A laboratory engineer describes an experiment in which the tensile strength of asynthetic fiber is of interest to the manufacturer. It is suspected that strength isrelated to the percentage of cotton in the fiber. Five levels of cotton percentageare used, and five replicates are run in random order, resulting in the databelow:Observations...Cotton (%)123415771511920121712181825141818191930192522192335710111511Does cotton percentage affect breaking strength? Test the hypothesis at alpha0.05F critical is Blank 1F stat is Blank 2Decision is to Blank 3 the null hypothesis. (accept or reject)Blank 1Add your answerBlank 2Add your answerBlank 3Add your answer

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Answered: A laboratory engineer describes an…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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The following data comes from a study on the effects of sunlight on pea plants, where x = distance (in centimeters) from an ultraviolet light source and y = sunburn index. x 18 21 25 26 30 32 36 40 40 50 51 54 61 62 62 y 4.0 3.7 3.0 2.9 2.6 2.5 2.2 2.0 2.1 1.5 1.5 1.5 1.3 1.2 1.1 The Correlation Coefficient for this data is r = (3 decimals) Use three words to describe this correlation: , ,
(b) A consumer testing agency is interested in determining whether there is a difference in the mileage for three brands of gasoline. To test this, four different vehicles are driven with each of these gasolines. Results are shown in the table below Gasoline Vehicle A B 19 25 22 II 26 33 39 20 28 25 IV 18 30 Perform a Freidmans test to detemine whether there is a difference between the three gasoline medians at the a = 5%. 21
Mr. Acosta, a sociologist, is doing a study to see if there is a relationship between the age of a young adult (18 to 35 years old) and the type of movie preferred. A random sample of 93 adults revealed the following data. Test whether age and type of movie preferred are independent at the 0.05 level. Person's Age Movie 18-23 yr 24-29 yr 30-35 yr Row Total Drama 8 16 10 34 Science Fiction 10 8 12 30 Comedy 11 8 10 29 Column Total 29 32 32 93 (a) What is the level of significance?State the null and alternate hypotheses. H0: Age and movie preference are not independent.H1: Age and movie preference are independent.H0: Age and movie preference are independent.H1: Age and movie preference are independent. H0: Age and movie preference are not independent.H1: Age and movie preference are not independent.H0: Age and movie preference are independent.H1: Age and movie preference are not independent. (b) Find the value of the chi-square statistic for the sample. (Round…
In an investigation of the visual scanning behaviour of deaf children, measurements of eye movement rates were taken on nine deaf and nine normal children as shown in the table below Deaf Children Normal Children 1.81 0.95 2.2 1.49 3.29 1.12 2.13 1.07 2.55 1 2.24 1.85 2.22 1.18 2.89 2.07 2.26 1.18 a. If the two samples are drawn from normal populations, test the hypothesis that on average eye movement rate for normal children is less than deaf children in the population at a 10% level of significance. b. What does the 10% level of significance mean? Does it appear that the distributions of eye-movement rates for deaf children and normal children differ at 5% level of significance (assuming samples are not drawn from normal population)? с.
Mr. Acosta, a sociologist, is doing a study to see if there is a relationship between the age of a young adult (18 to 35 years old) and the type of movie preferred. A random sample of 93 adults revealed the following data. Test whether age and type of movie preferred are independent at the 0.05 level. Person's Age Movie 18-23 yr 24-29 yr 30-35 yr Row Total Drama 7 13 14 34 Science Fiction 11 11 8 30 Comedy 8 10 11 29 Column Total 26 34 33 93 (A) Find the value of the chi-square statistic for the sample. (Round the expected frequencies to at least three decimal places. Round the test statistic to three decimal places.)
