BUS 277 - Analytical Methods in Business

4 Credits, 4 Contact Hours
4 lecture periods 0 lab periods
Business statistic topics and applications. Includes a review of descriptive measures and continuous probability distributions; sampling distributions, hypothesis testing, statistical inference, analysis of variance, and an introduction to additional correlation and regression techniques with an emphasis placed on application to business cases using data-rich case analysis.  Also includes, providing an in-depth study of trend analysis, forecasting, and decision-making business applications.  Also includes Excel workshops for statistical analyses on business and economic cases accompanied by sample reports incorporating test results, its conclusions, and the communication of such conclusions.

Prerequisite(s): MAT 212  or higher, and BUS 205  
Recommendation: Completion of CIS 120  before enrolling in this course. If any recommended course is taken, see a financial aid or Veteran’s Affairs advisor to determine funding eligibility as appropriate.
Information: Basic Excel knowledge is required before enrolling in this course. CIS 120  meets this requirement.
  

1. Evaluate a trend and forecast future business performance.
2.  Analyze the outcome of an ANOVA.
3.  Use a computer system in order to develop a multiple regression equation and interpret the results.

1. Employ the coefficient of correlation to measure association between two quantitative variables.
2. Identify various trends and develop different business models for predictions.
3. Apply the chi-square distribution for purposes of testing whether or not two nominal-scale (categorical) variables could be independent.
4. Develop forecasting models to predict future trends based on historical data.
5. Develop a decision model to interpret and solve a business problem using decision theory techniques.
6. Analyze whether the means of three or more quantitative populations are equal (possible approaches include one-way ANOVA and two-way ANOVA).
7. Calculate and interpret linear least-squares regression equations summarizing the relationship between two variables using software.
8. Calculate and interpret the standard error of the estimate and the coefficient of determination.
9. Perform individual and joint tests of significance on regression coefficients.
10. Demonstrate the ability to estimate multiple regression models and interpret the coefficients.
11. Apply Excel in workshop settings to calculate statistics using large data sets.
12. Report results from statistical case studies in business and economics.

1. Relevance of Statistics
   1. Probabilities in Business
   2. Sampling and Interval Estimation
   3. Hypothesis Testing Means
2. Categorical Data Analysis
   1. One-way Chi-Square test
   2. Pearson’s Chi-Square test
3. Correlation and Regression Analysis
   1. Correlation
   2. Simple linear regression
   3. Multiple regression
   4. Goodness-of-fit measures
   5. Regression models with dummy variables
   6. Inference with regression
   7. Logistic Regression and predictive analayais
4. Time Series
   1. Smoothing techniques
   2. Trend Regression
   3. Time Series
5. Design of Experiments and Analysis of Variance (ANOVA)
   1. Single factor ANOVAs
   2. Two factor ANOVAs without interaction
   3. Two factor ANOVAs with interaction
6. Decision Theory

        a. Conditions of certainty vs. uncertainty

        b. Value of perfect information

VII. Conducting Statistical Analysis via Software Programs

a. Applying proper statistical test for case study problems

b. Using Excel for statistics

1. VIII. Results Reporting

a. Standardized reporting of results

b. Applications of results to business case studies in various majors