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.
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.
Variability - How to calculate the standard deviation and variance as well as how to interpret percentiles are provided in simple and clear language.
Charts and Graphs - How to calculate a cumulative frequency distribution table as well as how to calculate a stem and leaf plot is illustrated.
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
Bonus Features: Cement understanding with practice opportunities including several quizzes with complete video coverage of the solutions.
Update: New Videos Added on Hypothesis Testing! (See Section 6 of the Course.)
An introduction to both the course and to the instructor is provided in this video.
In this video, the scales of measurement are covered, of which there are four in total: nominal, ordinal, interval, and ratio.
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.
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."
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.
This video reviews the answers to the quiz on central tendency and skewed distributions. The answers are also available in the attached PDF file.
In this video, we take a look at the weighted mean, which can be used for finding an overall mean for two groups.
In this video, the quiz answers are reviewed on the weighted mean.
In this video, we take a look at percentiles, including quartiles and deciles.
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.
Consider the following population of N = 5 values: X = 14, 9, 11, 7, 9. The population variance is equal to
This video reviews the quiz on the standard deviation and variance, illustrating step by step how to find each value.
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.
In this video we examine how to construct a stem and leaf plot on a set of numbers ranging from the tens to fifties.
In this video we introduce the concept of probability as well as how to calculate the probability for different examples using the 'classical approach'.
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.
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.
This video reviews the answers to the quiz, Properties of the z-Score Normal Distribution.
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.
In this video, we take a look at how to solve for an X value given a z-Score.
In this video, the answers are reviewed to the quiz, Solving for X Scores Given a z-Score.
This lecture begins our coverage on inferential statistics. In this video the null and alternative hypotheses are explained, with a focus on two-tailed tests.
In this video we take a look at several different examples of two-tailed hypothesis tests.
In this video the null and alternative hypotheses are covered for one-tailed tests. One tailed tests are used when the researcher / analyst is looking for a specific outcome (or direction of effect) and usually isn't interested if the opposite direction of effect is found.
In this video we take a look at several different examples of one-tailed hypothesis tests.
This video covers Type I and Type II Errors with Examples
Type I Error - Reject the null hypothesis when it is true.
Type II Error - Fail to reject (accept) the null hypothesis when it is false.
In this video we take a detailed look at what a p value is. Examples using both alpha of .05 (most commonly used level of alpha) and .01 are included.
P-values are produced in statistics when analyses are run by computer (or calculator).
In this video, the often-confused p value of .000 is covered. Why a p of .000 is often reported in computer output and exactly what it means is explained in this video.
This quiz covers p-values, including how to assess a hypothesis test based on different levels of alpha and what a p-value of .000 means.
In this video, the concept of statistical power is illustrated.
Power = The probability of rejecting the null hypothesis when it is false.
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 award-winning 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 often-feared subject matter. Our focus is in helping you to succeed in all your statistics work!