Stats

1. Statistical techniques be methods that convert data into information 2. Descriptive Statistics and pictural Presentation ar oft as important as inference a. Descriptive techniques describe and summarize * Mean, Median, Mode, Quartile, Percentile * Arithmetic, leaden Average, Geometric * Range, Variance, streamer Deviation, IQR * Covariance, Correlation b. A major(ip) note value of regression is the production of a model that describes the relationships among variables * Intercept, Slope, SS, MS, t, F, Rsq, Adj Rsq, stock(a) Error 3. There are a large deed of techniques because in that location are numerous objectives and types of data 4. chance and hazard Distributions form a keystone foundation of statistical inference 5. Probability Definitional Rules: a. 0 ? P (A) ? 1 b. P (A) + P (not-A) = 1 c. P (A or B) = P (A) + P (B) P (A and B) d. P (A and B) = P (A) * P (B | A) P (A and B) = P (B) * P (A | B) 6. Probability attending Rules a. taste = a period of k steps ( flavour 1: n1 outcomes, graduation 2: n2 outcomes Step k: nk outcomes) The total chassis of experimental outcomes is given by (n1)*(n2)**(nk) b. Permutation of n objects interpreted r at a condemnation ( dedicate counts): wager the number of experimental outcomes when r objects are to be selected from a set of n objects P= n!

n-r! c. Combinations of n objects taken r at a time (Order doesnt count): Count the number of experimental outcomes when r objects are to be selected from a set of n objects C= n!r!n-r! 7. hit-or-miss Variables and Probability Distributions: a. To conduct the judge assess: EX= x*Px b. To calculate the Variance: VarX= (x-EX)2*P(x) c. To calculate the Standard deviation: ?X= (x-EX)2*P(x) d. Linear Transformations: If Y = a*X + b, Then EY=a*EX+b, VarY=a2*VarX, ?Y=|a|*?X e. Linear Combinations:...If you require to get a affluent essay, order it on our website: Ordercustompaper.com

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