use and share that information for the problem at hand.
[ ]	7. Foundations and skills for life-long learning : purposeful learning activity, undertaken on an ongoing basis with the aim of improving knowledge, skills, and competence.
[X]	8. Quantitative Reasoning: ability to reason and solve quantitative problems from a wide array of authentic contexts and everyday life situations; comprehends and can create sophisticated arguments supported by quantitative evidence and can clearly communicate those arguments in a variety of formats.

2) PROGRAM STUDENT LEARNING OUTCOMES (PSLOs): The student will be able to:

Apply skills concepts and techniques in main functional areas of business and accounting;
Interpret and use quantitative techniques in solving business problems and decision-making using technological tools;
Develop and apply effective intercultural oral and written communication skills appropriate for business; and
Recognize and assess basic legal, environmental, and ethical challenges confronting businesses in general.

3) COURSE STUDENT LEARNING OUTCOMES (CSLOs) (General): The student will be able to:

Conduct hypothesis tests and statistical inferences;
Test for the equality of three or more population proportions;
Perform analysis of variance under various experimental designs;
Estimate simple and multiple regression models and interpret the results;
Use time series analysis and forecasting models to make accurate forecasts; and
Use modern statistical packages in estimating applied statistical procedures, methods, and models.

4. COURSE STUDENT LEARNING OUTCOMES (CSLOs) (Specific): The student will be able to:

CSLO (General) 1: Conduct hypothesis tests and statistical inferences.
Student Learning Outcome (specific)	ISLO	PSLO	Assessment Strategies
1.1. Develop null (Ho) and alternative (Ha) hypotheses.	3, 4, 8	2	The student will complete a homework graded with a rubric focused on developing Ho and Ha hypotheses.
1.2. Conduct tests for one and two population(s) mean(s): known and unknown.	3, 4, 8	2	The student will complete an assignment graded with a rubric focused on conducting tests for known and unknown one and/or two population(s) mean(s).
1.3 Conduct nonparametric tests of hypotheses.	3, 4, 8	2	The student will complete a test graded with a rubric focused on conducting nonparametric tests of hypotheses.
CSLO (General) 2: Test for the equality of three or more population proportions.
Student Learning Outcomes (specific)	ISLO	PSLO	Assessment Strategies
2.1 Conduct tests for one and two population(s) proportion(s).	3, 4, 8	2	The student will complete an assignment graded with a rubric focused on conducting tests for one and/or two population(s) proportion(s).
2.2 Compare multiple proportions for three or more populations.	3, 4, 8	2	The student will complete an assignment graded with a rubric focused on comparing multiple proportions for three or more populations.
2.3 Conducting test of independence and goodness of fit.	3, 4, 8	2	The student will complete a test graded with a rubric focused on a conducting test of independence and goodness of fit.
CSLO (General) 3: Perform analysis of variance under various experimental designs.
Student Learning Outcomes (specific)	ISLO	PSLO	Assessment Strategies
3.1 Develop inferences about one or two population(s) variance(s).	3, 4, 8	2	The student will complete an assignment graded with a rubric focused on developing inferences about one or two population(s) variance(s).
3.2 Perform analysis of variance using the Analysis of Variance (ANOVA) and Multivariate Analysis of Variance (MANOVA) methods.	3, 4, 8	2	The student will complete a test graded with a rubric focused on performing analysis of variance using the ANOVA and MANOVA methods.
3.3 Apply experimental design method on a dataset.	3, 4, 8	2	The student will complete class based activities graded with a rubric focused on applying experimental design methods
CSLO (General) 4: Estimate simple and multiple regression models and interpret the results.
Student Learning Outcomes (specific)	ISLO	PSLO	Assessment Strategies
4.1 Theorize on simple and multiple regression model assumptions.	3, 4	2	The student will complete class based activities graded with a rubric focused on theorizing between simple and multiple regression model assumptions.
4.2 Construct simple linear and multiple regression models and regression on a dataset.	3, 4, 8	2	The student will complete an assignment graded with a rubric focused on constructing simple linear and multiple regression models and regression on a dataset.
4.3 Construct confidence and prediction intervals.	3, 4, 8	2	The student will complete an assignment graded with a rubric focused on constructing confidence and prediction intervals.
4.4 Estimate the coefficient of determination.	3, 4, 8	2	The student will complete an assignment graded with a rubric focused on estimating the coefficient of determination.
CSLO (General) 5: Use time series analysis and forecasting models to make accurate forecasts.
5.1 Interpret time series patterns given a dataset.	3, 4, 8	2	The student will complete class based activities graded with a rubric focused on interpreting time series patterns given a dataset.
5.2 Develop forecast accuracy.	3, 4, 8*	2	The student will complete class based activities graded with a rubric focused on developing forecast accuracy.
5.3 Perform movement of average and exponential smoothing.	3, 4, 8	2	The student will complete class based activities graded with a rubric focused on performing movement of average and exponential smoothing.
5.4 Make trend projections given a dataset.	3, 4, 8	2	The student will complete an assignment graded with a rubric focused on making trend projections given a dataset.
5.5 Experiment with seasonality and trend.	3, 4	2	The student will complete class based activities graded with a rubric focused on experimenting with seasonality and trend.
5.6 Compute time series decomposition on a given distribution.	3, 4, 8	2	The student will complete class based activities graded with a rubric focused on computing time series decomposition on a given distribution.
CSLO (General) 6: Use modern statistical packages in estimating applied statistical procedures, methods, and models.
6.1 Use statistical packages (i.e. Excel and SPSS) to solve case studies.	3, 4, 8	2	The student will complete class based activities graded with a rubric focused on usage of statistical packages (i.e. Excel and SPSS) to solve case studies.
6.2 Solve statistical problems in statistical packages (i.e. Excel and SPSS) and interpret produced outputs.	3, 4, 8	2	The student will complete a practical test graded with a rubric focused on solving statistical problems in statistical packages (i.e. Excel and SPSS) and interpret produced outputs.
6.3 Apply built-in statistical package(s) functions (e.g. Excel and SPSS) to solve statistical problems	3, 4, 8	2	The student will complete a practical test graded with a rubric focused on applying built-in statistical package(s) (e.g., Excel and SPSS) functions to solve statistical problems.

5) COURSE CONTENT:

Descriptive statistics
Basic probability concepts
Binomial, normal, t-test, and chi-square distributions
Hypothesis testing and confidence intervals for one and two means and proportions
Regression

6) METHOD(S) OF INSTRUCTION:

[X] Lecture [ ] Cooperative learning groups

[ ] Laboratory [ X ] In-class exercises

[ ] Audio visual [ X ] Demonstrations

[ X ] Other-Learning Managment System

7) REQUIRED TEXT(S) AND COURSE MATERIALS:

Anderson, David. R., et al. Statistics for Business and Economics. 14th ed., Cengage Learning, 2020 (or most recent edition).

Scientific calculator

8) REFERENCE MATERIALS:

None

9) INSTRUCTIONAL COSTS:

None.

10) EVALUATION:

Summative evaluation is accomplished by having the student complete midterm and final exams.

The student must achieve a grade of “C” or higher to pass the course.

11) CREDIT BY EXAMINATION:

None.

BA 320 Applied Statistics for Business and Economics	Endorsed by CC: 07/28/22
	Approved by VPIA: 07/29/22

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BA-320 Applied Statistics for Business and Economics

Hours per Week

No. of Weeks

Total Hours

Semester Credits