A process engineer is trying to improve the life of a cutting tool. He has run a 2³ experimentusing cutting speed (A), metal hardness (B), and cutting angle (C) as the factors. The datafrom two replicates are shown in Table 13E.2.(1) Calculate the main effects of A, B, C, and all interaction effects.(2) Do any of the three factors affect tool life? Make an ANOVA table and draw conclusionfrom the F-values with α = 0.05.(3) What combination of factor levels produces the longest tool life?■ TABLE 13E.2Data for the Experiment in Exercise 13.2.ReplicateRunIII(1)221311a325435b354348ab552472с440453སྣ་ ནྟི406377bc605500abc392419

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Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.5: Correlation And Causation

Problem 11PPS

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What is an experiment?
An agricultural field trial compares the yield of two varieties of corn. The researchers divide in half each of 20 fields of land in different locations and plant each corn variety in one half of each plot. After harvest, the yields are compared in bushels per acre at each location. The 20 differences (Variety A - Variety B) givex¯=3.2x¯=3.2 and s=4.63s=4.63. Does this sample provide evidence that Variety A had a higher yield than Variety B? (a) State the null and alternative hypotheses: (Type "mu" for the symbol μμ , e.g. mu >> 1 for the mean is greater than 1, mu << 1 for the mean is less than 1, mu not = 1 for the mean is not equal to 1) H0H0 : HaHa : (b) Find the test statistic, t = (c) Answer the question: Does this sample provide evidence that Variety A had a higher yield than Variety B? (Use a 5% level of significance) (Type: Yes or No)
Beachcomber Ltd in a local car dealership that sells used and new vehicles. The manager of thecompany wants to know how different variables affect the sales of his vehicles. A random sample ofyearly data was taken with the view to testing the model:SALES=?+?AGE+?MIL+?ENGWhere SALES= amount that a vehicle is sold for($000’s), AGE = age of the vehicle, MIL= the totalmileage of the vehicle at the point of sale and ENG = the size of the engine. The sample of data wasprocessed using MINITAB and the following is an extract of the output obtained:The regression equation is *****PredictorCoef StDev t-ratio p-valueConstant1.7586 0.2525 6.9648 0.0000AGE 0.2124 0.3175 * 0.5042MIL -0.75270.3586 -2.0991 **ENG 4.8124 0.6196 7.7664 0.0000Analysis of VarianceSource DF SS MS F pRegression3 413.1291 138.7097*** 0.00Error 50 457.7607 2.2888Total 53a) What is dependent and independent variables? b) Fully write out the regression equation c) Fill in the missing values ‘*’, ‘**’, ‘***’and ‘***’. d) Hence…
Beachcomber Ltd in a local car dealership that sells used and new vehicles. The manager of thecompany wants to know how different variables affect the sales of his vehicles. A random sample ofyearly data was taken with the view to testing the model:SALES=?+?AGE+?MIL+?ENGWhere SALES= amount that a vehicle is sold for($000’s), AGE = age of the vehicle, MIL= the totalmileage of the vehicle at the point of sale and ENG = the size of the engine. The sample of data wasprocessed using MINITAB and the following is an extract of the output obtained: a) What is dependent and independent variables? b) Fully write out the regression equation c) Fill in the missing values ‘*’, ‘**’, and ‘***’. d) Hence test whether ? is significant. Give reasons for your answer. e) Perform the F Test making sure to state the null and alternative hypothesis. f) Given an interpretation of the term “R-sq” and comment on its value.
A medical student at a community college in city Q wants to study the factors affecting the systolic blood pressure of a person (Y). Generally, the systolic blood pressure depends on the BMI of a person (B) and the age of the person A. She wants to test whether or not the BMI has a significant effect on the systolic blood pressure, keeping the age of the person constant. For her study, she collects a random sample of 150 patients from the city and estimates the following regression function: Y= 15.50 +0.90B + 1.10A. (0.48) (0.35) The test statistic of the study the student wants to conduct (Ho: B, =0 vs. H4: B, #0), keeping other variables constant is. (Round your answer to two decimal places.) At the 5% significance level, the student will v the null hypothesis. Keeping BMI constant, she now wants test whether the age of a person (A) has no significant effect or a positive effect on the person's systolic blood pressure. So, the test statistic associated with the one-sided test the…
