Heights (cm) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 135 to 190 cm and weights of 41 to 150 kg. Let the predictor variable x be the first variable given. The 100 paired measurements yield x = 167.74 cm, y = 81.32 kg, r= 0.388, P-value = 0.000, and y = - 105+ 1.18x. Find the best predicted value of y (weight) given an adult male who is 176 cm tall. Use a 0.05 significance level. The best predicted value of y for an adult male who is 176 cm tall is kg. (Round to two decimal places as needed.)

Heights (cm) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 135 to 190 cm and weights of 41 to 150 kg. Let the predictor variable x be the first variable given. The 100 paired measurements yield x = 167.74 cm, y = 81.32 kg, r= 0.388, P-value = 0.000, and y = - 105+ 1.18x. Find the best predicted value of y (weight) given an adult male who is 176 cm tall. Use a 0.05 significance level. The best predicted value of y for an adult male who is 176 cm tall is kg. (Round to two decimal places as needed.)

Calculus For The Life Sciences

2nd Edition

ISBN:9780321964038

Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.

Chapter2: Exponential, Logarithmic, And Trigonometric Functions

Section2.CR: Chapter 2 Review

Problem 111CR: Respiratory Rate Researchers have found that the 95 th percentile the value at which 95% of the data...

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Heights (cm) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 132 to 194 cm and weights of 38 to 150 kg. Let the predictor variable x be the first variable given. The 100 paired measurements yield x 167.75 cm, y=81.58 kg, r0.318, P.value = 0.001, and y-109 1.14x. Find the best predicted value of y (weight) given an adult male who is 184 cm tal, Use a 0.05 significance level. The best predicted value of y for an adult male who is 184 cm tall is kg. (Round to two decimal places as needed.)
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I would need some help with finding the best predicted value of y corresponding to the given value of x.
A photoconductor film is manufactured at a nominal thickness of 25 mils. The product engineer wishes to increase the mean speed of the film, and believes that this can be achieved by reducing the thickness of the film to 20 mils. Eight samples of each film thickness are manufactured in a pilot production process, and the film speed (in microjoules per square inch) is measured. For the 25-mil film, the sample data result is = 1.15 and 81 = 0.11, while for the 20-mil film, the data yield 2 = 1.06 and 82 = 0.09. Note that an increase in film speed vould lower the value of the observation in microjoules per square inch. (a) Do the data support the claim that reducing the film thickness increases the mean speed of the film? Use a = 0.10 and assume that the two population variances are equal and the underlying population of film speed is normally distributed. What is the P-value for this test? Round your answer to three decimal places (e.g. 98.765). The data the claim that reducing the film…
A photoconductor film is manufactured at a nominal thickness of 25 mils. The product engineer wishes to increase the mean speed of the film and believes that this can be achieved by reducing the thickness of the film to 20 mils. Eight samples of each film thickness are manufactured in a pilot production process, and the film speed (in microjoules per square inch) is measured. For the 25-mil film, the sample data result is.x₁ = 1.15 and S₁ = 0.11, while for the 20-mil film, the data yield 2 = 1.06 and s2 = 0.09. Note that an increase in film speed would lower the value of the observation in microjoules per square inch. Do the data support the claim that reducing the film thickness increases the mean speed of the film? Use a = 0.10 and assume that the two population variances are equal and the underlying population of film speed is normally distributed. The appropriate decision for the test is to reject the null hypothesis True False
The owner of a used car dealership is trying to determine if there is a relationship between the price of a used car and the number of miles it has been driven. The owner collects data for 25 cars of the same model with different mileage and determines each car's price using a used car website. The analysis is given in the computer output. Predicto Coef 24157.2 -0.181 SE Coef t-ratio Constant 2164.1 2.965 0.046 0.000 Mileage 0.024 5.377 S = 3860.7 R-Sq = 68.0% R-Sq (Adj) = 69.5% Using the computer output, what is the value of the coefficient of determination? 0.46 0.68 0.70 0.82