A researcher conducted an experiment to test the effects of running 3 differenttypes of gasoline with 3 possible types of additive on the mileage obtained. Theexperiment assumed that there is an interaction between gasoline type and thetype of additive,hence, a two-factor ANOVA was employed in the data analysis. It was decided torun 36 motors - 4 in each factor level combinations. The following are theanalysis resultsMEANGAS TYPE 1GAS TYPE 2GAS TYPE 3ADDITIVE 1125.825127126.35126.3917ADDITIVE 2130.775133.6132.5132.2917ADDITIVE 3128.275137.825123129.7128.2917132.8083127.2833129.4611Analysis of Variance TableDfSum SqMean SqF ValuePr(>F)factor(gas.ty2207.7706103.885311.084820.000306pe)factor(additi2209.8872104.943611.197750.000287ve)factor(gas.type):factor(ad 4ditive)Residuals262.967865.741947.014830.00052327|253.049.371852NANAa.) Is there a significant interaction between the type of gasoline and the type of additive?Why?b.) What does the result on the test for significant interaction imply?c.) Say you are to choose between the three gasoline types, regardless of the type of additiveused and considering all other factors constant. Which gasoline would you prefer for yourmotor and why?

A researcher conducted an experiment to test the effects of running 3 different types of gasoline with 3 possible types of additive on the mileage obtained. The experiment assumed that there is an interaction between gasoline type and the type of additive, hence, a two-factor ANOVA was employed in the data analysis. It was decided to run 36 motors - 4 in each factor level combinations. The following are the analysis results MEAN

A researcher conducted an experiment to test the effects of running 3 different types of gasoline with 3 possible types of additive on the mileage obtained. The experiment assumed that there is an interaction between gasoline type and the type of additive, hence, a two-factor ANOVA was employed in the data analysis. It was decided to run 36 motors - 4 in each factor level combinations. The following are the analysis results MEAN