Dr. Ortega took a wide sample of people and timed them running a mile. There is a lot of variability in time, with some runners taking 5 minutes and others 20 minutes or more. Analyzing this further, Dr. Ortega wants to know what factors influence running speed? She hypothesizes that physical fitness and age play important roles, as do physical health and weight. For further clarity, Dr. Ortega calculates r2 for each variable and finds that the effect size for physical fitness is 29%. In 50 words or less, explain what this means. View keyboard shortcuts EditViewInsertFormatToolsTable 12pt Paragraph Dr. Ortega took a wide sample of people and timed them running a mile. There is a lot of variability in time, with some runners taking 5 minutes and others 20 minutes or more. Analyzing this further, Dr. Ortega wants to know what factors influence running speed? She hypothesizes that physical fitness and age play important roles, as do physical…
Foot ulcers are a 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 181 diabetic patients. The results are presented in the following table. Left Foot Right Foot 80 80 85 85 75 80 88 86 89 87 87 82 78 78 88 89 89 90 76 81 89 86 87 82 78 78 80 81 87 82 86 85 76 80 88 89 Construct a scatterplot of the right foot temperature (y) versus the left foot temperature (x). Verify that a linear model is appropriate. b. Compute the least-squares line for predicting the right foot temperature from the left foot temperature. If the left foot temperatures of two patients differ by 2 degrees, by how much would you predict their right foot temperatures to differ? Predict the right foot temperature for a patient whose left…
An agricultural field trial compares the yield of two varieties of corn. The researchers divide in half each of 9 fields of land in different locations and plant each corn variety in one half of each plot. After harvest, the yields are compared in bushels per acre at each location. The 9 differences (Variety A - Variety B) give x¯=3.35x¯=3.35 and s=4.61s=4.61. Does this sample provide evidence that Variety A had a higher yield than Variety B? (a) State the null and alternative hypotheses: (Type "mu" for the symbol μμ , e.g. mu >> 1 for the mean is greater than 1, mu << 1 for the mean is less than 1, mu not = 1 for the mean is not equal to 1)H0H0 : HaHa : (b) Find the test statistic, t = (c) Answer the question: Does this sample provide evidence that Variety A had a higher yield than Variety B? (Use a 5% level of significance)(Type: Yes or No)
Bardi Trucking Co., located in Cleveland, Ohio, makes deliveries in the Great Lakes region, the Southeast, and the Northeast. Jim Bardi, the president, is studying the relationship between the distance a shipment must travel and the length of time, in days, it takes the shipment to arrive at its destination. To investigate, Mr. Bardi selected a random sample of 20 shipments made last month. Shipping distance is the independent variable and shipping time is the dependent variable. The results are as follows: b-1. Fill in the blanks. (Round your answers to 3 decimal places. Negative values should be indicated by minus sign.) x⎯⎯x¯ y⎯⎯y¯ Sx Sy r b-2. State the decision rule for 0.01 significance level: H0: ρ ≤ 0; H1: ρ > 0. (Round your answer to 3 decimal places.) b-3. Compute the value of the test statistic. (Negative value should be indicated by a minus sign. Round your answer to 3 decimal places.) b-4. Can we…
8. You collect data on people's height and study the relationship between gender and height. A regression of the height on a binary variable (Female), which takes a value of one for females and zero otherwise, yields the following result: Height = 71.0- 4.84 x Female, R2 = 0.40, SER = 2.0 (0.3) (0.57) (a) What is the sample average male height? (b) What is the sample average female height? I (c) How to interpret the slope coefficient -4.84? (d) Is the error term in the regression more likely to be heteroskedastic or homoscedastic? Why? R English (United States) D'Focus Page 9 of 10 920 words 100%
The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. The bivariate data given below were taken from a sample of sixteen Cadets, each bought new two years ago, and each sold used within the past month. For each Cadet in the sample, we have listed both the mileage x (in thousands of miles) that the Cadet had on its odometer at the time it was sold used and the price y (in thousands of dollars) at which the Cadet was sold used. With the aim of predicting the used selling price from the number of miles driven, we might examine the least-squares regression line, Ŷ=42.39-0.52x. This line is shown in the scatter plot below. (The 2nd picture contains the rest of the data as it would not fit in the first pic and it includes the question as well.)
The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. The bivariate data given below were taken from a sample of sixteen Cadets, each bought new two years ago, and each sold used within the past month. For each Cadet in the sample, we have listed both the mileage x (in thousands of miles) that the Cadet had on its odometer at the time it was sold used and the price y (in thousands of dollars) at which the Cadet was sold used. The least-squares regression line for these data has equation Ŷ=42.80-0.53x. This line is shown in the scatter plot below. (The 2nd picture contains the rest of the data as it would not fit in the first pic and it includes the question as well.)

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