# Course Syllabus: Statistics 101 \$95.00
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## Course Description

Statistics are used in a variety of contexts ranging from scientific experiments to political advertisements and beyond. Because statistics can be used to mislead, an understanding of the topic can be helpful for more than just the mathematical skills that it imparts: knowledge of statistics theory can also be a strong defense against attempts by the unscrupulous to mislead others.

This statistics course introduces the basic concepts of statistical analysis, with a focus on both univariate (single-variable) and bivariate (two-variable) data. The course starts with an introduction to statistics terms and then moves on to organization and display of data. Analysis of univariate data by way of measures of central tendency (such as the mean or average), dispersion (such as the variance), and asymmetry ("skewness") is presented next, followed by an introduction to probability theory.

The relationship of probability to statistics is also discussed, providing students with the tools they need to understand how "chance" plays a role in statistical analysis. Statistical distributions, with a focus on the normal distribution and its uses, are also considered, along with a discussion of bivariate data and linear (least-squares) regression. Finally, the course culminates with a low-level introduction to hypothesis testing. Although this last topic could be a course of its own, the student is provided with enough theory and sufficient practice to conduct analyses of simple statistical hypotheses.

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. This course is designed for anyone who wants a little more than just a cursory overview of statistics, but who doesn't want to get bogged down in the mathematical theory that underlies it.

## 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 basic concepts of statistical analysis that use univariate (single-variable) and bivariate (two-variable) data

-       Learn statistics terms

-       Learn the organization and display of data

-       Learn measures of central tendency, dispersion and skewness

-       Learn the basics of probability theory

-       Learn about Statistical Distributions

-       Learn how to use  bivariate data and linear (least-squares) regression

-       Learn the basics of hypothesis testing

Course Objectives:

lessons will cover these topics-

1.            Statistics terms and motivation

2.            Displaying statistical data

3.            Measures of central tendency

4.            Selecting an appropriate measure of central tendency

5.            Measures of dispersion

6.            Measures of asymmetry

7.            Other statistical measures

8.            Introduction to probability I

9.            Introduction to probability II

10.        Statistical distributions

11.        The normal distribution

12.        Bivariate data

13.        Regression

14.        Hypothesis testing I

15.        Hypothesis testing II

## Course Materials

No additional course materials required to complete this course.

Each lesson will include a written and practice assignment that will directly apply what you have learned.
A brief quiz will follow each lesson. Students will successfully complete this course by mastering all learning outcomes with 70% or higher overall grade.

## Learning Outcomes

By successfully completing this course, students will be able to:
• Define statistics terms.
• Display statistical data.
• Define measures of central tendency.
• Select an appropriate measure of central tendency.
• Define measures of dispersion.
• Describe measures of asymmetry.
• Describe Probability I problems
• Describe and solve Probability II problems.
• Know statistical distributions.
• Describe the normal distribution.
• Describe bivariate data.
• Perform regression analysis.
• Describe Hypothesis Testing I and II, and
• Demonstrate mastery of lesson content at levels of 70% or higher.