07:01
A Gentle Introduction to the Normal Probability Distribution (10-4)
03:35
EXPONENTIAL Probability Distribution for Continuous Random Variables (10-3)
06:33
UNIFORM Probability Distribution for Continuous Random Variables (10-2)
05:01
CONTINUOUS Random Variables: The Joy of X Revisited (10-1)
04:22
HYPERGEOMETRIC Probability Distribution for Discrete Random Variables (9-10)
05:20
POISSON Probability Distribution for Discrete Random Variables (9-9)
05:17
BINOMIAL Probability Distribution for Discrete Random Variables (9-8)
03:35
BIVARIATE Probability Distribution for Discrete Random Variables (9-7)
02:05
COMPOUND Probabilities for Discrete Random Variables (9-6)
04:01
UNIFORM Probability Distribution for Discrete Random Variables (9-5)
04:55
EXPECTED Values and Variance for Discrete Random Variables (9-4)
04:52
Probability DISTRIBUTIONS for Discrete Random Variables (9-3)
05:58
DISCRETE Random Variables: Finite and Infinite Distributions (9-2)
03:31
Scientific vs. STATISTICAL Experiments: Getting an Outcome (9-1)
05:08
The GAMBLER’S Fallacy (8-12)
06:38
SUBJECTIVE Probability Distributions (8-11)
06:03
Mathematical, THEORETICAL, and Experimental Probability Distributions (8-10)
04:17
CONDITIONAL Probability (8-9)
07:41
Probability, Counting, COMBINATIONS and Permutations for Multiple Events (8-8)
07:12
The MULTIPLICATION and ADDITION Rules for Probability (8-7)
10:00
FACTORS Influencing the Probability of an Event: Replacement, Independence, Mutually Exclusive (8-6)
06:27
The VENN Diagram, Complement, UNION, and Intersection of Probability Events (8-5)
08:45
Statistical EXPERIMENTS and the Meaning of Randomness (8-4)
08:38
A Gentle INTRODUCTION to Probability (8-3)
04:29
The Grammar of PROBABILITY: Terminology (8-2)
06:22
Living with UNCERTAINTY: Why Probability Matters (8-1)
04:13
Determining SAMPLE Size for Confidence Intervals around PROPORTIONS (13-9)
06:08
Determining SAMPLE Size for Confidence Intervals around MEANS (13-8)
06:23
Create Confidence Intervals for PROPORTIONS (13-7)
03:53
Create Confidence Intervals for MEANS (13-6)
04:02
Normal vs. t-Distribution and When They are the Same (13-5)
14:00
The t Distribution: A BREWER’S Solution for Small Samples (13-4)
09:56
Degrees of FREEDOM: Why We Use n – 1 for Confidence Intervals (13-3)
07:44
Stats Blocks: How Using Samples LOSES One degree of Freedom to Vary (13-3b)
19:32
Rich Jameson Rememberance
07:17
Bullseye! Point Estimators are Always WRONG (13-2)
07:32
Point Estimation vs. Confidence Intervals in Election Polling Data (13-1)
04:41
Mathematical Measures of VARIABILTY: Sum of Squares, Variance, & Std. Deviation (5-10)
05:22
Mean Average Deviation (The WRONG Way) (5-9)
06:08
Simple Measures of Variability: PERCENTILES, Quartiles, & Range (5-8)
07:36
A Mean for All Seasons: Trimmed, Weighted, and Geometric Means (5-7)
04:30
The Arithmetic MEAN: Measures of Central Tendency (5-6)
04:25
The MEDIAN: Measures of Central Tendency (5-5)
07:20
The MODE: Measures of Central Tendency (5-4)
03:12
How to CHOOSE a Measure of Central Tendency and Variability (5-3)
09:51
Explaining CENTRAL Tendency and Variability for Statistics (5-2)
06:11
Describing Distributions: The FOUR Qualities of Every Distribution (5-1)
08:28
The 5-Number Summary and BOXPLOTS (6-10)
13:14
How to FIX OUTLIERS in a Distribution (6-9)
14:17
Assumptions: Calling Out OUTLIERS – Problems and Causes (6-8)
03:03
CHEBYSHEV’S Theorem: An Inequality for Everyone (6-7)
10:50
The EMPIRICAL Rule (68-95-99 Rule) (6-6)
03:53
An ATTRACTIVE Application of z Scores with Antonio (6-5)
07:17
The Need for z Scores and the z Score Formula (6-4)
05:21
Assumptions: Catching KURTOSIS – It’s in the Tails (6-3)
07:44
Assumptions: Spotting SKEWNESS in a Distribution (6-2)
11:24
Depicting Distributions with the BELL Curve and Frequency (6-1)
08:09
Why is Statistics REQUIRED? Your Very First Statistics Course (1-1)
09:32
I Do My Own RESEARCH - Introducing Statistical Research (1-2)
09:19
Speaking of Statistics – DEFINING the Field of Statistics (1-3)
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