Type III Sumdfof SquaresMeanSourceSig.SquareCorrectedModel114.000338.00010.133.004Intercept1200.00011200.000320.000 .00075.00075.00020.000 .002Present_length 27.000127.0007.200.028agepresent_length12.000112.0003.200.111Error30.0003.750Total1344.00012Corrected Total 144.00011a. R Squared = .792 (Adjusted R Squared = .714)%3DO 0.56O 0.41O 1.00O 0.84 A group of participants were given 10 minutes to memorize a list of 30 words. A two-way ANOVA with an alpha of .05 was usedto evaluate the impact of age (young adult, older adult) and presentation length (1 sec, 5 sec) on the number of words one canrecall. Calculate the Intraclass Correlation Coefficient for the SPSS output provided.R= (MSA - MS) + MSATests of Between-Subjects EffectsDependent Variable: recalledType III Sumdfof SquaresMeanFSquareSourceSig.Corrected114.000338.00010.133.004ModelIntercept1200.0001200.000320.000 000age75.00075.00020.000.002Present length 27.00027.0007.200028agepresent length12.000112.0003.200111Error30.000183.750Total1344.00012Corrected Total 144.00011

A two way ANOVA has two factors independent variables and dependent variable. Two way ANOVA mean…

Answered: A group of participants were given 10…

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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The Minitab output shown below was obtained by using paired data consisting of weights (in Ib) of 27 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 4500 lb to be used for predicting the highway fuel consumption amount. Use the information provided in the display to determine the value of the linear correlation coefficient. (Be careful to correctly identify the sign of the correlation coefficient.) Given that there are 27 pairs of data, is there sufficient evidence to support a claim of linear correlation between the weights of cars and their highway fuel consumption amounts? Click the icon to view the Minitab display. Minitab output The linear correlation coefficient is. (Round to three decimal places as needed.) The regression equation is Highway = 50.4- 0.00535 Weight %3D Predictor Сoef SE Coef T Constant 50.383 2.732 17.75 0.000 Weight - 0.0053502 0.0007856 -7.55 0.000 S= 2.17876 R-Sq = 65.1% R-…
what are the critical values r =?
The Minitab output shown below was obtained by using paired data consisting of weights (in lb) of 31 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 4000 lb to be used for predicting the highway fuel consumption amount. Use the information provided in the display to determine the value of the linear correlation coefficient. (Be careful to correctly identify the sign of the correlation coefficient.) Given that there are 31 pairs of data, is there sufficient evidence to support a claim of linear correlation between the weights of cars and their highway fuel consumption amounts? Click the icon to view the Minitab display. The linear correlation coefficient is (Round to three decimal places as needed.) Is there sufficient evidence to support a claim of linear correlation? Yes O No Minitab output The regression equation is Highway = 50.8 -0.00508 Weight Predictor Coef SE Coef T P Constant 50.772 2.793…
The Minitab output shown below was obtained by using paired data consisting of weights (in lb) of 26 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 3000 lb to be used for predicting the highway fuel consumption amount. Use the information provided in the display to determine the value of the linear correlation coefficient. (Be careful to correctly identify the sign of the correlation coefficient.) Given that there are 26 pairs of data, is there sufficient evidence to support a claim of linear correlation between the weights of cars and their highway fuel consumption amounts? Click the icon to view the Minitab display. The linear correlation coefficient is (Round to three decimal places as needed.) Minitab output The regression equation is Highway = 50.3 -0.00539 Weight Predictor Coef SE Coef Constant 50.288 2.998 Weight -0.0053868 0.0007773 |S=2.11773 R-Sq=64.0% R-Sq(adj) = 60.9% Predicted Values…
A researcher wanted to examine whether type of dog food (freeze dried meat vs generic brand kibble) would affect dogs’ attention span. The researcher hypothesized that dogs who ate freeze dried meat would have longer attention spans than those who ate generic brand kibble. The researcher used a single sample of 13 subjects, that took part in both treatment conditions. The researcher set the alpha level at .01. The mean of the difference scores (MD)was 7.0 and the SSD for the difference in attention spans was 144. What is the calculated test statistic to the nearest thousandth? Be sure to put the positive or negative sign in front of it. Note: SHOW ALL WORK!!! Based on your work above, do you reject or retain the null? reject retain Based on your conclusion regarding the null, was there a treatment effect? Yes No
all 12% 1:19 Y ☺ Lab Assignment #8_-150... ANOVA An experiment was conducted to determine if motivational techniques in management significantly impacted employee stress levels compared to no intervention. An employee survey was given to three groups: one group under a manager who started using a transformational motivation technique, one group under a manager who began using a transformational motivation technique, and then a control group with no new technique used. Stress levels were self-reported by the employees as shown below. Use alpha = 0.05 Transformational Transactional Control 2 6. 3 3 1. What is your null hypothesis? 2. What is your alternative hypothesis? After running the single factor analysis of variance on the data, what is the p-value for between 3. groups? Using the 95% significance level, is there a significance difference in stress levels between the three 4. groups? 5. Do you reject or accept the null hypothesis? Yes No Reject Accept II
Fifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support Correlation Results the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that Correlation coeff, r: 0.959614 a measured chest size can be used to predict the weight? Use a significance level of = 0.05. Critical r: +0.2680855 P-value (two tailed): 0.000 Но: Р H1:P (Type integers or decimals. Do not round.) Identify the correlation coefficient, r. (Round to three decimal places as needed.) Identify the critical value(s). (Round to three decimal places as needed.) O A. There is one critical value at r= . B. There are two critical values at r= ± Is there sufficient evidence to support the claim that there is a linear correlation between…
Using the linear correlation coefficient given above, calculate and give the value of the coefficient of determination. Explain in a sentence what this means in the context of this example, treating gpa as a predictor.
Fifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Use a significance level of x = 0.05 to answer the following questions. Correlation Results Correlation coeff, r: Critical r: P-value (two tailed): 0.000 Identify the correlation coefficient, r. r= (Round to three decimal places as needed.) Identify the critical value(s). (Round to three decimal places as needed.) OA. There are two critical values at r= ± OB. There is one critical value at r= Is there sufficient evidence to support the claim that there is a linear correlation between the weigh of bears and their chest sizes? Choose the correct below and, if necessary, fill in the answer box within your choice. (Round to three decimal places as needed.) exceeds the critical value. A. No, because the absolute value of r= OB. Yes, because the absolute value of r= OC. No, because r= exceeds the positive critical value. falls…
A team of epidemiologists at the Mayo Clinic wanted to find whether there is an association between obesity and cardiovascular disease (CVD). They conducted a prospective cohort study following obese and non-obese individuals who were free of CVD at the beginning of study for five years. The investigators were also interested in assessing age as a potential confounder, effect modifier, or both. Use the data below to answer the accompanying questions. CVD No CVD Total Obese 10 90 100 Not Obese 35 465 500 Total 45 555 600 CVD No CVD Total Obese 36 164 200 Not Obese 25 175 200 Total 61 339 400 1. Compute the appropriate measure of association for those who were less than age 50. 2. Compute the appropriate measure of association for those who were older or equal to age 50. 3. Compute the crude measure of association? 4. List three attributes that age must satisfy before it could…
Listed below are numbers of internet users per 100 people and numbers of scientific award winners per 10 million people for different countries. Construct a scatterplot, Fone the value of the linear correlation coefficient r, and find the p-value of r. Determine whether there is suffiencet evidence to support a claim of linear correlation between the two variables. Use a significance level of a=0.05 determine the linear correlation coefficient r determine the null and alternative hypothesis determine the test statistic Determine the p value

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