Section 1 : Introduction
Lecture 1 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM

Section 2 : Think with Data
Lecture 1 The meaning of data fluency 00:06:40 Duration
Lecture 2 Data fluency is for everyone 00:02:27 Duration
Lecture 3 Data fluency in practice 00:06:58 Duration
Lecture 4 Making intuitive thinking explicit 00:05:14 Duration
Lecture 5 Thinking about causes 00:05:01 Duration
Lecture 6 How to develop data fluency 00:04:26 Duration
Lecture 7 Data-driven decision-making 00:09:38 Duration
Lecture 8 ROI and the 8020 rule for data fluency 00:04:55 Duration
Lecture 9 Putting data in context 00:06:58 Duration

Section 3 : Prepare Data
Lecture 1 Data ethics
Lecture 2 Use in-house data 00:04:37 Duration
Lecture 3 Use open data
Lecture 4 Gather new data 00:06:28 Duration
Lecture 5 Use third-party data 00:04:13 Duration
Lecture 6 Assess the quality of data 00:04:47 Duration
Lecture 7 Assess the generalizability of data 00:06:59 Duration
Lecture 8 Assess the meaning of data 00:04:05 Duration
Lecture 9 Assess the ambiguities in data 00:04:24 Duration

Section 4 : Adapt Data
Lecture 1 Sort data 00:05:13 Duration
Lecture 2 Filter data 00:03:24 Duration
Lecture 3 Combine and split categories 00:06:02 Duration
Lecture 4 Code text 00:10:00 Duration
Lecture 5 Calculate sums and means 00:06:27 Duration
Lecture 6 Calculate rates 00:05:33 Duration
Lecture 7 Calculate ratios 00:04:10 Duration
Lecture 8 Adjust ratios in practice 00:03:42 Duration

Section 5 : Explore Data
Lecture 1 Visual primacy The importance of starting with pictures 00:07:52 Duration
Lecture 2 Bar charts 00:06:51 Duration
Lecture 3 Grouped bar charts 00:06:34 Duration
Lecture 4 Pie charts 00:08:04 Duration
Lecture 5 Dot plots
Lecture 6 Box plots
Lecture 7 Histograms 00:04:37 Duration
Lecture 8 Line charts 00:08:23 Duration
Lecture 9 Sparklines 00:05:02 Duration
Lecture 10 Scatterplots 00:08:22 Duration
Lecture 11 Data maps 00:03:29 Duration

Section 6 : Describe Data
Lecture 1 Numerical descriptions 00:01:24 Duration
Lecture 2 Describe measures of center 00:07:30 Duration
Lecture 3 Describe variability with the range and IQR 00:04:39 Duration
Lecture 4 Describe variability with the variance and standard deviation 00:07:10 Duration
Lecture 5 Rescale data with z-scores 00:03:08 Duration
Lecture 6 Interpret z-scores 00:05:19 Duration
Lecture 7 Describe group differences with effect sizes 00:07:53 Duration
Lecture 8 Predict scores with regression 00:07:29 Duration
Lecture 9 Describe associations with correlations 00:04:50 Duration
Lecture 10 Effect size for correlation and regression 00:04:37 Duration
Lecture 11 Exploring tables 00:07:43 Duration

Section 7 : Probability and Inference
Lecture 1 Basic probability 00:07:43 Duration
Lecture 2 Conditional probability
Lecture 3 Expected values 00:06:39 Duration
Lecture 4 Sampling variation 00:05:32 Duration
Lecture 5 Inference as describing populations

Section 8 : Continuing Your Data Fluency Learning Quest
Lecture 1 Next steps and additional resources 00:06:34 Duration