Different varieties of fruits and vegetables have different amounts of nutrients. These differences are important when these products are used to make babyfood. We wish to compare the mean carbohydrate content of two varieties of peaches. The data were analyzed with statistical software, and the followingoutput was obtained:NMeanVariety 1 5Variety 2 733.625.0StDev3.78110.392SE Mean1.6913.927Assuming the conditions for inference were met, which of the following is the most appropriate conclusion to draw at the a = 0.05 level?

The objective of the question is to determine if there is a significant difference in the mean…

Answered: Different varieties of fruits and…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Patients suffering from rheumatic diseases or osteoporosis often suffer critical losses in bone mineral density (BMD). Alendronate is one medication prescribed to build or prevent further loss of BMD. Holcomb and Rothenberg (A-3) looked at 96 women taking alendronate to determine if a difference existed in the mean percent change in BMD among five different primary diagnosis classifications. Group 1 patients were diagnosed with rheumatoid arthritis (RA). Group 2 patients were a mixed collection of patients with diseases including lupus, Wegener’s granulomatosis and polyarteritis, and other vasculitic diseases (LUPUS). Group 3 patients had polymyalgia rheumatica or temporal arthritis (PMRTA). Group 4 patients had osteoarthritis (OA) and group 5 patients had osteoporosis (O) with no other rheumatic diseases identified in the medical record. Changes in BMD are shown in the following table. (TABLE IS IN THE IMAGES) a. Formulate research question b. State the null hypothesis in narrative…
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The administrator of a school board in a large county was analyzing the average mathematics test scores in the schools under her control. She noticed that there were dramatic differences in scores among the schools. In an attempt to improve the scores of all the schools, she isolated factors that could account for the differences and were easily obtained from HR. Accordingly, she took a random sample of 40 schools across the county and for each determined: Test Score, Y: the mean test score last year at the school sampled Math Dgr, X1: the percentage of teachers in each school who have at least one university degree in math Age, X2: the mean age of the math teachers at the school sampled Income, X3: the mean annual income of the math teachers at the school sampled Conduct a simple linear regression analysis for each of the variables predicting mean test score and fill in the table below. Variable Equation…
4. Answer question 3
Let’s say you have a study looking at the DV “Time to help”. Your IV is whether potential helpers did not see (condition #1) or saw (condition #2) someone else helping. The mean time to help for those in condition #1 was 58 seconds (variance was 2.81). The mean time to help for those in condition #2 was 55 seconds (variance was 3.06). First, tell me what Cohen’s d (pooled) is. Second, tell me if the effect size is meaningful in terms or magnitude!
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This exercise contains only parts a and b. a) For the given data, the x=___ hours (round your response to three decimal places). For the given data, mean range =____hours (round your response to two decimal places). With z=3, the control limits for the mean chart are: UCLx = ____ hours (round your response to three decimal places). LCLx = _____ hours (round your response to three decimal places).
The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technologgy was also given a foot length of 10.8 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 10.8 cm, what is the single value that is the best predicted height for that person? H Click the icon to view the technology output. The single value that is the best predicted height is cm. Technology Output (Round to the nearest whole number as needed.) The regression equation is Height - 67.5 +5.15 Foot Length Predictor Coef SE Coef Constant 67.52 11.07 6.10 0.000 Foot Length 5.1508 0.4817 10.69 0.000 S-5.50271 R-Sq = 73.18 R-Sq (adj) = 72.44 Predicted Values for New Observations New Obs Fit SE Fit 95 CI 954 PI 123.149 1.605 (119.732, 126.566) (111.996, 134.302) Values of Predictors for New…
1. For the two following exercises, identify: the population, the parameter and the variable, a) A fitness center is interested in the mean amount of time a client exercises in the center each week. b) A cardiologist is interested in the mean recovery period of her patients who have had heart attack
The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technology was also given a foot length of 17.8 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 17.8 cm, what is the single value that is the best predicted height for that person? Click the icon to view the technology output. The single value that is the best predicted height is (Round to the nearest whole number as needed.) cm. Technology Output The regression equation is Height = 53.3+4.25 Foot Length Predictor Constant Coef SE Coef 53.28 11.44 Foot Length 4.2537 0.4699 S = 5.50739 R-Sq=72.3% R-Sq (adj) = 71.6% T 4.66 9.05 Predicted Values for New Observations New Obs 1 Fit SE Fit 128.996 1.733 (124.309, 133.683) 95% CI Foot New Obs Length 1 17.8 0.000 0.000 Values of Predictors for New…
You are asked to calculate the 94% Cl for the mean value of a normally distributed population with known variance = 144. Which of the following critical values should be used?

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