Big Ideas Math A Bridge To Success Algebra 1: Student Edition 2015

1st Edition

ISBN:9781680331141

Author:HOUGHTON MIFFLIN HARCOURT

Publisher:HOUGHTON MIFFLIN HARCOURT

Chapter4: Writing Linear Equations

Section: Chapter Questions

Problem 14CR

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A researcher conducted an experiment to test the effects of running 3 different types of gasoline with 3 possible types of additive on the mileage obtained. The experiment assumed that there is an interaction between gasoline type and the type of additive,hence, a two-factor ANOVA was employed in the data analysis. It was decided to run 36 motors – 4 in each factor level combinations. The following are the analysis results MEAN ADDITIVE 1 ADDITIVE 2 ADDITIVE 3 GAS TYPE 1 125.825 130.775 128.275 128.2917 GAS TYPE 2 127 133.6 137.825 132.8083 GAS TYPE 3 126.35 132.5 123 127.2833 126.3917 132.2917 129.7 129.4611 Analysis of Variance Table Df Sum Sq Mean Sq F Value Pr(>F) factor(gas.type) 2 207.7706 103.8853 11.08482 0.000306 factor(additive) 2 209.8872 104.9436 11.19775 0.000287 factor(gas.type):factor(additive) 4 262.9678 65.74194 7.01483 0.000523 Residuals 27 253.04 9.371852 NA NA a.) Is there a significant interaction between the type of…
There are 39 observations representing the 39 Peruvians in the dataset and 10 variables. Factor Analysis was performed on the data set, giving the following result for the factor loadings based on the correlation matrix, with PC as factor extraction method unrotated and using 3 factors. Variable Age Years Weight Height Chin Forearm Calf Pulse Systol Diastol Factor Loadings (Unrotated) (peruvian) Extraction: Principal components (Marked loadings are >.500000) Factor 2 Factor 1 -0.349816 0.763287 -0.416995 0.764342 -0.884494 0.243825 -0.255384 0.188597 -0.707324 -0.104618 -0.789642 -0.327357 -0.679921 -0.456050 -0.465664 0.034710 -0.522348 -0.274233 -0.479173 -0.166765 Factor 3 0.078367 0.169844 -0.220992 -0.680960 0.363285 0.365142 0.221273 0.272035 -0.538937 -0.562990 What is the specific variance of the variable Years? (final answer to 3 decimal places)
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 125 patients from the city and estimates the following regression function: Y= 15.50 + 0..90B+1.15A. (0.55) (0 40) The test statistic of the study the student wants to conduct (Ho: B, = 0 vs. H, B, #0), keeping other variables constant is. (Round your answer to two decimal places.) At the 5% significance level, the student will ▼ the null hypothesis. Keeping BMIl constant, she now wants to 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…
The administrators of a Faculty A were interested to understand personal characteristics of their students. They decided to conduct a survey and managed to get randomly 1625 students to respond to the survey. The same survey has been conducted for 3 years in a row and a summary report on students’ characteristics was produced. The first part of the survey was asking demographics questions on the students. The data in Table 1 show eight variables, each describing a different characteristic of the students taking the survey. For the data in the table, the description of the data is as follows: ID : An identifier for each of the individuals in the study. Gender : M for male and F for female Mathematics : To measure how much the student likes Mathematics courses (Really Don’t Like it, Not too much, I like it, Absolutely love it) Exercise : Number of times spent exercising per week Games : Number of hours spent playing online games per week GPA…
An automotive company used two different drivers to test the fuel economy of its latest crossover model. Each driver tested the same 20 vehicles from the factory. When the supervisor reviewed the data, she thought it looked like Driver A had different fuel economies than Driver B on average for the different vehicles and decided to test the data. To test the data, she first separated the data into pairs, with each car tested as a pair. The data is given below, with the fuel economy for each car given in miles per gallon. Assume that both populations are normally distributed. Use Excel to test if the true mean difference between Driver A and Driver B is significantly different from zero, where α=0.05, where each difference is calculated as Driver A−Driver B. Identify the t-test statistic, rounding to two decimal places, and the p-value, rounding to three decimal places. Pair DriverA DriverB 3 35 31 4 33 35 5…
A researcher conducted a 2-factor ANOVA on the data from his experiment and found a significant main effect of Factor A and a significant main effect of Factor B. Based on this information, what can he conclude about the interaction effect of Factor A & Factor B?
Microhabitat factors associate with forage and bed sites of barking deer in Hainan Island, China were examined. In this region, woods make up 4.8% of the land, cultivated grass plot makes up 14.7% and deciduous forests make up 39.6%, with the rest of the island classified as 'other'. Of the 426 sites where these deer forage, we found that 4 of these sites were woods, 16 were cultivated grassplot, 61 were deciduous forests, while the rest were classified as 'other'. Using R Studio: Conduct a hypothesis test to determine whether barking deer have a preference for foraging in certain habitats over others?
Red wine contains flavonol, an antioxidant thought to have beneficial health effects. But to have an effect, the antioxidant must be absorbed into the blood. The article "Red Wine is a Poor Source of Bioavailable Flavonols in Men't describes a study to investigate three sources of dietary flavonol-red wine, yellow onions, and black tea-to determine the effect of source on absorption. The article included the following statement. We recruited subjects via posters and local newspapers. To ensure that subjects could tolerate the alcohol in the wine, we only allowed men with a consumption of at least seven drinks per week to participate... Throughout the study, the subjects consumed a diet that was low in flavonols. (a) What are the three treatments in this experiment? (Select all that apply.) O red wine O alcohol tolerance O yellow onions O amount of flavonols in the diet black tea absorption of flavonols O gender (b) What is the response variable? O red wine O alcohol tolerance O yellow…
An agronomist is interested in comparing the efficacy of two fumigants (A and B) and a control (O) in eliminating wireworms. A field is divided into 4 sections, each section containing 3 plots. Fumigant A, B and O were randomly assigned to one plot within each section. The number of wireworms that remained on each plot after application of fumigant was recorded. Discuss the result of the post-hoc analysis.
A paper company has about 50 paper mills distributed over 3 provinces. Each mill records specified factors that contribute to its profitability. The company has classified the mills as Profitable and Non- Profitable. They recorded paper weight produced as an indicator of profitability. That is, X₁ = PAPER (weight in 10000 kilograms) Y = PROF (1 = profitable and 0 = not profitable) Y Profitable 1 1 0 It was found that Paper 2 1.5 0.8 ît= exp(-2.94 + 0.098X₁) 1 + exp(-2.94 +0.098X₁) 1. Give the fitted logistic response function. 2. Give the fitted logit response function 3. Show that ft loge € (₁^²) = = -2.94 + 0.098X₁ 4. Give the odds to be used of this logistic regression for X₁ = 0.7. Explain your result. 5. What is the estimated probability that a mill be profitable if it produces 7 000 kilograms of paper? 7. Interpret the regression coefficients of ît= Also find the odds ratio for b₁. exp(-2.94 + 0.098X₁) 1 + exp(-2.94 +0.098X₁)
Mr. Saif has conducted a research study to krow the attitude of graduate students towards entrepreneurship business. In this regard, he has collected the data from the Sultan Oaboos University, Muscat and University of Technology and Applied Sciences, Muscat usinga structured questionnaire. The feedback of 400 students has been collected from these universities. For the data analysIs, the researcher has used exploratory factor analysis and regression to evaluate the factors nfluienaing the attitude of students towards entrepreneurship business. Question: Evaluate the methodology approach used for this study by discussing its features.
You are interested in testing if there is a difference in weight-loss between 3 popular diet types; low calorie, low fat and low carb. Participants are randomly assigned one of the three groups or a control group. The control group will be told that are participating in a weight-loss study, but will not be following any particular diet. This is to study the placebo effect, weight-loss from just participating in the study.At the start of the study,each participant's weight is recorded in pounds. After 8 weeks they are weighed again, and the weight difference is recorded. A positive value represents a weight loss while a negative value represents a weight gain. Test at 5% significance. Low Calorie Low Fat Low Carb Control 5.3 2.2 3 0.1 4 3 3.1 3 4.3 1.8 2.5 -1.3 5.7 0.7 3.5 2.3 8.3 3.1 2.4 -0.6 Test Statistic: P-Value: