Course

Course Summary
Credit Type:
Course
ACE ID:
OTLR-0003
Organization:
Outlier.org
Location:
Online
Length:
7 weeks (140-210 hours) or 14 weeks (140-210 hours)
Dates Offered:
Credit Recommendation & Competencies
Level Credits (SH) Subject
Lower-Division Baccalaureate 3 general statistics
Description

Objective:

The course objective is to teach foundational descriptive and inferential statistical procedures. Topics covered include descriptive statistics; probability; discrete and continuous random variables; the normal distribution; the central limit theorem; confidence intervals; hypothesis testing with one and two samples; categorical data analysis; the chi-square distribution; linear regression; correlation; f-distribution; and one-way ANOVA. Students will be introduced to statistical tools including Desmos and R.

Learning Outcomes:

  • use descriptive statistics to analyze statistical data sets
  • explain basic probability outcomes
  • discuss concepts of experimental design
  • evaluate the linear association for a set of bivariate data
  • use inferential statistical procedures (i.e. hypothesis testing, confidence intervals, and the analysis of variance) to make conclusions
  • use R proficiently and apply basic statistical techniques to a variety of subjects with the aid of R statistical programming language to appropriately analyze quantitative data

General Topics:

  • The statistical process
  • Data and sampling
  • Experimental design and ethics
  • Graphs for visualizing data
  • Frequency distributions and histograms
  • Correlation coefficients
  • Outliers and other factors
  • Impacting correlation
  • Computing correlation and finding significance
  • Linear equations
  • The regression equation
  • Prediction
  • ANOVA
  • The F-distribution and the F-ratio
  • Measures of center
  • Measures of spread
  • Measures of location and box plots
  • Basics of probability
  • Rules of probability
  • Contingency tables
  • Introduction to random variables and probability distributions
  • Expectations of discrete random variables
  • Binomial distribution
  • Continuous random variables and the uniform distribution
  • Expectations of continuous random variables
  • The normal distribution
  • Law of large numbers and sampling variability
  • Central limit theorem for means and sums
  • What are interval estimates
  • Interval estimates using the normal distribution
  • Interval estimates using the student's t-distribution
  • Interval estimates using population
  • Proportions
  • Hypothesis testing, type I and II errors
  • Making decisions about hypotheses
  • Hypothesis testing examples
  • Understanding multiple scores and multiple groups
  • Matched or paired samples
  • Independent samples
  • Categorical data analysis
  • The Chi-square distribution
Instruction & Assessment

Instructional Strategies:

  • Audio Visual Materials
  • Computer Based Training
  • Discussion
  • Lectures
  • Practical Exercises

Methods of Assessment:

  • Examinations
  • Other
  • Quizzes
  • Discussion

Minimum Passing Score:

70%
Supplemental Materials