# Course

Course Summary
Credit Type:
Course
ACE ID:
STAT-0001
Organization's ID:
#201
Organization:
Location:
Online
Length:
8 weeks (120 hours)
Dates Offered:
Credit Recommendation & Competencies
Level Credits (SH) Subject
Lower-Division Baccalaureate 3 introduction to statistics
Description

## Objective:

The course objective is to introduce the student to the fundamentals of probability and study design including statistical significance, categorical data and contingency tables, random sampling, the Bootstrap, confidence intervals and more. You will also learn basics of inference and association including confidence intervals for proportions, correlation and simple regression, multiple regression, and using regression models to make predictions.

## Learning Outcomes:

• specify the design of a basic randomized controlled study
• Conduct computer resampling simulations, including the bootstrap and permutation test, to model the effects of chance
• Construct confidence intervals
• Test hypotheses
• Explain the role of random sampling in research
• Calculate empirical probabilities and use the multiplication and addition rules
• Explain independence and conditional probabilities
• apply Bayes Rule
• apply sound statistical principles to the design of studies
• calculate confidence intervals and test hypotheses regarding proportions, means, and simple regression
• interpret these results
• apply statistically valid designs to basic studies for a variety of applications
• Perform hypothesis test regarding proportions and means
• Perform hypothesis tests for independent and pair data
• Fit, interpret and test hypotheses regarding a simple linear regression
• Fit, interpret and test hypotheses regarding a comparison of proportions or two means
• Fit, interpret and test hypotheses regarding contingency table with count data
• apply the correct statistical hypothesis test for a variety of applications
• apply statistically valid designs to basic studies
• Test hypotheses regarding proportions and means
• Analyze studies with paired data correctly
• Fit, interpret, and test hypotheses regarding a simple regression
• Fit, interpret, and test hypotheses regarding a comparison of proportions or two means
• fit, interpret, and test hypotheses regarding contingency table with count data

## General Topics:

• Study design, statistical significance
• Categorical data, contingency tables
• More probability, random sampling, the bootstrap
• Confidence intervals
• Confidence intervals for proportions
• 2-sample comparisons
• Correlation and simple (1-variable) regression
• Multiple regression
• Prediction
• K-nearest neighbors
Instruction & Assessment

## Instructional Strategies:

• Classroom Exercise
• Computer Based Training
• Discussion
• Practical Exercises
• Project-based Instruction

## Methods of Assessment:

• Other
• Quizzes
• online proctored exam

## Minimum Passing Score:

70%
Supplemental Materials

(STAT-0038)
(STAT-0021)