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1. Normal distributions- studied by France’s de Moivre & Germany’s Gauss to provide foundation of statistics 2. Normal curves- bell curve graph/distribution 3. Upward cup on normal curve- less than x – or x + 4. Downward cup on normal curve- between x – or x + 5. Symmetry of normal curves- same on both sides of the mean 6. Empirical rule- 68%, 95%, 99.7% 7. Z value or z score- the number of standard deviations between x and with . z = (x-)/ 8. Standard units- mean = 0, greater than the mean = > 0, less than the mean = < 0 9. Standard normal distribution- = 0 and = 1, 68% between -1 & 1, 95% between -2 & 2, 99.7% between -3 & 3 10. Raw score, x = z + 11. Area under the standard normal curve = probability using z score 12. Area under any normal curve = probability given x or raw score 13. Population parameter- numerical measures mean (), variance (2), standard deviation ), and proportion (p) 14. Statistic - numerical measures…mean (x̄ ), variance (s2), standard deviation (s) and proportion (p̂) 15. Sampling distribution- probability distribution based on a random sample x = symbol for mean of a sampling distribution. It is = population mean x = symbol for standard error of the mean in a sampling distribution. Formula =/√n 18. Standard error of the mean- formula = /√n 19. Central limit theorem- z = (x-)/ (/n) when n >30 20. Normal approx. binomial dist. - n trials, r successes, p prob., q = 1-p, np> 5, nq > 5, = np, and = √npq 21. Continuity correction- left point -0.5, right point +0.5 22. estimation- calculating the interval around the mean based on your confidence level 23. Testing- calculating whether a hypothesis claim has sufficient supporting evidence 24. average – mean (x̄ ) for sample or mean for population

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