The following data represent the results from anindependent-measures experiment comparing threetreatment conditions. Use StatCrunch to conduct an analysisof variance with a = 0.05 to determine whether these dataare sufficient to conclude that there are significantdifferences between the treatments.Treatment A Treatment B6F-ratio=p-value =45LO558674Treatment C97111013

Answered: Image /qna-images/answer/e8808830-249c-4831-adcf-87543fb3511c.jpg

Answered: The following data represent the…

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 following data represent the results from an independent-measures study comparing two treatment conditions. Treatment Treatment One Two 5.5 4.4 6.7 4.2 6.1 5.3 6.7 5.8 6.5 Using SPSS, run the independent-measures single-factor ANOVA for this data: F-ratio: p-value: Now, run the independent-measures t test on the same data: t-statistic: p-value: What do you observe about the p-values? What is the relationship between the F-ratio and the t-statistic? > Next Question M
A math instructor claims that college women have more credit card debt than college men. She conducts a random sample of 38 college men and 32 college women, determines their average credit card debt, and obtains the following statistics in the picture: Test the claim that college women have more credit card debt than college men at the α = .05 level of significance. Assume unequal variances. a. Hypotheses: b. Test Statistic: c. Critical Value(s): d. Decision: e. Conclusion:
Compared to an independent-measures design, a repeated-measured study is more likely to find a significant effect because it reduces the contribution of variance due to ____. a. MD b. the effect of the treatment c. degrees of freedom d. individual differences
The following data summarize the results from an independent-measures study comparing three treatment conditions. Treatment I II III N = 12 3 5 6 G = 60 5 5 10 ∑X2 = 392 3 1 10 1 5 6 x̅1 = 3 x̅2 = 4 x̅3 = 8 T1 = 12 T2 = 16 T3 =32…
6) The following data summarize the results from an independent-measures study comparing three treatment conditions. Treatment II 3. 6. N= 12 10 G = 60 1 10 EX = 392 1 5. 6. M = 3 M = 4 M= 8 T= 12 T= 16 T= 32 SS = 8 SS = 12 SS = 16 a) Use an ANOVA with a = .05 to determine whether there are any significant differences among the three treatment means. b) Calculate n² to measure the effect size for this study. c) Write a sentence demonstrating how a research report would present the results of the hypothesis test and the measure of effect size. 3.
"A large candy manufacturer produces, packages and sells packs of candy targeted to weigh 52 grams. A quality control manager working for the company was concerned that the variation in the actual weights of the targeted 52-gram packs was larger than acceptable. That is, he was concerned that some packs weighed significantly less than 52-grams and some weighed significantly more than 52 grams. In an attempt to estimate the variance of the weights of all of the 52-gram packs the manufacturer makes, he took a random sample of n = 20 packs off of the factory line. The random sample yielded a sample variance of 3.5 grams. Use 90% confidence level. What is the confidence interval for the variance of the weight of the candy?"
The following data represent the results from an independent-measures experiment comparing three treatment conditions. Conduct an analysis of variance with α=0.05α=0.05 to determine whether these data are sufficient to conclude that there are significant differences in the means for the treatments. Treatment A Treatment B Treatment C 16 16 17 15 16 21 15 15 19 15 19 23 14 14 20 F-ratio (F-test statistic) = p-value = Conclusion: There is a significant correlation in the treatments I was able to show the treatments are independent The data does not provide evidence of a significant correlation for the treatments The data does not provide evidence of a significant difference in the means for the treatments I was unable to show the treatments are independent There is a significant difference in the means for the treatments The results obtained above were primarily due to the mean for the third treatment being noticeably different from the other two sample means.…
The following data represent the results from an independent-measures experiment comparing three treatment conditions. Conduct an analysis of variance with α=0.05 to determine whether these data are sufficient to conclude that there are significant differences between the treatments. Treatment A Treatment B Treatment C 8 10 16 10 9 12 9 10 14 9 8 15 9 13 13 F-ratio = p-value = Conclusion: There is a significant difference between treatments These data do not provide evidence of a difference between the treatments The results obtained above were primarily due to the mean for the third treatment being noticeably different from the other two sample means. For the following data, the scores are the same as above except that the difference between treatments was reduced by moving the third treatment closer to the other two samples. In particular, 3 points have been subtracted from each score in the third sample.Before you begin the calculation, predict how the…
The grams of carbohydrates for cereals made by three popular cereal manufacturers (Kellogg, General Mills, and Post) were collected and a one-way ANOVA was performed, as displayed in the table below. Analysis of Variance results: Where: mfr="General Mills" or mfr="Kellogg" or mfr="Post" Responses: carbo Factors: mfr Response statistics by factor mfr="General Mills" or mfr="Kellogg" or mfr="P Carbohydrates 20 mir General Mills 22 14.727273 no Means Std. Dev. Std. Error + 3.3478041 0.71375423 15 Kellogg Post 23 15.130435 4.4650598 0.93102933 9 13.222222 1.9220938 0.64069792 ANOVA table Source DF mi SS MS F-Stat P-value 2 23.786927 11.893464 0.86217854 0.4283 51 703.52789 13.794664 10 Total 153 727.31481 General Mills Kellogg Manufacturer Post Which manufacturer has the highest median grams of carbohydrates? Post O Cannot be determined. O General Mills Kellogg myhip
A data set includes weights of garbage discarded in one week from 62 different households. The paired weights of paper and glass were used to obtain the results shown to the right. Is there sufficient evidence to support the claim that there is a linear correlation between weights of discarded paper and glass? Use a significance level of α = 0.05. Click here to view a table of critical values for the correlation coefficient. Determine the null and alternative hypotheses. Ho: P H₁: p (Type # V 11 > cimals. Do not round.) ... Correlation matrix: Variables Paper Glass 10.1768 Paper Glass 0.1768 1
A data set includes weights of garbage discarded in one week from 62 different households. The paired weights of paper and glass were used to obtain the results shown to the right. Is there sufficient evidence to support the claim that there is a linear correlation between weights of discarded paper and glass? Use a significance level of α = 0.05. Click here to view a table of critical values for the correlation coefficient. Determine the null and alternative hypotheses. Ho: P H₁: P (Type integers or decimals. Do not round.) Identify the test statistic, r. r= (Round to three decimal places as needed.) Identify the critical value(s). (Round to three decimal places as needed.) A. There are two critical values at r = ± B. There is one critical value at r = State the conclusion. Because the absolute value of the test statistic is the positive critical value, there there is a linear correlation between the weights of discarded paper and glass for a significance level of α = 0.05.…
The following data represent the results from an independent-measures experiment comparing three treatment conditions. Conduct an analysis of variance with α=0.05α=0.05 to determine whether these data are sufficient to conclude that there are significant differences in the means for the treatments. Treatment A Treatment B Treatment C 6 4 13 4 6 11 4 9 7 6 6 10 5 5 9 F-ratio (F-test statistic) = p-value = Conclusion: The data does not provide evidence of a significant difference in the means for the treatments There is a significant difference in the means for the treatments I was unable to show the treatments are independent The data does not provide evidence of a significant correlation for the treatments I was able to show the treatments are independent There is a significant correlation in the treatments The results obtained above were primarily due to the mean for the third treatment being noticeably different from the other two sample means. For the…

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