The efficiency ratio for a steel specimen immersed in a  phosphating tank is the weight of the phosphate coating  divided by the metal loss (both in mg/ft2 ). The article  “Statistical Process Control of a Phosphate Coating  Line” (Wire J. Intl., May 1997: 78–81) gave the  accompanying data on tank temperature (x) and efficiency ratio (y). Temp. 170 172 173 174 174 175 176 Ratio .84 1.31 1.42 1.03 1.07 1.08 1.04 Temp. 177 180 180 180 180 180 181 Ratio 1.80 1.45 1.60 1.61 2.13 2.15 .84 Temp. 181 182 182 182 182 184 184 Ratio 1.43 .90 1.81 1.94 2.68 1.49 2.52 Temp. 185 186 188 Ratio 3.00 1.87 3.08 a. Construct stem-and-leaf displays of both temperature and efficiency ratio, and comment on interesting  features. b. Is the value of efficiency ratio completely and uniquely determined by tank temperature? Explain your   reasoning. c. Construct a scatterplot of the data. Does it appear  that efficiency ratio could be very well predicted by  the value of temperature? Explain your reasoning.

Laetisaric acid is a compound that holds promise for control of fungus diseases in crop plants. The accompanying data show the results of growing the fungus Pythium (y) in various concentrations of laetisaric acid (x). Laetisaric acid concentration (uG/mL) Fungus growth (mm) 0. 33.3 31.0 29.8 27.8 6. 28.0 6. 29.0 10 25.5 10 23.8 20 18.3 20 15.5 30 11.7 30 10.0 Mean 11.500 23.642 Standard deviation 10.884 7.8471 T =-0.98754 %3D a. State the linear regression equation, and with a 0.01 level of significance, predict the amount (in mm) of fungus growth when 25 uG/mL laetisaric acid is applied. Assume the pairs of data follow a bivariate normal distribution and that the scatterplot shows no evidence of a non-linear relationship in the data. b. Determine the percentage of the variation in fungus growth that is explained by the linear relationship between laetisaric acid concentration and fungus growth. Attack Eil

Chlorophylls a and b are plant pigments that absorb sunlight and transfer the energy into photosynthesis of carbohydrates from CO2 and H2O, releasing O2 in the process. Chlorophylls were extracted from chopped up grass and measured by spectrophotometry. The table shows results for chlorophyll a for four separate analysis of five blades of grass. Chlorophyll a (g/L) Blade 1 Blade 2 Blade 3 Blade 4 Blade 5 1.09 1.26 1.1 1.23 0.85 0.86 0.96 1.21 1.3 0.65 0.93 0.8 1.27 0.97 0.86 0.99 0.73 1.12 0.97 1.03 Four replicate measurements for each blade of grass tell us the precision of the analytical procedure (sanalysis). Differences between mean values for each of the five blades of grass are a measure of variation due to sampling (ssampling). Using Excel and it’s ANOVA function, find the standard deviations attributable to sampling and to analysis, as well as the overall standard deviation arising from both sources.

PLEASE ANSWER ALL THE PARTS OF QUESTION (THIS IS NOT A HRADED ASSIGNMENT)

Access the significsnce of each of the variables in the attached table. For age, write out all of the steps for hypothesis testing. For the other variables, report a p-value and conclusion. Write out the interpretation of the hazards ratios for age and sex in words. What is the estimated hazard ratio for a 10-year increase in age?

Given below are the ages and heart rates of 50 patents aho participated in a dinical tral for a new ant-hypertersive drug A a Graphicaly, what can you conclude about the relationship between age and heart rate? B. b. Test the hypothesis that p= 0 against the altemative that p0 at the 0.05 level of significance| Heart Rate (y) 100 76 Patient No. Age Patient No. Age Heart Rate 1 48 26 39 72 2 45 27 56 70 3 67 70 28 51 76 4 44 72 29 41 68 57 62 64 30 31 32 49 76 70 79 92 72 70 76 53 58 60 62 33 67 76 47 34 54 68 37 76 86 10 84 35 49 11 52 90 36 54 12 66 90 37 44 81 13 33 80 38 69 72 14 30 68 39 45 80 15 41 72 40 39 80 16 52 74 41 37 72 17 40 30 76 42 45 52 86 18 88 43 72 19 35 84 44 44 76 20 49 70 45 28 39 76 21 62 51 72 68 46 74 68 22 47 49 72 23 41 76 48 80 24 55 70 49 52 80 25 63 68 s0 27 82

Aa Febru The body mass index (BMI) of a person is defined to be the person's body mass divided by the square of the person's height. The article "Influences of Parameter Uncertainties within the ICRP 66 Respiratory Tract Model: Particle Deposition" (W. Bolch, E. Farfan, et al., Health Physics, 2001:378-394) states that body mass index (in kg/m2) in men aged 25-34 is lognormally distributed with parameters u = 3.215 and o = 0.157. a.Find the mean and standard deviation BMI for men aged 25-34. b.Find the standard deviation of BMI for men aged 25-34. c.Find the median BMI for men aged 25-34. d.What proportion of men aged 25-34 have a BMI less than 20? e.Find the 80th percentile of BMI for men agėd 25 -34. 04... Rext 田

Mist (airborne droplets or aerosols) is generated when metal- removing fluids are used in machining operations to cool and lubricate the tool and workpiece. Mist generation is a concern to OSHA, which has recently lowered substantially the workplace standard. The article "Variables Affecting Mist Generaton from Metal Removal Fluids" (Lubrication Engr., 2002: 10-17) gave the accompanying data on x = fluid-flow velocity for a 5% soluble oil (cm/sec) and y = the extent of mist droplets having diameters smaller than 10 μm (mg/m³): x y 89 177 189 354 362 442 965 .40 .60 .48 .66 .61 .69 .99 a. The investigators performed a simple linear regres- sion analysis to relate the two variables. Does a scat- terplot of the data support this strategy? b. What proportion of observed variation in mist can be attributed to the simple linear regression relationship between velocity and mist? c. The investigators were particularly interested in the impact on mist of increasing velocity from 100 to 1000 (a…

A study of a high-pressure inlet fogging method for a gas turbine engine analyzed a complete second-order model for y, heat rate (kilojoules per kilowat per hour) of a gas turbine as a function of two quantitative variables

A number of studies have shown lichens (certain plants composed of an alga and a fungus) to be excellent bio-indicators of air pollution. An article gives the following data (n = 13) on x = NO3- wet deposition (g N/m²) and y = lichen (% dry weight): x 0.05 0.10 0.11 0.12 0.31 0.37 0.42 0.58 0.68 0.68 0.73 0.85 0.92 y 0.53 0.58 0.45 0.54 0.57 0.53 1.03 0.89 0.90 1.02 0.91 1.00 1.66 Predictor Constant no3 depo Estimate 0.39329 0.9286 0.1767 S = 0.1866 R-sq = 71.5% Standard Error 0.09566 t Stat 4.11 5.26 p-value 0.002 0.000 R-sq (adj) = 68.9% (a) What are the least square estimates of B and ẞ₁? (Round your answers to three decimal places.) bo = = (b) What is the margin of error for a 95% CI for ẞ₁? (Round your answer to four decimal places.) Margin of Error = (c) Predict lichen N for an NO3 - deposition value of 0.7. (Round your answer to three decimal places.) % dry weight (d) What is the estimate of σ? (Round your answer to four decimal places.) S = % dry weight