Jul 22, 2024  
2019-2020 Course Catalog 
2019-2020 Course Catalog [ARCHIVED CATALOG]

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ECON 2021 - Statistics for Business and Economics

Credits: 3
Hours/Week: Lecture None Lab None
Course Description: This course is an introduction to quantitative decision making. It will focus on probabilistic and statistical techniques as applied to business decision-making. Topics include probability, classical statistics, expected value, and sampling. This course includes the use of a statistical software package.
MnTC Goals

Prerequisite(s): None
Corequisite(s): None
Recommendation: None

Major Content
  1. Comparisons Involving Means
  2. Comparisons Involving Proportions and a Test of Independence
  3. Continuous Probability Distributions.
  4. Data and Statistics.
  5. Descriptive Statistics: Numerical Measures
  6. Descriptive Statistics: Tabular and Graphical Presentations
  7. Discrete Probability Distributions
  8. Hypothesis Tests
  9. Interval Estimation
  10. Introduction to Probability
  11. Multiple Regression
  12. Sampling and Sampling Distributions
  13. Simple Linear Regression

Learning Outcomes
At the end of this course students will be able to:

  1. Explain the differences between the regression model, the regression equation, and the estimated regression equation
  2. Perform regression analysis to develop an equation that estimates mathematically how two variables are related
  3. Explain how the analysis of variance procedure can be used to determine if the means of more than two populations are equal
  4. Analyze the difference between two population means when the samples are independent and when the samples are matched
  5. Compute probabilities using a normal probability distribution. Understand the role of the standard normal distribution in this process
  6. Discuss the role probability information plays in the decision making process
  7. Formulate and test hypotheses about a population mean and/or a population proportion
  8. Interpret tabular summarization procedures for quantitative data such as: frequency and relative frequency distributions, cumulative frequency and cumulative relative frequency distributions
  9. Interpret summarization procedures for qualitative data such as : frequency and relative frequency distributions, bar graphs and pie charts

Competency 1 (1-6)
Competency 2 (7-10)

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