# Introduction to Statistics

## Introductory Statistics as Covered in the Social, Behavioral, and Natural Sciences ### What you'll learn:

• Understand and learn how to calculate a number of different descriptive statistics
• Increase marketable job skills in data analytics
• Increase your quantitative and numerical reasoning skills!

### Requirements:

• No special software or other materials are required.

### Description:

November, 2019

In the course, you will learn how to easily and effectively analyze and interpret data involving introductory statistics. The following topics are covered in this course:

Scales of measurement - nominal, ordinal, interval, ratio.

• Goal/Learning Objective: Easily understand the often-confused scales of measurement covered in most statistics texts.

Central Tendency - mean, median, and mode are illustrated along with practice problems; measures of central tendency and skewed distributions are explained, as well as how to calculate the weighted mean.

• Goals/Learning Objectives: Summarize a set of data, find the center location in a distribution of scores, understand and identify the location of measures of central tendency in skewed distributions, understand and interpret how to find the overall or combined mean for two different sets of data.

Variability - How to calculate the standard deviation and variance as well as how to interpret percentiles are provided in simple and clear language.

• Goals/Learning Objectives: Understand and explain variability (spread) in a set of numbers, including how to rank data and interpret data such as standardized test scores (for example, the 95th percentile).

Charts and Graphs - How to calculate a cumulative frequency distribution table as well as how to calculate a stem and leaf plot is illustrated.

• Goals/Learning Objectives: Learn how to easily organize, summarize, understand, and explain a set of numbers.

Probability, the Normal Curve and z-Scores - An introduction to probability is provided, along with properties of the normal distribution and how to calculate and interpret z-scores

• Goals/Learning Objectives: Understand beginning probability including important characteristics of the normal (Gaussian) distribution, as well as how to calculate and interpret z-scores.

Bonus Features: Cement understanding with practice opportunities including several quizzes with complete video coverage of the solutions.

Update: New Videos Added on Hypothesis Testing and on Correlation!    (See Sections 6 and 7 of the Course.)

### Who this course is for:

• Those interested in learning more about descriptive statistics should take this course (those interested only in inferential statistics should not take the course)

### Course Details:

• 2.5 hours on-demand video
• 7 downloadable resources
• Full lifetime access
• Access on mobile and TV
• Certificate of completion