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Applied Statistics 101

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  • 14
  • 17
    Exams &
  • 21
    average time
  • 2.1
  • 922
    have taken this course

Course Description

Large sets of numbers can be daunting, and characterizing them in a few words or numbers can be even more daunting. This course considers how to take data sets--whether large or small--and describe them using a few numbers (descriptive statistics). This, however, is only a small portion of the course.

The majority of the course is dedicated to reaching statistically justified conclusions on the basis of these descriptive statistics. For instance, does the average value of one data set deviate from another in what might be called a "statistically significant" manner? To this end, the course covers cross tabulation of data (including the chi-square test), correlation, linear regression, Student's t-tests, analysis of variance (ANOVA), repeated measures analysis, and factor analysis. 

Although the course does not always provide rigorous mathematical justifications for every aspect of the statistical tools and theory discussed therein, it does provide common-sense explanations of many of these aspects, and it includes numerous real-world examples to illustrate the use of these tools.

Thus, this course teaches students to take sets of data, describe them using a few numbers (including the mean, variance, and skewness), and then reach statistically justifiable conclusions about those data sets. Students should come away from the course with confidence in their ability to tackle basic applied statistics problems and with the fundamental knowledge needed to learn more in-depth statistical theory.

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  • 6 Months to Complete
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  • Accredited CEUs
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Course Lessons

Average Lesson Rating:
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"Extraordinarily Helpful"
(46 votes)

Lesson 1 - Descriptive Statistics I

o Review arithmetic means and some associated concepts in descriptive statistics
o Consider other types of means, including geometric and power means
11 Total Points
  • Lesson 1 Video A
  • Lesson 1 Video B : How to Take an Exam
  • Review 2 Articles: Descriptive statistics; Free Graph Paper
  • Complete Assignment: Introduction
  • Complete Exam: Lesson 1 Descriptive Statistics I
  • Complete: Feedback about the exam.

Lesson 2 - Descriptive Statistics II

o Use moments about the mean to represent measures of dispersion and asymmetry
o Calculate the variance, standard deviation, and skewness of data sets
10 Total Points
  • Lesson 2 Video
  • Review 2 Articles: Definition of Measure of Dispersion; Definition of Skewness
  • Complete Exam: Lesson 2 Descriptive Statistics II

Lesson 3 - Frequencies

o Create frequency tables to represent data sets
o Calculate relative, cumulative, and cumulative relative frequencies
o Create and interpret bar graphs and histograms
9 Total Points
  • Lesson 3 Video
  • Review Practice Worksheet: Example2Explainedfurther.docx
  • Review 3 Articles: Frequency Distributions; Graphing with Excel; Variance Formulas in Excel
  • Complete Exam: Lesson 3 Frequencies

Lesson 4 - Multivariate Data

o Recognize multivariate data versus univariate data
o Represent multivariate data using tables and scatterplots
o Calculate descriptive statistics for multivariate data, including covariances
10 Total Points
  • Lesson 4 Video
  • Review Article: Definition of Multivariate statistics
  • Complete Exam: Lesson 4 Multivariate Data

Lesson 5 - Cross Tabulation I

o Create cross tabulations for bivariate data sets
o Review the basic terminology and procedure associated with statistical hypothesis testing
10 Total Points
  • Lesson 5 Video
  • Review Article: Contingency table
  • Complete Exam: Lesson 5 Cross Tabulation I

Lesson 6 - Cross Tabulation II

o Understand how to calculate the chi-square statistic for a cross tabulation
o Use the chi-square statistic to test hypotheses regarding cross tabulations
10 Total Points
  • Lesson 6 Video
  • Review 2 Articles: A table of critical values for the chi-square statistic; Cross tabulations and the chi-square statistic
  • Complete Exam: Lesson 6 Cross Tabulation II

