Street-Smart Stats cover
Lesson 1 Introduction to Statistical Research Methods
Lesson 2 Visualizing Data
Lesson 3 Central Tendency
Lesson 4 Variability
Lesson 5 Standardizing
Lesson 6 Normal Distribution
Lesson 7 Sampling Distributions
Lesson 8 Estimation
Lesson 9 Hypothesis Testing
Lesson 10 t-Tests for Dependent Samples
Lesson 11 t-Tests for Independent Samples
Lesson 12 Intro to One-Way ANOVA
Lesson 13 One-Way ANOVA: Test significance of differences
Lesson 14 Correlation
Lesson 15 Linear Regression
Lesson 16 Chi-Squared Tests

Keep the standard deviation in the back of your head for the time being, and let’s move on to a different but related question. If you know a particular value, how can you describe how this value compares to others in the dataset?

For example, Katie plays competitive chess, and her United States Chess Federation rating is 1800. We know that the higher the number, the better the rating. But just how good is a rating of 1800? We could say that Katie’s rating is lower than 8110 other chess players, but we don’t know how many chess players exist in total.

A more descriptive way to compare a rating of 1800 to other ratings is to look at the distribution of ratings of other US players.



In this case, we get 88% by adding all the absolute frequencies for each bin up to a rating of 1800, and then dividing by the total number
of chess players. It’s easier to analyze proportions and percentages using relative, rather than absolute, frequencies.

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