Prerequisites

CIT 22000

Learn how to use samples to decide whether a population possesses a particular characteristic
Determine how unlikely it is that an observed sample could have come from a hypothesized population
Understand the two types of errors possible when testing hypotheses
Learn when to use one-tailed tests
Learn when to use two-tailed tests
Learn the five-step process of testing hypotheses
Understand how and when to use the normal distributions for testing hypotheses about population means and proportions

Learn how to use samples from two populations to test hypotheses about how the populations are related
Learn how hypothesis tests for differences between population means take different forms, depending on whether the samples are large or small
Distinguish between independent and dependent samples when comparing two means
Learn how to reduce a hypothesis test for the difference of means from dependent samples to a test about a single mean
Learn how to test hypotheses that compare the proportions of two populations having some attribute of interest
Understand how prob values can be used in testing hypotheses
Get a feel for the kinds of outputs computer statistical packages produce for testing hypotheses

Recognize situations requiring the comparison of more than two means or proportions
Introduce the chi-square and F distributions and learn how to use them in statistical inferences
Use the chi-square distribution to see whether two classifications of the same data are independent of each other
Use a chi-square test to check whether a particular collection of data is well described by a specified distribution
Use the chi-square distribution for confidence intervals and testing hypotheses about a single population variance
Compare more than two population means using analysis of variance
Use the F distribution to test hypotheses about two population variances

Learn how many business decisions depend on knowing the specific relationship between two or more variables
Use scatter diagrams to visualize the relationship between two variables
Use regression analysis to estimate the relationship between two variables
Use the least-squares estimating equation to predict future values of the dependent variable
Learn how correlation analysis describes the degree to which two variables are linearly related to each other
Understand the coefficient of determination as a measure of the strength of the relationship between two variables
Learn limitations of regression and correlation analyses and caveats about their use

Learn why forecasting changes that take place over time are an important part of decision making
Understand the four components of a time series
Use regression-based techniques to estimate and forecast the trend in a time series
Learn how to measure the cyclical component of a time series
Compute seasonal indices and use them to deseasonalize a time series
Recognize irregular variation in a time series
Deal simultaneously with all four components of a time series
Use time-series analysis for forecasting