The etiology of high blood pressure remains a subject of active investigation. One widely accepted hypothesis is that excessive sodium intake adversley affects blood pressure outcomes. To explore this...

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The etiology of high blood pressure remains a subject of active investigation. One widely accepted hypothesis is that excessive sodium intake adversley affects blood pressure outcomes. To explore this hypothesis, an experiment was set up to measure the responsiveness to the taste of salt and to relate the responsiveness to blood pressure level. The protocol used involved giving 3 day old infants in a newborn nursery a drop of various solutions, this eliciting the sucking response and noting the vigor with which they sucked- denoted by MSB (mean number of sucks per burst of sucking). The content of the solution was changed over 10 consecutive periods: (1) water, (2) water, (3) 0.1 molar and salt water, (4) 0.1 molar salt and water, (5) water, (6) water, (7) 0.3 molar salt and water, (8) 0.3 molar salt and water (9) water, (10) water. In addition, as a control, the response of the baby to the taste of sugar was also measured after the salt-taste protocol was completed. In this experiment, the sucking response was measured over five different periods with the following stimuli: (1) nonnutritive sucking, that is, a pure sucking response was elicited without using any external substance, (2) water, (3) 5% sucrose + water, (4) 15% sucrose + water, (5) nonnutritive sucking.


The data for the first 100 infants in the study are in an excel attachment. (I will attach the document)


Construct a variable measuring the response to salt. For example, one possibility is to compute the averageMSB for trials 3 and 4 - average MSB for trials 1 and 2 = average MSB when the solution was 0.1 molar salt and water - average MSB when the solution was water. A similar index could be computed comparing trials 7 and 8 with trials 5 and 6.


Problem 1) Obtain descriptive statistics and graphic displays for these salt-taste indices. Do the indices appear to be normally distributed? Why or Why not? Compute the sample mean for this index, and obtain 95% CIs about the point estimate.


Problem 2) Construct indices measuring responsiveness to sugar taste and provide descriptive statistics and graphical displays for these indices. Do the indices appear to be normally distributed? Why or Why not? Compute the sample mean for this index, and obtain 95% CIs about the point estimate.


Problem 3) We want to relate the indices to blood pressure level. Provide a scatter plot relating mean SBP and mean DBP, respectively, to each of the salt-taste and sugar-taste indices. Does there appear to be a relation between the indices and blood pressure level?


Summarize in a 2 -3 page summary. Include intorduction, methods, results and discussion.

Answered Same DayDec 31, 2021

Answer To: The etiology of high blood pressure remains a subject of active investigation. One widely accepted...

Robert answered on Dec 31 2021
123 Votes
1) We have defined four salt indices as below:
SI1 = average MSB for trials 3 and 4 - average MSB for trials 1 and 2
SI2 = average MSB for trial
s 5 and 6 - average MSB for trials 3 and 4
SI3 = average MSB for trials 7 and 8 - average MSB for trials 5 and 8
SI4 = average MSB for trials 9 and 10 - average MSB for trials 7 and 8
The following table gives the descriptive statistics for the salt-indices:
Descriptive Statistics

Minimum Maximum Mean
Std.
Deviation Skewness Kurtosis
SI1 -53.33 8.84 -18.3132 8.77492 -.121 2.574
SI2 -15.42 17.50 .6591 5.87401 -.023 .800
SI3 -21.75 17.17 -2.7970 6.80404 -.138 .909
SI4 -14.50 23.34 2.1950 6.31550 .572 1.873
The following figure shows the histogram for SI1:


The following figure shows the histogram for SI2:
The following figure shows the histogram for SI3:
The following figure shows the histogram for SI4:


From the above histograms we can see that the histograms of each of the 4 indices are fairly
approximated by the corresponding Normal curves. Thus we can conclude that the indices appear to be
normally distributed.
Now, from the Descriptive Statistics Table we can see that the sample means for these indices are:
Sample mean of SI1 = -18.3132
Sample mean of SI2 = 0.6591
Sample mean of SI3 = -2.7970
Sample mean of SI4 = 2.1950
Now, 95% CI is given by: (x-bar – t0.025;n-1*s/√n, x-bar + t0.025;n-1*s/√n) where x-bar = sample mean, n =
sample size, s = sample SD and...
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