Lesson 7 - Correlation

o Understand how variance can be used to define a statistic that measures the linear relationship between variables
o Use the correlation coefficient to quantify the correlation between two variables
10 Total Points
  • Lesson 7 Video
  • Review Article: Correlation
  • Complete Exam: Lesson 7 Correlation

Lesson 8 - Student's t-Tests I

o Learn and apply hypothesis testing procedure to the one-sample Student's t-test 10 Total Points
  • Lesson 8 Video
  • Review Article: A table of values for the Student's t distribution
  • Complete Exam: Lesson 8 Students t-Tests I

Lesson 9 - Student's t-Tests II

o Apply the paired two-sample Student's t-test to determine if two samples have statistically different means 10 Total Points
  • Lesson 9 Video
  • Review Article: Making Sense of the Two-Sample T-Test
  • Complete Exam: Lesson 9 Students t-Tests II

Lesson 10 - One-Way ANOVA

o Identify the test statistic for one-way ANOVA
o Use one-way ANOVA to compare the means of multiple sample groups
10 Total Points
  • Lesson 10 Video
  • Review Article: A table of values for the F distribution
  • Complete Exam: Lesson 10 One-Way ANOVA

Lesson 11 - Repeated Measures

Recognize repeated measures designs
Determine an alternate method of evaluating means for repeated measures designs (repeated measures ANOVA)
10 Total Points
  • Lesson 11 Video
  • Review 2 Articles: Repeated Measures ANOVA; Total Sum of squares
  • Complete Exam: Lesson 11 Repeated Measures

Lesson 12 - Factor Analysis

o Recognize some of the key terms associated with factor analysis
o Understand the overall purpose and procedures of exploratory and confirmatory factor analysis
10 Total Points
  • Lesson 12 Video
  • Review 2 Articles: Definition of Factor Analysis; Factor Analysis Training
  • Review Video: Factor analysis tutorial
  • Complete Exam: Lesson 12 Factor Analysis

Lesson 13 - Linear Regression I

Previously, we considered scatterplots as a way to display bivariate data sets. Scatterplots lead us to ask whether we can statistically construct a function that approximates the data. 10 Total Points
  • Lesson 13 Video
  • Complete Exam: Lesson 13 Linear Regression I

Lesson 14 - Linear Regression II

We now extend our look at linear regression by considering path diagrams, which can be a useful tool for visually representing the relationships among variables in a data set. 96 Total Points
  • Lesson 14 Video
  • Complete Exam: Lesson 14 Linear Regression II
  • Complete: The Final Exam
Total Course Points
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Learning Outcomes

By successfully completing this course, students will be able to:
  • Define descriptive statistics.
  • Demonstrate statistics and the use frequencies and how to solve these problems.
  • Identify multivariate data.
  • Demonstration Cross Tabulation problems and solutions
  • Demonstrate understanding of correlation in statistics.
  • Demonstrate problem and solution use of t-Tests.
  • Demonstrate One-Way ANOVA statistical problems and solutions
  • Demonstrate Repeated Measures.
  • Demonstrate Factor Analysis.
  • Describe basic usage of SPSS for graphing and solving applied statistics problems, and
  • Demonstrate mastery of lesson content at levels of 70% or higher.
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Additional Course Information

Online CEU Certificate
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Document Your CEUs on Your Resume
Course Title: Applied Statistics 101
Course Number: 9770454
Languages: English - United States, Canada and other English speaking countries
Course Type: General Education
CEU Value: 2.1 IACET CEUs (Continuing Education Units)
CE Accreditation: Universal Class, Inc. has been accredited as an Authorized Provider by the International Association for Continuing Education and Training (IACET).
Grading Policy: Earn a final grade of 70% or higher to receive an online/downloadable CEU Certification documenting CEUs earned.
Assessment Method: Lesson assignments and review exams
Course Author: Jeff Clark, Ph.D.
Instructor: April Cordry-Moore
Syllabus: View Syllabus
Duration: Continuous: Enroll anytime!
Course Fee: $70.00 (no CEU Certification) || with Online CEU Certification: $95.00

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