A doctor collects data on all the men in his practice. Their daily potassium intakeis 4500 mg/day, with a standard deviation of 1000 mg/day. They have an averagesystolic blood pressure of 150 mmHg, with a standard deviation of 10 mmHg. Thetwo variables have correlation r =3.-0.4.(a) One of the men is at the 25 percentile of potassium intake and 75 percentile ofblood pressure. Relative to all other men at the 25th percentile potassium intake,this man's blood pressure is (circle one)smaller than averageabout averagelarger than averageJustify your answer using a written explanation and/or a diagram. (b) A man is selected at random from the practice. His potassium intake is 5500mg/day, which means that he isSD(s) above the averagepotassium intake of men in the practice. Another way of expressing his relativepotassium intake is that he is at thepercentile of intake amongall men in the practice.(c) Using regression, we can predict the man from part (b) will have a bloodpressure that isSD(s)(choose betweenabove/below) average. Therefore, he is predicted to be at thepercentile of blood pressure.

Answer: (a) One of the men is at the 25 percentile of potassium intake and 75 percentile of blood…

Answered: (b) A man is selected at random from…

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 patient is classified as having gestational diabetes if their average glucose level is above 140 milligrams per deciliter (mg/dl) one hour after a sugary drink is ingested. Rebecca's doctor is concerned that she may suffer from gestational diabetes. There is variation both in the actual glucose level and in the blood test that measures the level. Rebecca's measured glucose level one hour after ingesting the sugary drink varies according to the Normal distribution with μ=140+5 mg/dl and σ=5+1 mg/dl. Using the Central Limit Theorem, determine the probability of Rebecca being diagnosed with gestational diabetes if her glucose level is measured: Once? n=5+2 times n=5+4 times Comment on the relationship between the probabilities observed in (a), (b), and (c). Explain, using concepts from lecture why this occurs and what it means in context.
Low-Density Lipoprotein (or LDL) is considered the "bad" cholesterol because it forms plaques in arteries, raising the risk for heart attack and stroke. Suppose you are interested in predicting LDL (in mg/dL) using one's age (in years). Assume that LDL levels and age are normally distributed and that the correlation between the two variables is 0.534. Based solely on the regression effect, a person whose age is at the 60th percentile is predicted to have an LDL level ____. [Source: Ldl cholesterol: Definition, risks, and how to lower it. (2020, March 09). Retrieved from https://www.webmd.com/heart-disease/ldl-cholesterol-the-bad-cholesterol] Question 4 options: A) above the 60th percentile B) exactly at the 60th percentile C) exactly at the 40th percentile D) I need more information to answer this E) below the 60th percentile
The adjusted R-squared accounts for the amount of variance explained while also adjusting for the number of independent variables in the linear regression equation. True or False
The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1^x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age Bone Density35 35043 34053 33954 32155 310 Step 3 of 6 : Determine if the statement "Not all points predicted by the linear model fall on the same line" is true or false.
A set of n=15 pairs of x and y scores has sx=10, ssy=40, and sp=30. What is the slope for the regression for predicting y from x?
Hello! Please analyse the table 3 and 4 in the image attached. the data is supposed to see if there is a relationship between the prevalence of obesity(table3) or life expectancy (table4) between males and females. thank you!
The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1^x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age Bone Density35 35043 34053 33954 32155 310 Step 4 of 6 : Determine the value of the dependent variable yˆ at x=0.
2. I surveyed 150 adults in the U.S. and asked them how many hours of TV the watched on average per week. I then ran a regression of # of hours of TV on whether or not they were a college graduate (=1 if yes, =0 if no), their age in years, the number of children in their household, and whether or not they live a cold climate (=1 if latitude is greater than 41.2, =0 otherwise). The results fro the regression are shown in the table below. Estimate p-value College Graduate -0.8 0.003 Age 0.1 0.150 Number of Children 0.10 0.521 Cold Climate 1.8 0.047 Intercept -1.23 0.041 (a) What is the dependent variable in this regression? (b) What are the independent variable(s) in this regression? (c) What is the unit of analysis? (d) What is the sample size? (e) What is one binary variable used in this analysis? (f) What is one ratio variable used in this analysis? (g) What is the predicted number of TV hours watched by a 50 year old, colleg graduate, with no children at home who lives in Arizona…
Explain the process of Computing the Regression Line?
In a fisheries researchers experiment the correlation between the number of eggs in tge nest and the number of viable (surviving ) eggs for a sample of nests is r=0.67 the equation of the regression line for number of viable eggs y versus number of eggs in the nest x is y =0.72x + 17.07 for a nest with 140 eggs what is the predicted number of viable eggs ?
Several surveys in the United States and Europe have asked people to rate their happiness on a scale of 3 = "very happy," 2 = "fairly happy," and 1 = "not too happy," and then tried to correlate the answer with the person's income. For those in one income group (making $25,000 to $55,000) it was found that their "happiness" was approximately given by y = 0.065x - 0.613, where x is in thousands of dollars. Find the reported "happiness" of a person with the following incomes (rounding your answers to one decimal place). (a) $30,000 (b) $50,000 (c) $55,000
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