**$70.00**

no certificate

**$95.00**

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.

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### Request More Information

Have a question? Contact us for more information.### Course Lessons

#### 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#### 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#### 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#### 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#### 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#### 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#### 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#### Lesson 8 - Student's t-Tests I

o Learn and apply hypothesis testing procedure to the one-sample Student's t-test#### 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#### 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#### Lesson 11 - Repeated Measures

Recognize repeated measures designs

Determine an alternate method of evaluating means for repeated measures designs (repeated measures ANOVA)#### 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#### Lesson 13 - SPSS

o Gain some familiarity with SPSS

o Use SPSS to calculate statistical results in some simple cases

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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.

Lesson 1 Exercise | Assignment | 25 |

Lesson 1 Descriptive Statistics I | Exam | 10 |

Lesson 2 Exercise | Assignment | 25 |

Lesson 2 Descriptive Statistics II | Exam | 10 |

Lesson 3 Exercise | Assignment | 25 |

Lesson 3 Frequencies | Exam | 9 |

Lesson 4 Exercise | Assignment | 25 |

Lesson 4 Multivariate Data | Exam | 10 |

Lesson 5 Exercise | Assignment | 25 |

Lesson 5 Cross Tabulation I | Exam | 10 |

Lesson 6 Exercise | Assignment | 25 |

Lesson 6 Cross Tabulation II | Exam | 10 |

Lesson 7 Exercise | Assignment | 25 |

Lesson 7 Correlation | Exam | 10 |

Lesson 8 Exercise | Assignment | 25 |

Lesson 8 Students t-Tests I | Exam | 10 |

Lesson 9 Exercise | Assignment | 25 |

Lesson 9 Students t-Tests II | Exam | 10 |

Lesson 10 Exercise | Assignment | 25 |

Lesson 10 One-Way ANOVA | Exam | 10 |

Lesson 11 Exercise | Assignment | 25 |

Lesson 11 Repeated Measures | Exam | 10 |

Lesson 12 Factor Analysis | Exam | 10 |

Lesson 13 Exercise | Assignment | 25 |

Lesson 13 SPSS | Exam | 10 |

The Final Exam | Exam | 129 |

Total Points: | 558 |

### Student Testimonials

- "
*The instructor always got back to me quickly when I had a question or comment. He also graded the assignments and exams in a very timely manner.*" --**Cindy C.**

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