Section 1 : Introduction
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Lecture 1 | INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM | |
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Lecture 2 | The big picture | 00:02:11 Duration |
Section 2 : Excel Statistics Fundamentals
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Lecture 1 | Using Excel functions | 00:06:12 Duration |
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Lecture 2 | Understanding Excel statistics functions | 00:05:55 Duration |
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Lecture 3 | Working with Excel graphics | 00:04:23 Duration |
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Lecture 4 | Installing the Excel Analysis Toolpak |
Section 3 : Types of Data
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Lecture 1 | Differentiating data types | 00:04:20 Duration |
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Lecture 2 | Independent and dependent variables | 00:01:00 Duration |
Section 4 : Probability
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Lecture 1 | Defining probability | 00:01:55 Duration |
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Lecture 2 | Calculating probability | 00:06:14 Duration |
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Lecture 3 | Understanding conditional probability | 00:02:06 Duration |
Section 5 : Central Tendency
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Lecture 1 | The mean and its properties | 00:02:16 Duration |
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Lecture 2 | Working with the median | 00:02:23 Duration |
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Lecture 3 | Working with the mode | 00:01:53 Duration |
Section 6 : Variability
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Lecture 1 | Understanding variance | 00:04:30 Duration |
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Lecture 2 | Understanding standard deviation | 00:02:48 Duration |
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Lecture 3 | Z-scores | 00:03:02 Duration |
Section 7 : Distributions
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Lecture 1 | Organizing and graphing a distribution | 00:03:58 Duration |
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Lecture 2 | Graphing frequency polygons | 00:02:05 Duration |
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Lecture 3 | Properties of distributions | 00:03:05 Duration |
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Lecture 4 | Probability distributions | 00:04:10 Duration |
Section 8 : Normal Distributions
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Lecture 1 | The standard normal distribution | |
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Lecture 2 | Meeting the normal distribution family | 00:01:32 Duration |
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Lecture 3 | Standard normal distribution probability | 00:04:10 Duration |
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Lecture 4 | Visualizing normal distributions | 00:01:37 Duration |
Section 9 : Sampling Distributions
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Lecture 1 | Introducing sampling distributions | 00:03:45 Duration |
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Lecture 2 | Understanding the central limit theorem | 00:03:53 Duration |
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Lecture 3 | Meeting the t-distribution | 00:02:24 Duration |
Section 10 : Estimation
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Lecture 1 | Confidence in estimation | 00:04:45 Duration |
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Lecture 2 | Calculating confidence intervals | 00:05:16 Duration |
Section 11 : Hypothesis Testing
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Lecture 1 | The logic of hypothesis testing | |
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Lecture 2 | Type I errors and Type II errors | 00:03:22 Duration |
Section 12 : Testing Hypotheses about a Mean
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Lecture 1 | Applying the central limit theorem | 00:04:17 Duration |
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Lecture 2 | The z-test and the t-test | 00:08:02 Duration |
Section 13 : Testing Hypotheses about a Variance
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Lecture 1 | The chi-squared distribution | 00:03:37 Duration |
Section 14 : Independent Samples Hypothesis Testing
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Lecture 1 | Understanding independent samples | 00:02:54 Duration |
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Lecture 2 | Distributions for independent samples | 00:03:48 Duration |
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Lecture 3 | The z-test for independent samples | 00:02:27 Duration |
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Lecture 4 | The t-test for independent samples | 00:07:00 Duration |
Section 15 : Matched Samples Hypothesis Testing
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Lecture 1 | Understanding matched samples | |
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Lecture 2 | Distributions for matched samples | 00:02:04 Duration |
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Lecture 3 | The t-test for matched samples | 00:04:34 Duration |
Section 16 : Testing Hypotheses about Two Variances
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Lecture 1 | Working with the F-test | 00:03:00 Duration |
Section 17 : The Analysis of Variance
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Lecture 1 | Testing more than two parameters | 00:03:22 Duration |
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Lecture 2 | Introducing ANOVA | 00:06:22 Duration |
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Lecture 3 | Applying ANOVA | 00:01:41 Duration |
Section 18 : After the Analysis of Variance
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Lecture 1 | Types of post-ANOVA testing | 00:02:05 Duration |
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Lecture 2 | Post-ANOVA planned comparisons | 00:03:07 Duration |
Section 19 : Repeated Measures Analysis
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Lecture 1 | What is repeated measures | |
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Lecture 2 | Applying repeated measures ANOVA | 00:02:36 Duration |
Section 20 : Hypothesis Testing with Two Factors
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Lecture 1 | Statistical interactions | 00:05:04 Duration |
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Lecture 2 | Two-factor ANOVA | 00:05:21 Duration |
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Lecture 3 | Performing two-factor ANOVA | 00:02:05 Duration |
Section 21 : Regression
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Lecture 1 | Understanding the regression line | 00:05:46 Duration |
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Lecture 2 | Variation around the regression line | 00:03:11 Duration |
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Lecture 3 | Analysis of variance for regression | 00:05:16 Duration |
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Lecture 4 | Multiple regression analysis | 00:03:16 Duration |
Section 22 : Correlation
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Lecture 1 | Hypothesis testing with correlation | 00:02:26 Duration |
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Lecture 2 | Understanding correlation | 00:02:39 Duration |
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Lecture 3 | The correlation coefficient | 00:03:00 Duration |
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Lecture 4 | Correlation and regression | 00:02:00 Duration |