OBU009 – Business Statistics

OBU009- BUSINESS STATISTICS
5-6 Semester Hours/8-9 Quarter Hours
Prerequisite: A college algebra or business algebra course that includes exponential and logarithmic functions. Note: Some schools require business calculus or calculus as a prerequisite for business statistics. Transfer students are advised to check the specific prerequisites for business statistics at their destination school.

Related TAGs: Business

Outcomes marked with an asterisk are essential and must be taught.

OBU009 may be met by a single course or by a sequence of courses covering the business statistics learning outcomes.

General Course Description:
This is a course of study that introduces statistical thinking and statistical methods to business students. The American Statistical Association has developed a set of six recommendations for the teaching of introductory statistics – these recommendations are known as the “Guidelines for Assessment and Instruction in Statistics Education.” The recommendations are as follows:

Emphasize statistical literacy and develop statistical thinking;
Use real data;
Stress conceptual understanding rather than mere knowledge of procedures;
Foster active learning in the classroom;
Use technology for developing conceptual understanding and analyzing data;
Use assessments to improve and evaluate student learning;

Using these recommendations as guiding principles, OBU009 should develop the more specific learning outcomes and skills summarized below:

Summary of Learning Outcomes and Academic Skills: Any introductory course of study in business statistics meeting the requirements for OBU009 must use business related materials to develop the following general learning outcomes and academic skills. It is expected that courses will support the use of technology and technology should be fully integrated in the course, especially in graphical depictions and regression analysis:

Give an overview of various types of sampling and the importance of randomization.
Understand how to organize and summarize data by using descriptive statistics and appropriate statistical graphics.
Understand the concept of probability and its applications in a business context.
Understand discrete and continuous random variables and be able to use their distributions to compute probabilities.
Understand the concept of sampling distributions.
Understand how to estimate population parameters using point and interval estimates.
Use hypothesis testing as a tool for statistical decision making in a business context.
Use hypothesis testing to compare two populations within the business context.
Understand and be able to test the hypothesis of independence of two categorical variables.
Understand and interpret simple linear regression analysis and use it in business decision making.
Understand and apply multiple linear regression analysis in a business context.
Understand and apply Analysis of Variance in a business context.

To qualify for OBU009 (Business Statistics), a course must cover as a minimum the essential learning outcomes, noted by an asterisk. A course in Business Statistics may also commonly include some of the listed nonessential learning outcomes. These optional topics should be included only if there is adequate course time to do so beyond giving primary course attention to the essential learning outcomes. At least 70% of the classroom instructional time has to be spent on the essential learning outcomes. The optional learning outcomes are learning experiences that enhance, reinforce, enrich or are further applications of the essential learning outcomes. If review of prerequisite course content is necessary, only a minimal amount of time should be devoted to such review.

Summary of Body of Knowledge Requirements for OBU009: Any introductory course of study in business statistics meeting the requirements for OBU009 must provide coverage of the following learning outcomes.

Outcomes marked with an asterisk are essential and must be taught.

1 . Give an overview of various types of sampling and the importance of randomization.

1.01 Understand selecting a simple random sample.*
1.02 Distinguish between observational and experimental studies.*
1.03 Understand basic principles of survey sampling*

2 . Understand how to organize and summarize data by using descriptive statistics and appropriate statistical graphics.

2.01 Use graphical methods to display a distribution of a variable and show relationships between two variables.*

2.02 Compute and interpret measures of central tendency and spread (variation), e.g., mean, median, mode, range, variance, standard deviation, percentiles and quartiles.*

2.03 Describe the shape of a distribution. Understand and apply the Empirical Rule for symmetric data and applications.*

3. Understand the concept of probability and its applications in a business context.

3.01 Understand the concept of probability and the properties that probabilities must satisfy. Perform computations using the rules of probability; addition and multiplication rules.*

3.02 Use conditional probability to understand the association between two categorical variables in two-way cross-tabulation tables. Interpret statistical independence of two variables.*

3.03 Understand Bayes’ Rule and use it to compute probabilities.

3.04 Understand the concept of statistical independence and use it to compute probabilities.*

4. Understand discrete and continuous random variables and be able to use their distributions to compute probabilities.

4.01 Understand discrete random variables and use their distributions to compute probabilities.*

4.02 Understand, compute, and interpret the expected value, variance, and standard deviation of a discrete random variable. In particular, discuss the binomial distribution and some of its business applications.*

4.03 Discuss Poisson, Geometric and Hypergeometric distributions and some of their business applications.

4.04 Understand the concept of a continuous random variable and density curve. Find probabilities and percentiles for uniform and normal densities. Use the normal probability distribution and some of its business applications such as control charts.*

4.05 Discuss exponential distributions and some of its business applications.

5. Understand the concept of sampling distributions.

5.01 Discuss sampling distributions for sample means and sample proportions. Use simulation to illustrate sampling distributions.*

5.02 Compute and interpret the mean and standard error of the sample mean and sample proportion.*

5.03 Use the Central Limit Theorem to understand the shape of a distribution and use it to compute probabilities.*

6. Understand how to estimate population parameters using point and interval estimates.

6.01 Compute point estimates of a population mean and population proportion and understand their properties.*

6.02 Understand the concept of a confidence interval for a population mean including its margin of error and level of confidence.*

6.03 Compute and interpret a confidence interval for a population mean (z-based and t-based intervals).*

6.04. Compute and interpret a z-based confidence interval for a population proportion.*

6.05 Be able to determine the sample size needed to give a specific margin of error and confidence level when estimating a population mean or proportion inference.*

7. Use hypothesis testing as a tool for statistical decision making in a business context.

7.01 Understand the concept and steps of performing a hypothesis test.*

7.02 Use both a critical value and p -value to test a hypothesis about a population mean and proportion.*

8. Use hypothesis testing to compare two populations within the business context.

8.01 Understand testing procedures for comparing two population means or two population proportions.*

8.02 Use independent samples and paired sample test procedures to compare two population means.*

9. Understand and be able to test the hypothesis of independence of two categorical variables.

9.01 Understand the Pearson test of independence and the Chi-Square sampling distribution.*

9.02 Interpret non-dependence in the contingency table when the hypothesis of independence is rejected.*

10. Understand and interpret simple linear regression analysis and use it in business decision making.

10.01 Use a scatter plot to assess the appropriateness of performing a simple linear regression. Understand the distributional assumptions of a linear regression model.*

10.02 Find and interpret the least squares estimates of the intercept and slope. Use the least squares line to make predictions.*

10.03 Find and interpret the correlation coefficient and the coefficient of determination. Understand the distinction between correlation and causation.*

10.04 Use inferential techniques to test the significance of the slope.*

10.05 Understand the residuals and use residual plots to test the assumptions of the model.*

10.06 Construct and interpret confidence intervals for the mean response and prediction intervals for future responses.

11. Understand and apply multiple linear regression analysis in a business context.

11.01 Understand the assumptions of a multiple linear regression model.*

11.02 Estimate and interpret the model parameters.*

11.03 Test the significance of model parameters and use a linear model to make predictions.*

11.04 Find and interpret the multiple coefficient of determination, R-squared, and adjusted R-squared.*

11.05 Construct and interpret confidence intervals for the mean response and prediction intervals for future responses.

12. Understand and apply Analysis of Variance in a business context.

12.01 Understand the assumptions of an ANOVA model.

12.02 Understand the F-procedure for testing the equality of population means in a one-way ANOVA.

12.03 In the case when the test is rejected, understand the use of multiple comparison methods.

Understand basic principles of statistical process control and interpreting control charts.