Jul 13, 2020
 HELP OHIO University Undergraduate Catalog 2019-20 [Archived Catalog] Print-Friendly Page (opens a new window)

# ISE 3040 - Fundamentals of Statistics

To prepare technology students to understand and use statistics to evaluate and make decisions about processes and results that they encounter in their engineering and technology jobs. Topics include probability distributions, sampling distributions, confidence intervals, hypothesis tests, ANOVA, and simple linear regression.

Requisites: MATH 1300 or 1350 or 163A or 2301 and WARNING: No credit for both this course and the following (always deduct credit for first course taken): ECON 3810 or GEOG 2710 or GEOL 3050 or ISE 3200 or MATH 2500 or PSY 1110 or QBA 2010
Credit Hours: 3
General Education Code: 2AS
Repeat/Retake Information: May be retaken two times excluding withdrawals, but only last course taken counts.
Lecture/Lab Hours: 3.0 lecture
Learning Outcomes:
• Calculate confidence intervals for mean, difference in means, variance, ratio of two variances, proportion, difference in two proportions.
• Calculate expected values and variance for discrete distributions.
• Calculate mean and variance for a random sample.
• Calculate required number of samples to achieve a specific statistical power for a hypothesis test for population means.
• Calculate statistical power for a hypothesis test for population means.
• Compare two populations for mean and variation using statistics from a random sample.
• Describe the parameters and the application of common probability functions: uniform (discrete), Binomial, and Normal.
• Determine best measure of central tendency for a sample from a known population distribution.
• Determine best methods for graphical presentation of data and statistical analyses.
• Distinguish between discrete and continuous random variables.
• Estimate population proportions using binomial tables and normal approximations to the binomial, for small and large samples respectively.
• Perform one-way ANOVA.
• Perform randomized complete block ANOVA.
• Perform simple linear regression.
• Perform single sample and 2-sample hypothesis tests for mean, variance, and proportion.
• Plot X, Y data and identify linear and transformable patterns.
• Use ANOVA techniques to identify weak regression models.
• Use Minitab and functions in Microsoft Excel for basic statistical analysis.
• Use tables to calculate probability for the following distributions: Normal, T, F, chi-square.