Upon successful completion of the course, students will be able to: explain the importance of statistics to business; explain the references between quantitative and qualitative data and identify examples of each type of data; define and apply terms such as data sets, mean, median, mode, standard deviation, and variance; summarize and interpret data in a tabular format using frequency distributions and visually with histograms; define and apply the concept of a probability distribution and explain the properties of different distributions; differentiate between discrete and continuous probability distributions; define and apply the concept of a random variable and differentiate the population from a sample; relate the central limit theorem to sample size and normal distribution; describe and identify the different sampling methods, including systematic, stratified random, cluster, convenience, panel, and quota sampling and identify examples of each; use a point estimator from a sample to estimate the entire population; estimate intervals over which the population parameter could exist using sample data; apply hypothesis testing to test population parameters using one or two samples; identify the dependent and independent variables in the linear regression model; plot a regression line and explain how the regression coefficient shapes that line; and work with statistical data in a spreadsheet environment.