# Course Syllabus: Applied Statistics 101

no certificate

with CEU Certificate*

## 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.

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.

## Course Requirements

The course assumes a minimal understanding of and proficiency in algebra, but many of the concepts can be understood, and even many of the calculations performed, without an extensive mathematical background.

## Course Goals and Objectives

**Course Goals:**

Learn other types of means, including geometric and power means associated in descriptive statistics

Learn how to represent measures of dispersion and asymmetry

Calculate the variance, standard deviation, and skewness of data sets

Create frequency tables to represent data sets

Represent multivariate data using tables and scatterplots

Create cross tabulations for bivariate data sets

Understand how variance can be used to define a statistic that measures the linear relationship between variables

Understand the fundamental concepts associated with stepwise linear regression

Calculate data values for standardized variables

Calculate standardized regression coefficients using matrix math

Recognize and construct path diagrams

Learn and apply hypothesis testing procedure to the one-sample Student's t-test

Apply the paired two-sample Student's t-test to determine if two samples have statistically different means

Identify the test statistic for one-way ANOVA

Use one-way ANOVA to compare the means of multiple sample groups

Recognize repeated measures designs

Understand the overall purpose and procedures of exploratory and confirmatory factor analysis

**Lessons will cover these topics: **

Descriptive Statistics I

Descriptive Statistics II

Frequencies

Multivariate Data

Cross Tabulation I

Cross Tabulation II

Correlation

Linear Regression I

Linear Regression II

Student's t-Tests I

Student's t-Tests II

One-Way ANOVA

Repeated Measures

Factor Analysis

## Course Materials

No additional course materials required to complete this course.

## Grading Policy

Students will successfully complete this course with an overall grade of 70% or higher.

## Learning Outcomes

- 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.

## Assessment Guide

Introduction | 1 |

Lesson 1 Descriptive Statistics I | 10 |

Feedback about the exam. | 0 |

Lesson 2 Descriptive Statistics II | 10 |

Lesson 3 Frequencies | 9 |

Lesson 4 Multivariate Data | 10 |

Lesson 5 Cross Tabulation I | 10 |

Lesson 6 Cross Tabulation II | 10 |

Lesson 7 Correlation | 10 |

Lesson 8 Students t-Tests I | 10 |

Lesson 9 Students t-Tests II | 10 |

Lesson 10 One-Way ANOVA | 10 |

Lesson 11 Repeated Measures | 10 |

Lesson 12 Factor Analysis | 10 |

Lesson 13 Linear Regression I | 10 |

Lesson 14 Linear Regression II | 6 |

The Final Exam | 90 |

Total Points: | 226 |

## Related Articles

- Applied Statistics: Factor Analysis
- Applied Statistics: Descriptive Statistics II
- Applied Statistics: Repeated Measures
- How to Apply Hypothesis Testing Procedure to the One-Sample Student's t-Test
- How to Apply the Paired Two-Sample Student's t-Test to Determine if Two Samples have Statistically Different Means
- Solving Exponential and Logarithmic Functions
- Calculating the Mean and Standard Deviation of a Distribution
- Review of Mathematical Properties and Order of Operations
- How to Solve Linear Inequalities
- Types of Errors in Hypothesis Testing
- How to Calculate Perimeter
- Solving Geometry Problems Involving Circles
- Introduction to Derivatives
- Why is Geometry Important in Everyday Life?
- Using Classical Geometric Construction Techniques