BPS used ANOVA to analyze the results of a study to see which of two colors best attracts cerealleaf beetles. Assume that the two colors are equal in attracting cereal leaf beetles. Prove thatyellow traps more insects than white. Use different nonparametric statistics to prove Here andin EX26 - 28.MTW are the data:ColorsInsects TrappedYellow 45 5948463847White 211214171317

Given information: Yellow White 45 21 59 12 48 14 46 17 38 13 47 17

Answered: BPS used ANOVA to analyze the results…

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 manager of a company that assembles and exports a particular type of pumps wants to know if there is a link between the number of hours spent by assembly workers in training and their productivity on the job. A random sample of 7 assembly workers was selected and their performances evaluated. The summary of the obtained data is listed in Table 2. Table 2: Shows the time spend by workers during training and their productivity on jobTraining hours (x) 20 36 20 38 40 33 32Output (y) 40 70 44 56 60 48 62 (i) Construct a scatter plot of the sample data and comment on the relationship between hours of training and output. (ii) Estimate a simple regression line, using the method of least squares, to identify a linear relationship between the hours of training received by assembly workers and their output (i.e. number of units assembled per day). (iii) Interpret, in context, the gradient/slope of the regression line. (iv) Estimated the output at 20 hours training time. (v) Interpret the…
The maximum weights (in kilograms) for which one repetition of a half squat can be performed and the times (in seconds) to run a 10-meter sprint for 12 international soccer players are shown in the attached data table with a sample correlation coefficient r of - 0.958. A 13th data point was added to the end of the data set for an international soccer player who can perform the half squat with a maximum of 210 kilograms and can sprint 10 meters in 1.99 seconds. Describe how this affects the correlation coefficient r. Use technology. Click the icon to view the data set. Data Table The new correlation coefficient r going from - 0.958 to (Round to three decimal places as needed.) Maximum weight, x Time, y 175 1.81 185 1.79 155 2.06 210 1.42 155 2.07 195 1.62 190 1.69 165 1.88 195 1.59 180 1.64 165 1.97 175 1.91 210 1.99
8) The following results are from data that were collected from the various high schools around the county. The dependent variable is % OF STUDENTS GOING TO COLLEGE, and the independent variables are: AVERAGE CLASS SIZE, COMBINED SAT SCORES, SPENDING PER STUDENT, AVERAGE TEACHER SALARY, AND % TAKING THE SAT Since the 3 variables AVERAGE CLASS SIZE, SPENDING PER STUDENT, AND AVERAGE TEACHER SALARY are each not significant at the 10% level of significance individually, in order to test to see if as a group they are significant the 3 variables are excluded and another regression is run. The results are as follows: a) At the 10% level of significance, test whether as a group AVERAGE CLASS SIZE, SPENDING PER STUDENT, AND AVERAGE TEACHER SALARY are significant. Be sure to state the null and alternative hypotheses for this hypothesis test.
(b) A rescarcher supccts that the fish in a particular elevated wetland have elevated mercury level. To confirm that, five striped bass in that wetland were caught and their tissues were tested for mercury. Then four striped bass in an unpolluted wetland were also caught and tested for the purpose of comparison. Table QI shows the fish mercury levels in mg/kg. Table QI shows the fish mercury levels in mg/kg. Sample from polluted wetland Sample from unpolluted wetland 0.580 0.382 0.711 0.276 0.571 0.570 0.666 0.366 0.598 Construct the 95% confidence interval for the difference in the population means. Then, test at the 5% level of significance, whether the researcher's suspicion is valid. Assume that the population variances are equal.
Is there an association between daily screen time and exercise habits in high school students? Mia selects a random sample of 123 high school students and categorizes them into 1 of 3 categories of screen time and whether they exercise. She would like to determine if there is convincing evidence of an association. Let = 0.05. What are the hypotheses for this test? H0: There is an association between daily screen time and exercise habits in high school students.Ha: There is no association between daily screen time and exercise habits in high school students.H0: There is no association between daily screen time and exercise habits in high school students.Ha: There is an association between daily screen time and exercise habits in high school students.H0: There is no difference in the distribution of daily screen time and exercise habits in high school students.Ha: There is a difference in the distribution of daily screen time and exercise habits in high school students.H0: There is a…
Researchers collected data on the numbers of hospital admissions resulting from motor vehicle crashes, and results are given below for Fridays on the 6th of a month and Fridays on the following 13th of the same month. Use a 0.05 significance level to test the claim that when the 13th day of a month falls on a Friday, the numbers of hospital admissions from motor vehicle crashes are not affected. Friday the 6th: Friday the 13th: 10 10 13 11 13 69 11
5. Ten competitors in a beauty contest are ranked by three judges in the following order. Judge I: 1 6 5 10 3 2 4 9 7 8 CS Scanned with CamScanner
Based on these tables, would you accept or reject the hypothesis that individuals in bad neighborhoods commit more crime?
Since the chi-square does not indicate the strength of the association, a researcher must then conduct a separate test for the measure of association. True False
For the following data (bad, good, very good, very good, very good, * excellent), the mode is very good O bad good O excellent no mode O
please helppp

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