Hydrogen 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 y 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 0. State the appropriate null and alternative hypotheses. O Ho: p = 0 Hip<0 O Ho: p = 0 H:p > 0 O Hoi p = 0 H,ip #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.) 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 from 0. O Reject H,. The data suggests that the population correlation coefficient differs significantly from 0. O Fail to reject H. The data suggests that the population correlation coefficient differs significantly from 0. O Reject Hg. The data does not suggest that the population correlation coefficient differs significantly from 0. (b) If a simple linear regression analysis had been carried out, what percentage of observed variation in porosity could be attributed to the model relationship? (Round your answer to one decimal place.) %

1.8 A Canadian manufacturer identified a critical diameter on a crank bore that needed to be maintained within a close tolerance for the product to be successful. Sam- ples of size 4 were taken every hour. The values of the differences (measurement - specification), in ten- thousandths of an inch, are given in Table 1.4. (a) Calculate the central line for an X-bar chart for the 24 hourly sample means. The centerline is x = — . . . (4.25 -3.00 -1.50 +3.25)/24. = (b) Is the average of all the numbers in the table, 4 for each hour, the same as the average of the 24 hourly averages? Should it be? (c) A computer calculation gives the control limits LCL = -4.48 UCL 7.88 = Construct the X-bar chart. Identify hours where the process was out of control.

Please don’t use excel

The table below lists different amounts (metric tons) of explosives and the corresponding value on the Richter scale for the explosions. Construct a scatterplot and identify the mathematical model that best fits the given data. x (metric tons) 3 12 17 43 114 463 y (Richter scale) 2.9 3.8 4.1 4.4 4.6 5.1 2.5+ 2.5- 600 2.5- 600 2.5- 600 600 What is the equation of the best model? Select the correct choice below and fill in the answer boxes to complete your choice. Enter only nonzero values. (Type integers or decimals rounded to three decimal places as needed.) O A. y= (Dr O B. In x y = Oc. y = x + x+ OD. y= O E. y= +

1. Model 1: OLS, using observations 1-706 Dependent variable: RST   Coefficient Std. Error t-ratio p-value   const 3586.38 38.9124 92.17 <0.0001 *** TOTWRK −0.150746 0.0167403 −9.005 <0.0001 ***   Mean dependent var 3266.356 S.D. dependent var 444.4134 Sum squared resid 1.25e+08 S.E. of regression 421.1357 R-squared 0.103287 Adjusted R-squared 0.102014 F(1, 704) 81.08987 P-value(F) 1.99e-1810538.19 Log-likelihood −5267.096 Akaike criterion 10538.19 Schwarz criterion 10547.31 Hannan-Quinn 10541.71 RSTi =3586.38−0.150746 x TOTWRKi , R2=0.103287,SER=421.1357                                     (38.9124) (0.0167403)   Question? could you please help with this question below. 3) By observing the GRETL output in Part (1) above, provide a detailed explanation of the coefficient of determination. Based on your analysis, is this a good model? Why or why not?

12

could you write with a pen and paper?

1-What these statistics tell you about the kurtosis of the variables:

Answer asap please

The accompanying specific gravity values describe various wood types used in construction. 0.33 0.35 0.36 0.36 0.37 0.38 0.40 0.40 0.40 0.41 0.41 0.42 0.42 0.42 0.42 0.42 0.43 0.44 0.45 0.46 0.46 0.47 0.48 0.48 0.49 0.53 0.54 0.54 0.55 0.58 0.61 0.66 0.66 0.67 0.68 0.77 Construct a stem-and-leaf display using repeated stems. (Enter numbers from smallest to largest separated by spaces. Enter NONE for stems with no values.)