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Course Criteria
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3.00 Credits
Continuation of MAT 121/MAT 125. Topics include inference about the means, standard deviations and proportions, goodness of fit, analysis of variance, regression analysis, correlation, and nonparametric tests. In addition, students will learn to use SPSS, a statistical analysis software that is available for free through the Ram Cloud. Finally, students will hone their technical writing skills by summarizing their statistical analyses with written reports.
Prerequisite:
(ECO 251 or MAT 121 or MAT 125)
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3.00 Credits
The purpose of this course is to introduce students to the statistical methodology used in the analysis of data from a political survey. Topics will include sampling techniques, hypothesis testing, sample size calculation, categorical data analysis, simple linear regression, and ANOVA. There will be a field trip to the Center for Opinion Research at Franklin and Marshall College at the beginning of the semester.
Prerequisite:
(MAT 121 or PSC 200)
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3.00 Credits
In this course we will apply concepts such as regression, classification, clustering, decision trees and others to evaluate players and teams from baseball, basketball, football, hockey and soccer. We will also introduce the statistical programming language R in order to analyze recent (and large!) data sets.
Prerequisite:
(ECO 251 or MAT 121 or MAT 125)
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3.00 Credits
In this class students will learn the important role that probability and statistics play in the enjoyment and development of games ranging from blackjack and the lottery to Battleship and World of Warcraft. Statistical topics include descriptive statistics, probability, discrete random variables, and multivariate linear modeling. Throughout the course students will use statistical tools to not only develop optimal strategies while gaming but also to analyze the current trends in contemporary gaming, determine which factors correlate with a game's popularity, and how to develop algorithms for computer opponents.
Prerequisite:
(MAT 121 or MAT 125)
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3.00 Credits
Course will give students the ability to manage and manipulate data effectively, conduct basic statistical analysis, and generate reports and graphics primarily using the SAS Statistical Software Program.
Prerequisite:
(MAT 121 or MAT 125)
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3.00 Credits
This course will cover simple and multiple linear regression methods and linear time series analysis with an emphasis on fitting suitable models to data and testing and evaluating models against data.
Prerequisite:
(MAT 121 or MAT 125), (MAT 143 or MAT 145 or MAT 161)
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3.00 Credits
The purpose of this course is to guide students in learning how to design, conduct and analyze the results of scientific studies so that valid and objective inferences about the population are obtained. It will cover ANOVAs, block, factorial, and split plot designs, as well as response surface analysis.
Prerequisite:
(MAT 121 or MAT 125)
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3.00 Credits
Course will cover select topics in categorical analysis, nonparametrics and time series analysis. Emphasis will be placed on statistical programming, particularly simulations.
Prerequisite:
MAT 421, STA 311, STA 319, STA 320
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3.00 Credits
This course will provide an introduction to statistical learning and predictive modeling. Tools will be developed for visualizing and understanding complex data sets. All data analysis will be done using the statistical programming language R.
Prerequisite:
STA 319
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3.00 Credits
Course will synthesize lessons learned throughout the students career with the goal of preparing students for work as professional statisticians. Topics will include report writing, presentations, statistical consulting, sampling design, and resume writing.
Prerequisite:
(ENG 368 or ENG 371 or ENG 375)
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