(mg/ml) Absorbancy 540nm 0 0.158 1 0.210 2 0.260 3 0.305 4 0.360 5 0.410 6 0.455 7 0.510 8 0.530 9 0.550 10 0.554 What
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You obtained the following raw data when setting up a Biuret standard curve:
| BSA (mg/ml) | Absorbancy 540nm |
| 0 | 0.158 |
| 1 | 0.210 |
| 2 | 0.260 |
| 3 | 0.305 |
| 4 | 0.360 |
| 5 | 0.410 |
| 6 | 0.455 |
| 7 | 0.510 |
| 8 | 0.530 |
| 9 | 0.550 |
| 10 | 0.554 |
What would the quality of the line-fit (R2 value) be if you do not exclude experimental outliers?
(Give you answer to 4 decimal places)
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- 3: A production manager at Ultra Clean Dishwashing Company is monitoring the quality of the company’s production process. There has been concern relative to the quality of the operation in accurately filling the 16 ounces of dishwashing liquid. Th e product is designed for a fill level of 16.00, ± 0.30. The company collected the following sample data on the production process: Observations Sample 1 2 3 4 1 16.40 16.11 15.90 15.78 2 15.97 16.10 16.20 15.81 3 15.91 16.00 16.04 15.92 4 16.20 16.21 15.93 15.92 5 15.87 16.21 16.34 16.43 6 15.43 15.49 15.55 15.92 7 15.43 16.21 15.99 16.00 8 15.50 15.92 16.12 16.02 9 16.13 16.21 16.05 16.01 10 15.68 16.43 16.20 15.97 a) Is the process mean in statistical control?My answers were incorrectA drug company claims that their products’ contaminations never vary by more than 2%. Sample of 5 specimens were tested and the percentages of the purities are recorded as Observation no. 1 2 3 4 5 Percentages (%) 98.6 97.2 98.9 97.7 97.9 a. Do the sample data have enough proof to oppose the manufacturer’s claim? (HINT: take the range of 2% equal 4σ.) b. Find a 90% confidence interval for σ2.
- Please answer numbers 4 to 6.1. 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?To compare the dry braking distances from 30 to 0 miles per hour for two makes of automobiles, a safety engineer conducts braking tests for 35 models of Make A and 35 models of Make B. The mean braking distance for Make A is 43 feet. Assume the population standard deviation is 4.6 feet. The mean braking distance for Make B is 46 feet. Assume the population standard deviation is 4.5 feet. At α=0.10, can the engineer support the claim that the mean braking distances are different for the two makes of automobiles? Assume the samples are random and independent, and the populations are normally distributed. The critical value(s) is/are Find the standardized test statistic z for μ1−μ2.
- need with bell shape curve pleaseThe mean exam score for 44. male high school students are 19.9 and the population standard deviation is 5.2. The mean exam score for 55female high school students is 19.4 and the population standard deviation is 4.9. At α=0.01, can you reject the claim that male and female high school students have equal exam scores? Complete parts (a) through (e). (a) Identify the claim and state H0 and Ha. What is the claim? A. Male high school students have lower exam scores than female students. B. Male and female high school students have different exam scores. C. Male and female high school students have equal exam scores. D. Male high school students have greater exam scores than female students. What are H0 and Ha? Find the critical value(s) and identify the rejection region(s). The critical value(s) is/are Find the standardized test statistic z for μ1−μ2.2. To investigate the effect of pH and catalyst concentration on product viscosity (sSt). Two levels of pH were used 5.6 and 5.9 and two catalyst concentration 2.5 and 2.7. Four products were tested with each combination of pH and catalyst. a. Use the estimate table below to test for main effects and interaction using a = 0.05. What are your conclusions? Predictor Constant Coefficient SDCoeff 191.563 165.49 pH 2.937 1.158 2.52 Catalyst -0.062 1.158 -0.05 pH*Catalyst 5.812 1.158 5.02 b. What is the value for the overall average viscosity? c. Write the regression model for this experiment. d. Below the interaction plot for the experiment. Discuss the information provided by the plot. To maximize viscosity what would be the recommended setting? Interaction Plot for Viscosity Data Mears 200 195 190- 185 Catalyst Concentration Mean Product Viscosity (cSt)
- Suppose μ₁ and ₂ are true mean stopping distances at 50 mph for cars of a certain type equipped with two different types of braking systems. The data follows: m = 8, x = 115.6, $₁=5.09, n = 8, y = 129.5, and s₂ = 5.33. Calculate a 95% CI for the difference between true average stopping distances for cars equipped with system 1 and cars equipped with system 2. (Round your answers to two decimal places.) USE SALT Does the interval suggest that precise information about the value of this difference is available? O Because the interval is so narrow, it appears that precise information is available. O Because the interval is so wide, it appears that precise information is available. O Because the interval is so narrow, it appears that precise information is not available. O Because the interval is so wide, it appears that precise information is not available.(note: use mu for mean or average, p for proportion, >= for >, <= for ≤, =/ for ‡ ) State the null and alternative hypotheses to be used in testing the following claims and determine generally where the critical region is located: (a) The mean snowfall at Lake George during the month of February is 21.8 centimeters. Ho: Blank 1 H1: Blank 2 (b) No more than 20% of the faculty at the local university contributed to the annual giving fund. Ho: Blank 3 H1: Blank 4 (c) At least 70% of next year's new cars will be in the compact and subcompact category. Ho: Blank 5 H1: Blank 6 (d) The average rib-eye steak at the Longhorn Steak house is at least 340 grams. Ho: Blank 7 H1: Blank 8A random sample of 17 adult male wolves from the Canadian Northwest Territories gave an average weight x1 = 98.6 pounds with estimated sample standard deviation s1 = 5.6 pounds. Another sample of 26 adult male wolves from Alaska gave an average weight x2 = 88.2 pounds with estimated sample standard deviation s2 = 6.0 pounds. (a) Categorize the problem below according to parameter being estimated, proportion p, mean μ, difference of means μ1 – μ2, or difference of proportions p1 – p2. Then solve the problem. μp μ1 – μ2p1 – p2 (b) Let μ1 represent the population mean weight of adult male wolves from the Northwest Territories, and let μ2 represent the population mean weight of adult male wolves from Alaska. Find a 99% confidence interval for μ1 – μ2. (Use 1 decimal place.) lower limit upper limit (c) Examine the confidence interval and explain what it means in the context of this problem. Does the interval consist of numbers that are all positive? all negative? of…
