o determine whether a linear relationship exists between stiffness x (mg-cm) and thickness y (mm). 8.07 24.69 12.33 6.85 24.22 35.69 0.29 0.65 0.31 0.27 0.80 0.57 State the appropriate null and alternative hypotheses. O Ho: P = 0 H₂: P o O Ho: P=0 H₂: P = 0 y O Ho: P =0 H₂: P = 0 Compute the val sample correlation coefficient Round your answer to four decimal places
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- 1. Analyze the data as a two way factorial design. Johnson and Leone (Statistics and Experimental Design in Engineering and the Physical Sciences, Wiley, 977) describe an experiment to investigate warping of copper plates. The two factors studied were the temperature and the copper content of the plates. The response variable was a measure of the amount of warping. The data were as follows: Temperature (°C) 50 75 100 125 40 17, 20 12,9 16, 12 21, 17 Copper Content (%) 60 80 16, 21 18, 13 18, 21 23, 2! 24, 22 17, 12 25, 23 23, 22 100 28, 27 27, 31 30, 23 29, 31Hydrogen content is conjectured to be an important factor in porosity of aluminum alloy castings. An article gives the accompanying data on x = content and y = gas porosity for one particular measurement technique. 0.18 0.20 0.21 0.21 0.21 0.22 0.23 0.23 0.24 0.24 0.25 0.28 0.30 0.37 0.48 0.71 0.42 0.44 0.55 0.44 0.24 0.48 0.22 0.82 0.86 0.72 0.70 0.74 Minitab gives the following output in a response to a Correlation command: Correlation of Hydrcon and Porosity = 0.425 (a) Test at level 0.05 to see whether the population correlation coefficient differs from o. State the appropriate null and alternative hypotheses. O Ho: p = 0 Hip 0 O Ho: p = 0 Hip + 0 O Ho: p+0 Hip = 0 Calculate the test statistic and determine the P-value. (Round your test statistic to two decimal places and your P-value to three decimal places.) t = P-value = State the conclusion in the problem context. O Fail to reject H: The data does not suggest that the population correlation coefficient differs significantly…A river was contaminated with waste materials. Specimens of these materials were collected andtheir physical appearance recorded as shown in Table 3. Is there evidence of association betweencolor and texture for these waste materials based on the given hypothesis? Explain your findings.Use ? = 0.05.H0: No relationship between texture and colourH1: Relationship exist between texture and colour colour colour colour texture light medium dark fine 4 20 8 medium 5 23 12 coarse 21 23 4
- Han Samples are collected from the River X and pH values are observed. 9 different pH values are listed in table 3. Table 3 Concentrations 4.2 3.8 6.0 3.5 8.1 4.9 4.1 3.2 4.0Draw box plot and find a. Bowley’s coefficient of skewness b. Karl Pearson’s coefficient of skewness c. Third momentWhen computing the Z value to compare between two samples of two populations, o2 is a parameter of the statistical equation. Select one: O True O FalseFifty male subjects drank a measured amount x (in ounces) of a medication and the concentration y (in percent) in their blood of the active ingredient was measured 30 minutes later. The sample data are summarized by the following information: n = 50 Ex = 112.5 Ex? = 356.25 %3D Ey = 4.83 Ey = 0.667 Exy = 15.255 0 < x < 4.5 Or= 0.875 Or= 0.709 Or= -0.846 Or=0.460 Or= 0.965
- The average life expectancy of tires 40,000 miles. The company has rece The manager hopes to find out wheth life test, 40 tires were used, and their following SPSS results: One-Sample Statistics Std. Dev Mean time 40881.8262 40 2945 One- df Sig. (2-taile 1.893 Set up Ho: M = 40,000 %3D HA: The test statistic is 1.893 The distribution of the test stati Make the statistical decision (o Express the statistical decisionArm circumferences (cm) and heights (cm) are measured from randomly selected adult females. The 142 pairs of measurements yield x=32.14cm, y=163.36cm, r=.084, P value=.32 and y=160+.111x. Find the best predicted value of y (height) given an adult female with an arm circumference of 40cm. Let the predictor variable x be arm circumference and the response variable y be height. Use a .05 significance level.The price X (dollars per pound) and consumption y (in pounds per capita) of beef were samples for 10 randomly selected years. The following data should be used to answer the question that follows. n = 10 Ex = 36.19 Ix² = 134.17 2.9 < x s 6.2 Ey = 774.7 Iy² = 60739.23 Exy = 2832.21 Using this data, a student calculated SSy = 28.43 SSx = 3.2 SSy= 717. Calculate the %3D %3D value of the standard error or regression, Se , and enter you answer accurate to the nearest hundredth (2 decimal places).
- Foot ulcers are common problem for people with diabetes. Higher skin temperatures on the foot indicate an increased risk of ulcers. The article “An Intelligent Insole for Diabetic Patients with the Loss of Protective Sensation" (Kimberly Anderson, M.S. Thesis, Colorado School of Mines), reports measurements of temperatures, in °F, of both feet for 18 diabetic patients. The results are presented in the Table Q1. Table Ql: Measurements of temperatures, in °F of left foot Vs right foot for 18 diabetic patients Left Foot Right Foot Left Foot Right Foot 80 80 76 81 85 85 89 86 80 86 75 87 82 88 78 78 89 87 80 81 87 82 87 82 78 78 86 85 88 89 76 80 89 90 88 89 (d) Test the slope, ß1 = 1 at 5% level of significance. (e) Calculate the coefficient of correlation r and r2 and then interpret their values7. Inertial weight (in tons) and fuel economy (in mi/gal) were measured for a sample of seven diesel trucks. The results are presented in the following table. Weight 8.00 24.50 27.00 14.50 28.50 12.75 21.25Mileage 7.69 4.97 4.56 6.49 4.34 6.24 4.45 (a) Construct a scatterplot of mileage (y) versus weight (x). Verify that a linear model is appropriate.(b) Compute the least-square line for predicting mileage from weight.(c) If two trucks differ in weight by 5 tons, by how much would you predict their mileags differ?(d) Predict the mileage for trucks with a weight of 15 tons.(e) Find all predicted values and residuals for this regression model.(f) Compute the estimate for the error variance.(g) Construct 95% two-sided confidence intervals for intercept and slope parameters.A sociologist wants to determine if the life expectancy of people in Africa is less than the life expectancy of people in Asia. The data obtained is shown in the table below. Africa Asia = 63.3 yr. 1 X,=65.2 yr. 2 o, = 9.1 yr. = 7.3 yr. n1 = 120 = 150