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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 oftenconfused 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 zScores  An introduction to probability is provided, along with properties of the normal distribution and how to calculate and interpret zscores
Goals/Learning Objectives: Understand beginning probability including important characteristics of the normal (Gaussian) distribution, as well as how to calculate and interpret zscores.
Bonus Features: Cement understanding with practice opportunities including several quizzes with complete video coverage of the solutions.
Update 11/16: Additional Topics to be Added Soon!
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Section 1: Course Introduction and Introduction to Statistics  

Lecture 1  02:41  
An introduction to both the course and to the instructor is provided in this video. 

Lecture 2  11:02  
In this video, the scales of measurement are covered, of which there are four in total: nominal, ordinal, interval, and ratio. 

Quiz 1 
Scales of Measurement

4 questions  
Section 2: Central Tendency  
Lecture 3  05:46  
This video lecture covers the mean, median, and mode. First the mode is covered, including examples of two modes (bimodal) and three or more modes (multimodal). Next, finding the median is covered for both an even and odd number of values. After the median, how to calculate the mean (arithmetic average) is covered. 

Quiz 2 
Quiz  Mean, Median, and Mode

5 questions  
Lecture 4  04:12  
In this video, the answers to the mean, median, and mode quiz are reviewed with explanations provided. The answers are also available in the attached PDF file. Note: On problem #5, I state, "1, 3, 3, 5", but should have stated "1, 3, 3, 3, 5." 

Lecture 5  04:28  
In this video, we take a look at the relationship between the mean, median, and mode and asymmetrical (skewed) distributions. As the video illustrates, the order of the three measures of central tendency (where they fall on a number line in relation to each other) depends on whether a distribution is positively or negatively skewed. 

Quiz 3 
Quiz  Central Tendency and Skewed Distributions

3 questions  
Lecture 6  02:44  
This video reviews the answers to the quiz on central tendency and skewed distributions. The answers are also available in the attached PDF file. 

Lecture 7  04:42  
In this video, we take a look at the weighted mean, which can be used for finding an overall mean for two groups. 

Quiz 4 
The Weighted Mean

3 questions  
Lecture 8  03:50  
In this video, the quiz answers are reviewed on the weighted mean. 

Section 3: Variability  
Lecture 9  05:55  
In this video, we take a look at percentiles, including quartiles and deciles. 

Quiz 5 
Percentiles

5 questions  
Lecture 10  06:29  
In this video, we take a look at how to calculate the variance and standard deviation by hand. Each step and calculation is illustrated in arriving at the solutions. 

Quiz 6  2 questions  
Consider the following population of N = 5 values: X = 14, 9, 11, 7, 9. The population variance is equal to 

Lecture 11  07:11  
This video reviews the quiz on the standard deviation and variance, illustrating step by step how to find each value. 

Section 4: Charts, Tables, and Graphs  
Lecture 12  02:46  
In this video, we examine how to construct a cumulative frequency distribution table, which includes the columns X, f, and cf. X corresponds to the values (or scores) of a variable X, f is the frequency value for each X (how many of each X there are), and cf is the cumulative frequency. 

Lecture 13  03:14  
In this video we examine how to construct a stem and leaf plot on a set of numbers ranging from the tens to fifties. 

Section 5: Probability, the Normal Curve and zScores  
Lecture 14  04:15  
In this video we introduce the concept of probability as well as how to calculate the probability for different examples using the 'classical approach'. 

Lecture 15  06:57  
In this video, the normal distribution and z scores are covered. First, properties of the normal distribution are described, including how the mean, median, mode are equal to zero and how the normal distribution is symmetrical. Next the areas under the curve are illustrated, closing with a demonstration of the 68, 95, 99.7 rule for values that are 1, 2, and 3 standard deviations away from the mean. 

Lecture 16  03:27  
In this video lecture, we take a look at the properties of the z score normal distribution, including (1) that it is symmetrical, (2) that the mean, median, and mode are all equal to zero, and (3) that the standard deviation is equal to 1. 

Quiz 7 
Properties of the z Score Normal Distribution

5 questions  
Lecture 17  02:52  
This video reviews the answers to the quiz, Properties of the zScore Normal Distribution. 

Lecture 18  05:10  
In this video lecture, z scores are covered, including how to solve for z scores for a number of different examples. Also illustrated is how the z score indicates the number of standard deviations a value is from the mean. For example, a z score of 1.5 indicates that a value is 1.5 standard deviations above the mean. 

Quiz 8 
Solving for zScores

5 questions  
Lecture 19 
Video Review of Quiz  Solving for zScores

04:22  
Lecture 20  05:45  
In this video, we take a look at how to solve for an X value given a zScore. 

Quiz 9 
Solving for X Given a zScore

5 questions  
Lecture 21  05:04  
In this video, the answers are reviewed to the quiz, Solving for X Scores Given a zScore. 

Section 6: Conclusion  
Lecture 22  00:57  
In this video we wrap up the course and introduce some of the other courses by Quantitative Specialists. 
Quantitative Specialists (QS) was founded by an awardwinning university instructor who has taught statistics courses for over 15 years. At QS, we are passionate about all things statistical, especially in helping others understand this oftenfeared subject matter. Our focus is in helping you to succeed in all your statistics work!