Research has shown that losing even one night's sleep can have a significant effect on performanceof complex tasks, such as problem solving (Linde & Bergstroem, 1992). To demonstrate thisphenomenon, a sample of n = 25 college students was given a problem-solving task at noon on oneday and again at noon on the following day. The students were not permitted any sleep between thetwo tests. For each student, the difference between the first and second score was recorded. Forthis sample, the students averaged Mp = 4.7 points better on the fırst test with a variance of s² = 64for the difference scores.a. Do the data indicate a significant change in problem-solving ability? Use a two-tailed test with a =.05.(1) Ho: (Select][ Select ][ Select ]H1:[ Select ][ Select ][ Select ](2) a = [Select]df = (Select)Critical region boundary/boundaries: ( Select ][ Select ](3) Estimated Standard Error =[ Select )( Select ][ Select ](4) | [ Select]b. Compute an estimated Cohen's d to measure the size of the effect.d = [Select]

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Answered: (1) Ho: [ Select ) [ Select ] [ Select…

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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A researcher was investigating variables that might be associated with the academic performance of high school students. He examined data from 1990 for each of the 53 cities randomly selected in the US. The dataincluded the average Math SAS score of all high school seniors in the city that took the exam (labeled as the variable SAT-M), the average number of dollars per pupil spent on education by the city (labeled as thevariable $Per Pupil), and the percentage of high school seniors in the city that took the exam (labeled as the variable %Taking). Find the 95% confidence interval for B1, the coefficient of the variable $Per Pupil and find the proportion of the variation in the variable SAT-M is explained by the explanatory variables $Per Pupil and %Taking?
Exercise 4. (a) x²(5.7) ~ Gamma(?,?), (b) x²(8) ~ Gamma(?,?), (c) - Gamma(4, 3) ~ x² (?)
9) Find L3.2 (5) using the nodes xo = 3,x1 = 4, x2 = 6 ,x3 = 8 %3D
A weight-loss program wants to test how well their program is working. The company selects a simple random sample of 51 individual that have been using their program for 15 months. For each individual person, the company records the individual's weight when they started the program 15 months ago as an x-value. The subject's current weight is recorded as a y-value. Therefore, a data point such as (205, 190) would be for a specific person and it would indicate that the individual started the program weighing 205 pounds and currently weighs 190 pounds. In other words, they lost 15 pounds. When the company performed a regression analysis, they found a correlation coefficient of r = 0.707. This clearly shows there is strong correlation, which got the company excited. However, when they showed their data to a statistics professor, the professor pointed out that correlation was not the right tool to show that their program was effective. Correlation will NOT show whether or not there is…
10. You estimated a regression with the following output. Source | SS df MS Number of obs = 333 -------------+---------------------------------- F(1, 331) = 4608.21 Model | 32636494.1 1 32636494.1 Prob > F = 0.0000 Residual | 2344225.8 331 7082.25316 R-squared = 0.9330 -------------+---------------------------------- Adj R-squared = 0.9328 Total | 34980719.9 332 105363.614 Root MSE = 84.156 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 30.79902 .4537022 67.88 0.000 29.90652 31.69153 _cons | 20.85313 42.1964 0.49 0.621 -62.1538 103.8601…
Consider the following population model for household consumption: cons = a + b1 * inc+ b2 * educ+ b3 * hhsize + u where cons is consumption, inc is income, educ is the education level of household head, hhsize is the size of a household. Suppose a researcher estimates the model and gets the predicted value, cons_hat, and then runs a regression of cons_hat on educ, inc, and hhsize. Which of the following choice is correct and please explain why. A) be certain that R^2 = 1 B) be certain that R^2 = 0 C) be certain that R^2 is less than 1 but greater than 0. D) not be certain
(d) Does a linear relation exist between the speed at which a ball is hit and the distance the ball travels? The variables speed at which the ball is hit and the distance the ball travels are positively associated because r is positive and the absolute value of the correlation coefficient is greater than the critical value ( ) (Round to three decimal places as needed.)
A problem that occurs with certain types of mining is that some byproducts tend to be mildlyradioactive, and these products sometimes get into our freshwater supply. The EPA has issuedregulations concerning a limit on the amount of radioactivity in supplies of drinking water.Particularly, the maximum level for naturally occurring radiation is 5 picocuries per liter ofwater (on average). A random sample of 24 water specimens from a city’s water supply gave ̄x= 4.61 and s = 0.87. Do these data provide sufficient evidence to indicate that the meanlevel of radiation is safe (below the maximum level set by the EPA)? Test usingα= 0.05.

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(1) Ho: [ Select ) [ Select ] [ Select ] H: [ Select] [ Select] [ Select ] (2) a = (Select] df = [ Select] Critical region boundary/boundaries: ( Select] [ Select ] (3) Estimated Standard Error = ( Select ] [ Select ] [ Select ]