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Aug 06, 2026
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ECON 2021 - Statistics for Business and Economics Credits: 3 Hours/Week: Lecture 3 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 None
Prerequisite(s): None Corequisite(s): None Recommendation: None
Major Content
- Comparisons involving means
- Comparisons involving proportions and a test of independence
- Continuous probability distributions.
- Data and statistics.
- Descriptive statistics: numerical measures
- Descriptive statistics: tabular and graphical presentations
- Discrete probability distributions
- Hypothesis tests
- Interval estimation
- Introduction to probability
- Multiple regression
- Sampling and sampling distributions
- Simple linear regression
Learning Outcomes At the end of this course students will be able to:
- explain the differences between the regression model, the regression equation, and the estimated regression equation
- perform regression analysis to develop an equation that estimates mathematically how two variables are related
- explain how the analysis of variance procedure can be used to determine if the means of more than two populations are equal
- analyze the difference between two population means when the samples are independent and when the samples are matched
- compute probabilities using a normal probability distribution. Understand the role of the standard normal distribution in this process
- discuss the role probability information plays in the decision making process
- formulate and test hypotheses about a population mean and/or a population proportion
- interpret tabular summarization procedures for quantitative data such as: frequency and relative frequency distributions, cumulative frequency and cumulative relative frequency distributions
- interpret summarization procedures for qualitative data such as : frequency and relative frequency distributions, bar graphs and pie charts
Minnesota Transfer Curriculum (MnTC): Goals and Competencies Competency Goals (MnTC Goals 1-6) None Theme Goals (MnTC Goals 7-10) None
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