Section 1 : Introduction

Lecture 1 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM Pdf
Lecture 2 What you should know

Section 2 : Foundational Concepts of Data Analysis

Lecture 3 Calculate mean and median values 6:26
Lecture 4 Measure maximums, minimums, and other data characteristics
Lecture 5 Analyze data using variance and standard deviation 6:34
Lecture 6 Introducing the central limit theorem 3:32
Lecture 7 Analyze a population using data samples
Lecture 8 Identify and minimize sources of error 2:5

Section 3 : Visualize Data

Lecture 9 Group data using histograms 3:35
Lecture 10 Identify relationships using XY scatter charts 2:20
Lecture 11 Visualize data using logarithmic scales 3:16
Lecture 12 Add trendlines to charts 3:18
Lecture 13 Forecast future results 5:15
Lecture 14 Calculate running averages 4:37

Section 4 : Test a Hypothesis

Lecture 15 Formulate a hypothesis
Lecture 16 Interpret the results of your analysis 1:53
Lecture 17 Consider the limits of hypothesis testing 1:18

Section 5 : Utilize Data Distributions

Lecture 18 Use the normal distribution 6:1
Lecture 19 Use the exponential distribution 5:24
Lecture 20 Use a uniform distribution 0:0
Lecture 21 Use the binomial distribution 4:50
Lecture 22 Use the Poisson distribution 4:22

Section 6 : Measure Covariance and Correlation

Lecture 23 Visualize what covariance means 2:38
Lecture 24 Calculate covariance between two columns of data 4:21
Lecture 25 Calculate covariance among multiple pairs of columns 5:16
Lecture 26 Visualize what correlation means 4:42
Lecture 27 Calculate correlation between two columns of data 2:33
Lecture 28 Calculate correlation among multiple pairs of columns 4:32

Section 7 : Perform Bayesian Analysis

Lecture 29 Introduce Bayesian analysis
Lecture 30 Analyze a sample problem Kahneman’s Cabs 4:14
Lecture 31 Create a classification matrix 3:27
Lecture 32 Calculate Bayesian probabilities in Excel 5:58
Lecture 33 Update your Bayesian analysis 2:49

Section 8 : Conclusion

Lecture 34 Further resources 1:40