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Viewing: ST 305 : Statistical Methods

Last approved: Mon, 26 Oct 2015 23:16:39 GMT

Last edit: Mon, 26 Oct 2015 23:16:34 GMT

Change Type
ST (Statistics)
305
031138
Dual-Level Course
Cross-listed Course
No
Statistical Methods
Statistical Methd
College of Sciences
Statistics (17ST)
Term Offering
Fall and Spring
Offered Every Year
Spring 2015
Previously taught as Special Topics?
No
 
Course Delivery
Face-to-Face (On Campus)

Grading Method
Graded with S/U option
4
16
Contact Hours
(Per Week)
Component TypeContact Hours
Lecture4.0
Course Attribute(s)


If your course includes any of the following competencies, check all that apply.
University Competencies

Course Is Repeatable for Credit
No
 
 
Spencer Muse
Professor

Open when course_delivery = campus OR course_delivery = blended OR course_delivery = flip
Enrollment ComponentPer SemesterPer SectionMultiple Sections?Comments
Lecture5050NoBased on recent enrollment history.
Open when course_delivery = distance OR course_delivery = online OR course_delivery = remote
Prerequisites: MA 141 and (COS 100 or E 115); Corequisite: ST 307
Is the course required or an elective for a Curriculum?
Yes
SIS Program CodeProgram TitleRequired or Elective?
17STBSStatistics (BS)Required
17STMStatistics (minor)Elective
13MTHEDSTMathematics Education (BS): StatisticsRequired
Basic concepts of data collection, sampling, and experimental design. Descriptive analysis and graphical displays of data. Probability concepts, and expectations. Normal and binomial distributions. Sampling distributions and the Central Limit Theorem. Confidence intervals and hypothesis testing. Tests for means/proportions of two independent groups. One factor analysis of variance. Understanding relationships among variables; correlation and simple linear regression. Computer use is emphasized.

ST 305 is being restructured slightly. The course previously had a 50-minute, 0-credit problem session/computer lab. This is being deleted. A new corequisite of a SAS computing course (either the 1-credit ST 307 or the 3-credit ST 306) is being added. ST majors will take 306, minors and others will typically take 307.


ST 306 and 307 are new courses. 307 is being taught as a 495 section in Fall 2015, and will be changed to ST 307 during the semester as it has been approved by UCCC. ST 306 course action is forthcoming, and is intended to be taught for the first time in Fall 2016. 


No

Is this a GEP Course?
No
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Requisites and Scheduling
 
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Additional Information
Complete the following 3 questions or attach a syllabus that includes this information. If a 400-level or dual level course, a syllabus is required.
 
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College(s)Contact NameStatement Summary
College of EducationKathy Cabe TrundleThe proposed changes to ST 305 will add one more credit to undergrad programs requiring ST 305 (for the new 1-credit ST 307 corequisite). Contact hours will remain unchanged, since the 50-minute problem session/computer lab is being eliminated.
Taught as part of standard course load for Muse (Fall) and Tzeng (Spring).

Students will learn the basic tools of statistical practice: descriptive and graphical displays of data; design of samples and experiments; elementary probability and sampling theory; core statistical inference procedures.


Student Learning Outcomes

Describing Data



  • Display quantitative and categorical data effectively with graphs

  • Describe quantitative and categorical data effectively with numerical measures

  • Describe the key aspects of distributions of variables


Producing Data



  • Design basic experiments and sample using randomization

  • Recognize variations from simple random samples

  • Distinguish statistics from parameters, populations from samples


Probability



  • Perform calculations based on elementary rules of probability: the addition rule for disjoint events, multiplication rule for independent events, complement rule.

  • Use density curves to compute probabilities

  • Manipulate normal random variables to compute probabilities

  • Compute means and variances of random variables, and of linear functions of random variables


Sampling Distributions



  • Describe key properties of the sampling distribution of a sample mean

  • Use the sampling distribution of a sample mean to compute probabilities about means and sums of random variables

  • Clearly describe and use the Central Limit Theorem


Statistical Inference



  • Correctly apply one- and two-sample confidence interval and significance test procedures for population means

  • Clearly define confidence level, significance level, and power, and describe the impact of sample size and population variability on these quantities.

  • For the simple linear regression setting, correctly apply confidence interval and significance test procedures for the slope and intercept.

  • Apply and interpret prediction intervals and confidence intervals for mean response

  • Carry out ANOVA-based analyses of simple linear regression

  • Describe the differences between ANOVA-based analysis of simple linear regression and multiple regression

  • Carry out 1- and 2-way ANOVA analyses including analyses of main effects and interaction.



  • Demonstrate the ability to carry out all course analyses using SAS


Evaluation MethodWeighting/Points for EachDetails
Test652 highest exams 25 each; 1 lowest exam 15 points
Homework15Approximately 10 assignments per semester.
Final Exam20Cumulative final exam.
TopicTime Devoted to Each TopicActivity
Displaying and Describing Distributions2 weeks
Design of Samples and Experiments1 week
Intro to Probability Theory2 weeks
Intro to Sampling Theory2 weeks
Inference for Means and Proportions3 weeks
Simple Linear Regression2 weeks
Multiple Regression1 week
1-way ANOVA1 week
2-way ANOVA1 week

Key: 6234