MTH 2450 - Business Statistics and Analytics

• Apply basic probability concepts and counting techniques
• Formulate events from statements in various applications
• Apply Venn diagrams to identify sets or compute probability of events
• Evaluate conditional probability and implement multiplication rule
• Apply Bayes’ Theorem
• Evaluate measures of central tendency and dispersion of a set of observations
• Recognize and utilize binomial and normal distributions
• Discern joint distributions of random variables
• Differentiate dependent random variables from independent random variables
• Visualize and identify outliers or any anomaly in data
• Provide point estimation for sample mean and sample variance, and interval estimation for population mean and population proportion
• Interpret reported statistics
• Distinguish type I and type II errors and provide examples
• Conduct hypothesis tests about one population mean, population proportion, and population variance
• Perform hypothesis tests about difference of two parameters
• Distinguish between linear relationship, nonlinear relationship, and no relationship for a sample of observations
• Compute and interpret Pearson’s correlation coefficient
• Construct simple linear regression from sample points
• Validate the fit of regressions

• Evaluation of algebraic formulas

• Multiplication rules and Bayes’ theorem
• Independence of events
• Discrete random variables and continuous random variables
• Probability distributions
• Measures of central tendency and dispersion
• One-sample hypothesis testing and statistical inference
• Two-sample hypothesis testing and statistical inference
• Linear regressions
• Analysis of variance (if time permits)