IUB CJUS-K 300 - Standard Deviation (2 pages)
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Standard Deviation
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Learned all the formulas for standard deviation and variance
- Lecture number:
- 5
- Pages:
- 2
- Type:
- Lecture Note
- School:
- Indiana University, Bloomington
- Course:
- Cjus-K 300 - Techniques of Data Analysis
- Edition:
- 1
Documents in this Packet
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Lecture 22: Pearson's Correlation
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Lecture 21: Bi-Variate Regression
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Lecture 17: Matched Sample T Tests
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Lecture 16: Hypothesis Testing with 2 Population Means
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Lecture 14: Chi Square Test of Independence
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Lecture 13: Chi Squared Goodness of Fit
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Lecture 11: Hypothesis Testing
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Lecture 10: Confidence Intervals Cont.
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Lecture 9: Confidence Intervals Pt. 1
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Lecture 6: Intro To Probability
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Lecture 2: Levels of Measurement
2 pages
Unformatted text preview:
CJUS K300 1nd Edition Lecture 5 Outline of Last Lecture II Measures of Central Tendency III Distributions Outline of Current Lecture IV Variance V Standard Deviation Current Lecture Getting rid of a negative sign take the absolute value is the most obvious way In this case we should square all the negative numbers so we do not have any negative deviations Variance A one number summary of how spread out the values for a variable are taking into account every value for the variable For population data the variance is referred to as sigma squared 2 2 x 2 N For a sample the variance is referred to as s 2 S 2 E x x 2 n 1 Standard deviation is the square root of the variance When the numbers are more spread out the variance is larger and when the variance is larger the standard deviation is larger Easier view of the formulas Variance for population data These notes represent a detailed interpretation of the professor s lecture GradeBuddy is best used as a supplement to your own notes not as a substitute
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CJUS-K 300 : EXAM 1
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