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Udacity Statistics May 2015
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Resources: Covers the tail end of Udacity's Intro to Descriptive Statistics and the majority of Udacity's Intro to Inferential Statistics
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Purpose: Created as a reference sheet for practical use of statistics analysis methods
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z-Scores:
A z-score is a statistical measurement of a score's relationship to the mean in a group of scores. A z-score of 0 means the score is the same as the mean
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Confidence Intervals:
A confidence interval (CI) is a type of interval estimate of a population parameter. It is an observed interval (i.e., it is calculated from the observations), in principle different from sample to sample, that frequently includes the parameter of interest if the experiment is repeated.
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Dependent t-Tests:
The dependent t-test (also called the paired t-test or paired-samples t-test) compares the means of two related groups to detect whether there are any statistically significant differences between these means.
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Independent t-Tests:
The independent t-test, also called the two sample t-test or student's t-test, is an inferential statistical test that determines whether there is a statistically significant difference between the means in two unrelated groups.
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r^2:
The coefficient of determination, denoted R2 or r2 and pronounced R squared, is a number that indicates how well data fit a statistical model
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ANOVA:
Analysis of variance (ANOVA) is a collection of statistical models used in order to analyze the differences between group means and their associated procedures (such as "variation" among and between groups)
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Regression:
Linear regression is an approach for modeling the relationship between a scalar dependent variable y and one or more explanatory variables (or independent variable) denoted X.
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Chi-Squared:
The chi-squared (I) test is used to determine whether there is a significant difference between the expected frequencies and the observed frequencies in one or more categories. Does the number of individuals or objects that fall in each category differ significantly from the number you would expect? Is this difference between the expected and observed due to sampling variation, or is it a real difference?
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