1. Chapter 11: Section 11.1, Exercise 10. "The strength of concrete used in commercial..." Here is the ANOVA table for this data set: Analysis of Variance for Strength Source Batch Method Error Total DF 86.7913 23.229 24.045 134.067 MS 9.644 11.614 1.336 7.22 0.000 8.69 0.002 2 18 29 Follow these instructions: a, with α-0.01, perform the 2 tests of hypothesis: (Factor A-Batch) Ho:CA2-0 vs. Ha : ƠA2 (Factor B-Method) Ho: β1-62-63-o vs. Ha. Ho is false. 0 . . Follow the 4-step procedure and use the P-values above. b. Suppose that Factor A (Batch) is a random effect. Compute by hand arn estimate of ơA2 How much of total variation in a single observation is attributed to differences between batches? c. 10. The strength of concrete used in commercial construction tends to vary from one batch to another. Consequently small test cylinders of concrete sampled from a batch are "cured" for periods up to about 28 days in temperature- and moisture-controlled environments before strength measure- ments are made. Concrete is then "bought and sold on the basis of strength test cylinders" (ASTM C 31 Standard Test Method for Making and Curing Concrete Test Specimens in the Field). The accompanying data resulted from an experi- ment carried out to compare three different curing methods with respect to compressive strength (MPa). Analyze this data Batch Method A Method B Method C 30.7 29.1 30.0 31.9 30.5 26.9 28.2 32.4 26.6 28.6 33.7 30.6 32.2 34.6 33.0 29.3 28.4 32.4 29.5 29.4 30.5 30.5 33.5 32.4 27.8 30.7 33.6 29.2 33.2 4 10

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Contingency Table

A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.

Binomial Distribution

Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.