A tire company claims that their new tires will have an average life of 122000 miles. A consumer group wishesto test this claim at the a = 0.05 level of significance.Which would be correct hypotheses for this test?O Ho:u = 122000, H : µ 122000o Ho:u = 122000, H1: µ < 122000Ho:u < 122000, H1 : µ = 122000O Ho:u 122000, H1 : µ = 122000o Ho:u = 122000, H1: µ > 122000A random sample of 46 sets of tires were tested and had an average life of 121945 miles, with a standarddeviation of 66.8 miles.Find the test statistic (2 decimal places):Give the P-value (4 decimal places, if less than 0.001 answer 0):Which is the correct result:O Do not Reject the Null HypothesisO Reject the Null HypothesisWhich would be the appropriate conclusion?O There is not significant evidence to suggest that the average life of the tires is different than 122000There is significant evidence to suggest that the average life of the tires is different than 122000 miles

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Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.1: Measures Of Center

Problem 9PPS

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0. 40 Define the term of Experimental Error ?
A diet center wanted to test three different methods for losing weight to determine if the average weight loss (reported in pounds/week) for each method is the same. The results for the three methods are tabulated below. Given that there is a significant difference between the three methods, use the Tukey test to determine if there is a significant difference between each pair of methods. Let a=0.05. (picture attached)
According to the CDC, the average weight of men in 1990 was 181 pounds. Consider a claim that the average weight of men increased by 2014. (https://abcnews.go.com/Health/average-weight-american-men-15-pounds-20-years/story?id=41100782) Use these hypotheses: H0:H0: μμ = 181(Population mean weight of men in 2014 is same as that in 1990) Ha:Ha: μμ > 181(Population mean weight of men in 2014 has increased) Based on sample data, you fail to reject the null hypothesis and compared to the unknown truth if your decision was wrong, then you would have made: Type I Error because H0H0 was incorrectly rejected. Type II Error because H0H0 was incorrectly not rejected. Based on sample data, you fail to reject the null hypothesis. Then your conclusion would be: The sample data support the claim that the average weight of men increased. There is not sufficient sample evidence to support the claim that the average weight of men increased.
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A veterinarian claims that the mean weight of German Shepherd Dogs is 75 pounds. A test is made. The hypotheses are Ho: μ = 75 and Ha: μ ≠ 75. Explain a type 1 error
According to the CDC, the average weight of men in 1990 was 181 pounds. Consider a claim that the average weight of men increased by 2014. (https://abcnews.go.com/Health/average-weight-american-men-15-pounds-20-years/story?id=41100782) Use these hypotheses: H0: μ = 181(Population mean weight of men in 2014 is same as that in 1990) Ha: μ > 181(Population mean weight of men in 2014 has increased) Based on sample data, you fail to reject the null hypothesis and compared to the unknown truth if your decision was wrong, then you would have made: Type II Error because H0H0 was incorrectly not rejected. Type I Error because H0H0 was incorrectly rejected. Based on sample data, you fail to reject the null hypothesis. Then your conclusion would be: The sample data support the claim that the average weight of men increased. There is not sufficient sample evidence to support the claim that the average weight of men increased.
A researcher is interested in testing the relationship between smoking and BMI (kg/m2) in adults aged 30-45. In order to test this association, the researcher divides smoking into currently more than a pack a day, currently less than a pack a day, and never smokers. The following table represents the BMIs for each participant enrolled by their respective smoking category. Current Smoker (≥1pack/day) Current Smoker (<1 pack/day Never Smoked 26.7 29.4 22.1 29.4 28.6 30.4 24.3 27.4 21.3 28.4 23.2 26.4 21.6 20.1 19.7 27.4 20.6 19.8 26.8 19.7 21.6 36.4 19.6 22.3 31.5 21.6 24.3 27.4 21.5 *Continue as though all assumptions for ANOVA are met. A) Calculate the MSW and MSB for the data represented above. B) Carry out a formal test for a one-way analysis of variance among the groups and interpret your results.

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