Ohio State Newark: Statistics 1350.01 - Elementary Statistics: Recommended Sources

Standard Deviants Series:

• Introduction to statistics and the relative frequency histogram
• Binomial probability distribution
• Hypothesis testing, types of error, and small samples
• Measures of variability and relative standing
• Other graphical methods and numerical methods
• Poisson probability distribution and the urn model
• Probability  
• Probability distributions for continuous random variables
• Random variables  
• Sampling distributions and large samples

Statistics With Naomi Lowe series:

• Introduction
• Branches of Statistics : Lecture 1, Part 1
• Summarizing Data : Lecture 1, Part 2
• Central Tendency and Variability : Lecture 2
• Z-Scores : Lecture 3, Part 1
• Z-Scores and the Normal Curve : Lecture 3, Part 2
• Hypothesis Testing : Lecture 4
• Hypothesis Testing With Means : Lecture 5
• Stastical Significance : Lecture 6
• T-Tests : Lecture 7
• Independent T-Tests : Lecture 8
• ANOVA : Lecture 9
• Correlation and Regression : Lecture 10
• Chi-Square : Lecture 11
• Randomization : Lecture 12

Against all odds : inside statistics series

• What Is Statistics?
• Stemplots
• Histograms and Distributions
• Measures of Center
• Boxplots
• Standard Deviation
• Normal Curves
• Normal Calculations
• Checking Assumptions of Normality
• Scatterplots
• Fitting Lines to Data
• Correlation
• Two-Way Tables
• The Question of Causation
• Designing Experiments
• Census and Sampling
• Samples and Surveys
• Introduction to Probability
• Probability Models
• Random Variables
• Binomial Distribution
• Sampling Distributions
• Control Charts
• Confidence Intervals
• Tests of Significance
• Small Sample Inference for One Mean
• Comparing Two Means
• Inference for Proportions
• Inference for Two-Way Tables
• Inference for Regression
• One-Way ANOVA
• Summary

Basics / Multiple Topics

• The Joy of Stats  
• Introduction to statistics and the relative frequency histogram 
• Introduction to statistics
• Pie charts, bar graphs, and pareto charts
• Median and mode
• Expected values, means, variances, and standard deviations
• Descriptive verses inferential statistics
• Box and whisker plots

Applications

• Math Improves March Madness Predictions 
• Mathematical Patterns May Help Forecast Future Crimes 
• TEDTalks : Mona Chalabi—3 Ways To Spot A Bad Statistic
• TEDTalks : Alan Smith—Why You Should Love Statistics
• TEDTalks Peter Donnelly, How Juries Are Fooled by Statistics 
• Prediction by the Numbers 
• Ranking Sports Teams in New Ways 
• Science of Successful Basketball Teams 
• Statistics in everyday life
• Prediction by the Numbers

Distributions & Tests:

• Binomial probability distribution 
• Sampling distributions and large samples 
• Sampling distributions 
• Taking a Chance Key Probability Concepts
• The area under the normal distribution 
• The frequency distribution
• The normal distribution 
• Poisson probability distribution and the urn model 
• The student t-distribution
• An introduction to the t-test
• Using a student t-distribution statistical table

Probability:

• Data Analysis and Probability 
• Introduction to probability 
• Probabilities on joint events 
• Probability - introduction 
• Probability - summary 
• Probability distributions for continuous random variables 
• Probability statements 
• Probability trees 
• Probability 
• Probability 
• Taking a Chance Key Probability Concepts 
• Introduction to probability
• Probability - introduction

Randomness and Random Variables:

• Handling variability 
• Random variables and discrete probability distributions 
• Random variables 

Samples/Sampling:

• Sampling, Surveying, and Data Analysis 
• Using samples 
• An introduction to sampling
• An introduction to sample design
• Frequentist approaches sample size in adaptive clinical designs 

Other:

• Other graphical methods and numerical methods 
• Bivariate data when y depends on x 
• Breaking the Wall of Randomness How Random Phenomena Disseminate 
• Describing data 
• Hypothesis testing, types of error, and small samples 
• Measures of variability and relative standing 
• An introduction to correlation & regression

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