The following data represent petal lengths (in cm) for independent random samples of two species of iris. Petal length (in cm) of Iris virginica: x1; n1 = 36 5.2 5.6 6.1 6.1 5.1 5.5 5.3 5.5 6.9 5.0 4.9 6.0 4.8 6.1 5.6 5.1 5.6 4.8 5.4 5.1 5.1 5.9 5.2 5.7 5.4 4.5 6.4 5.3 5.5 6.7 5.7 4.9 4.8 5.8 5.2 5.2 Petal length (in cm) of Iris setosa: x2; n2 = 38 1.6 1.8 1.4 1.5 1.5 1.6 1.4 1.1 1.2 1.4 1.7 1.0 1.7 1.9 1.6 1.4 1.5 1.4 1.2 1.3 1.5 1.3 1.6 1.9 1.4 1.6 1.5 1.4 1.6 1.2 1.9 1.5 1.6 1.4 1.3 1.7 1.5 1.5 (a) Use a calculator with mean and standard deviation keys to calculate x1, s1, x2, and s2. (Round your answers to four decimal places.) x1=s1=x2=s2= (b) Let μ1 be the population mean for x1 and let μ2 be the population mean for x2. Find a 99% confidence interval for μ1 − μ2. (Round your answers to two decimal places.) lower limitupper limit
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3. Can SAT scores predict college performance? Let x be a variable that represents SAT score of a computer science major, and let y be a variable that represents a student’s GPA upon graduation. A random sample of n =15 computer science majors provided their SAT scores and GPAs: x 1232 1070 1086 1287 1130 1048 1121 1095 1135 1208 1333 1160 1186 1243 1261 y 3.52 2.91 2.4 3.47 3.47 2.37 2.4 2.24 3.02 3.32 3.59 2.54 3.19 3.71 3.58 The scatter diagram for the SAT score and GPA is given below: (a) Find the sample correlation coefficient r. Truncate to two decimal places. What does the value tell you about the data? (b) Find the equation of the least squares line . Truncate to four decimal places. What does the slope mean? (c) Find the value of the coefficient of determination . Truncate to two decimal places. What does this number mean? (d) What is the predicted GPA if a computer science major got a…
Correlation studies are often used to help determine whether certain characteristics are controlled more by genetic influences or by environmental influences. These studies often examine adopted children and compare their behaviors with the behaviors of their birth parents and their adoptive parents. One study examined how much time individuals spend watching TV (Plomin, Corley, DeFries, & Fulker, 1990). The following data are similar to the results obtained in the study. a. Compute the correlation between the children and their birth parents. b. Compute the correlation between the children and their adoptive parents. c. Based on the two correlations, does TV watching appear to be inherited from the birth parents or is it learned from the adoptive parents?
A group is interested in seeing if the mean gas mileages from two different brands of gasoline are the same. To test this, they sampled 23 cars that used Type A gas and 17 cars that used Type B gas. From these samples, they calculated the following descriptive statistics (in terms of miles per gallon): Type A Gas Type B Gas ?n 23 17 ?⎯⎯⎯x¯ 29 29 ?s 4 5 (Assume the samples are independent and that the populations are normally distributed with unknown mean and standard deviation) (a) Is there significant evidence to suggest that there is a difference in gas milage? Test this at the ?=0.05α=0.05 significance level. State your conclusions regarding H0 (b) Calculate a 95% confidence interval for the true difference of the means. State your conclusions after calculating the interval.
2. A researcher had rats engage in a lever-press task for either a small, medium, or larger reward. The number of lever presses was the dependent variable. The data were as follows: Reward Size Small Medium Large 1 4 6 4 3 5 1 4 4 2 5 T = 13 SS = 2.75 T= 6 T= 20 SS = 9 SS = 2 EX2 = 165 a. Do the data indicate that reward size had a significant impact on lever-pressing? Use the hypothesis testing steps & p = .05. Compute any necessary post-hoc tests. b. Compute eta-squared to measure the effect size.
The following data represent soil water content (percent water by volume) for independent random samples of soil taken from two experimental fields growing bell peppers. Soil water content from field I: x1; n1 = 72 15.1 11.3 10.2 10.8 16.6 8.3 9.1 12.3 9.1 14.3 10.7 16.1 10.2 15.2 8.9 9.5 9.6 11.3 14.0 11.3 15.6 11.2 13.8 9.0 8.4 8.2 12.0 13.9 11.6 16.0 9.6 11.4 8.4 8.0 14.1 10.9 13.2 13.8 14.6 10.2 11.5 13.1 14.7 12.5 10.2 11.8 11.0 12.7 10.3 10.8 11.0 12.6 10.8 9.6 11.5 10.6 11.7 10.1 9.7 9.7 11.2 9.8 10.3 11.9 9.7 11.3 10.4 12.0 11.0 10.7 8.6 11.1 Soil water content from field II: x2; n2 = 80 12.3 10.3 13.6 8.1 13.5 7.8 11.8 7.7 8.1 9.2 14.1 8.9 13.9 7.5 12.6 7.3 14.9 12.2 7.6 8.9 13.9 8.4 13.4 7.1 12.4 7.6 9.9 26.0 7.3 7.4 14.3 8.4 13.2 7.3 11.3 7.5 9.7 12.3 6.9 7.6 13.8 7.5 13.3 8.0 11.3 6.8 7.4 11.7 11.8 7.7 12.6 7.7 13.2 13.9 10.4 12.9 7.6 10.7 10.7 10.9 12.5 11.3 10.7 13.2 8.9 12.9 7.7 9.7 9.7 11.4 11.9 13.4 9.2 13.4 8.8 11.9 7.1 8.6 14.0…

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