Course Description

Welcome to an empowering journey through the world of Applied Statistics, where numbers unlock the secrets of data, and informed decisions are born. This course is your gateway to transforming intimidating data sets into clear, actionable insights using the power of statistics.

Begin your statistical adventure by mastering the art of Descriptive Statistics. Learn how to succinctly summarize vast amounts of data with key metrics like mean, variance, and skewness. This foundational skill set is just the beginning, as these summaries pave the way for deeper analysis.

Dive into the core of the course where the real magic happens—Inferential Statistics. Here, you will explore how to make compelling arguments and draw robust conclusions from your data. Questions like "Is the average value of one dataset significantly different from another?" will not only be answered but demonstrated through practical, real-world applications. You'll delve into advanced techniques such as cross-tabulation and chi-square tests, correlation studies, linear regression, Student's t-tests, analysis of variance (ANOVA), repeated measures analysis, and even factor analysis.

While the mathematical underpinnings of these tools are vast, this course emphasizes intuitive understanding over complex equations. Through a blend of common-sense explanations and a wealth of real-life examples, you will see these statistical methods come to life, demystifying data and revealing patterns and truths hidden within.

By the end of this course, you will not only possess the skills to describe and analyze data sets effectively but also the confidence to apply these skills in real-world scenarios. Whether you're tackling basic applied statistics problems or gearing up for more advanced study, this course will equip you with a solid foundation in statistical reasoning that is crucial for a multitude of careers and research paths.

Embark on this statistical journey with us and transform the way you view data forever. Whether for academic pursuits, professional advancement, or personal curiosity, mastering applied statistics opens a world of possibilities and gives you the tools to navigate the data-driven decisions of tomorrow.

  • Completely Online
  • Self-Paced
  • Printable Lessons
  • Full HD Video  
  • 6 Months to Complete
  • 24/7 Availability
  • Start Anytime
  • PC & Mac Compatible
  • Android & iOS Friendly
  • Accredited CEUs
Universal Class is an IACET Accredited Provider
 

Learning Outcomes

By successfully completing this course, students will be able to:
  • Calculate the geometric mean of a given data set and compare it with the arithmetic mean to demonstrate differences in data characterization.
  • Define and calculate the arithmetic mean of a given data set to understand the central tendency of the data.
  • Calculate the variance and standard deviation of a given data set to assess its dispersion around the mean.
  • Demonstrate the ability to compute skewness to evaluate the asymmetry of a data distribution.
  • Create a frequency table to represent a given data set, calculating relative, cumulative, and cumulative relative frequencies accurately.
  • Demonstrate the ability to interpret bar graphs and histograms by analyzing visual representations of frequency data efficiently.
  • Demonstrate the ability to create and interpret scatterplots, calculate mean vectors, and covariance matrices for bivariate data sets.
  • Recognize and differentiate between univariate and multivariate data by describing specific examples and key characteristics.
  • Demonstrate the ability to create cross tabulations for bivariate data sets by organizing gender and handedness into a contingency table.
  • Identify and define the null and alternative hypotheses in a statistical hypothesis test for analyzing cross tabulations related to gender and handedness.
  • Demonstrate the ability to interpret chi-square test results and determine hypotheses significance based on critical values
  • Understand how to calculate expected frequencies in a cross tabulation using row, column, and grand totals
  • Demonstrate the calculation of Pearson's correlation coefficient for a given data set to quantify the linear relationship between two variables.
  • Demonstrate mastery of lesson content at levels of 70% or higher.
 
 

Assessment Guide

Assessment Points
Introduction 1 points
Lesson 1 Descriptive Statistics I 10 points
Feedback about the exam. 0 points
Lesson 2 Descriptive Statistics II 10 points
Lesson 3 Frequencies 9 points
Lesson 4 Multivariate Data 10 points
Lesson 5 Cross Tabulation I 10 points
Lesson 6 Cross Tabulation II 10 points
Lesson 7 Correlation 10 points
Lesson 8 Students t-Tests I 10 points
Lesson 9 Students t-Tests II 10 points
Lesson 10 One-Way ANOVA 10 points
Lesson 11 Repeated Measures 10 points
Lesson 12 Factor Analysis 10 points
Lesson 13 Linear Regression I 10 points
Lesson 14 Linear Regression II 6 points
The Final Exam 90 points
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