Explanation The given test hypotheses are: Null hypothesis: H 0 : μ = 70 . Alternate hypothesis: H 1 : μ ≠ 70 . It is given that the level of significance α = 0.05 . P-value : P- value is defined as the probability of obtaining a result at least as extreme as the observed value, given that the null hypothesis H 0 is true. The test is said to be statistically significant when P -value < α , for level of significance α . Decision based on the P -value method: If P − value ≤ α , reject H 0

2nd Edition

ISBN: 9781266836428

Author: Navidi

Publisher: MCG

See similar textbooks

Question

Chapter 8.2, Problem 69E

To determine

Explain whether any additional information is necessary to be included in the report and identify such information.

Expert Solution & Answer

Want to see the full answer?

Check out a sample textbook solution

See solution

Chapter 8.2, Problem 68E

Chapter 8.2, Problem 70E

Students have asked these similar questions

Question 2 A nickel-titanium alloy is used to make components for jet turbine aircraft engines. Cracking is a potentially serious problem in the final part because it can lead to nonrecoverable failure. A test is run at the parts producer to determine the effect of four factors on cracks. The four factors are: pouring temperature (A), titanium content (B), heat treatment method (C), amount of grain refiner used (D). Two replicates of a 24 design are run, and the length of crack (in mm x10-2) induced in a sample coupon subjected to a standard test is measured. The data are shown in Table 2. 1 (a) Estimate the factor effects. Which factor effects appear to be large? (b) Conduct an analysis of variance. Do any of the factors affect cracking? Use a = 0.05. (c) Write down a regression model that can be used to predict crack length as a function of the significant main effects and interactions you have identified in part (b). (d) Analyze the residuals from this experiment. (e) Is there an…

A 24-1 design has been used to investigate the effect of four factors on the resistivity of a silicon wafer. The data from this experiment are shown in Table 4. Table 4: Resistivity Experiment for Exercise 5 Run A B с D Resistivity 1 23 2 3 4 5 6 7 8 9 10 11 12 I+I+I+I+Oooo 0 0 ||++TI++o000 33.2 4.6 31.2 9.6 40.6 162.4 39.4 158.6 63.4 62.6 58.7 0 0 60.9 3 (a) Estimate the factor effects. Plot the effect estimates on a normal probability scale. (b) Identify a tentative model for this process. Fit the model and test for curvature. (c) Plot the residuals from the model in part (b) versus the predicted resistivity. Is there any indication on this plot of model inadequacy? (d) Construct a normal probability plot of the residuals. Is there any reason to doubt the validity of the normality assumption?

Stem1: 1,4 Stem 2: 2,4,8 Stem3: 2,4 Stem4: 0,1,6,8 Stem5: 0,1,2,3,9 Stem 6: 2,2 What’s the Min,Q1, Med,Q3,Max?

Chapter 8 Solutions

ALEKS 360 ESSENT. STAT ACCESS CARD

Ch. 8.1 - Check Your Understanding 1. Last year, the mean...Ch. 8.1 - Prob. 2CYU Ch. 8.1 - Prob. 3CYU Ch. 8.1 - Prob. 4CYU Ch. 8.1 - Prob. 5CYU Ch. 8.1 - Prob. 6CYU Ch. 8.1 - Prob. 7E Ch. 8.1 - Prob. 8E Ch. 8.1 - Prob. 9E Ch. 8.1 - In Exercises 9–12, determine whether the statement...

Knowledge Booster