Inside your array, add new columns and then populate them by modifying your INSERT INTO or

UPDATE SET statements. We are creating columns of analytics that can be used to build

interesting charts to answer the following medical concerns:

$1.$ You should now have a column of the actual

heartrate from a treadmill test, and a column

of what the maximum heartrate should have

been when exercising $(\mathrm{.}85*$ the # in the image

to the right, for each age group$).$

Now let$$s analyze the subjects of the study

categorizing the subjects based on their

treadmill test. Create a new column in your

array that holds text. USE CASE$()$ to write a

new metric that puts subjects into groups

based on their actual max heart rate on the

treadmill test as compared to the max their

age group. For example if the max heart rate

for a $30$ year old is $161,$ then you could put

people into groups based on their treadmill

test such as:

a$)$ reached or exceeded max heartrate $($these are the subjects that should walk more often$)$

b$)$ reached $90\%$ of max heart rate

c$)$ reached $70\%$ of max heart rate

d$)$ reached only $50\%$ of max heart rate on treadmill test $($these are the really healthy subjects,

walking on a treadmill did not spike their heart rate, because they are accustomed to the

activity$).$

$2.$ One of the medical directors read a study that reported that better than BMI, the simple

metric of weight in pounds divided by height in inches yields a very accurate predictor of

health. You are asked to create this Weight$/$Height metric. Do some analysis, comparing this

metric to the groupings on the treadmill test

a$)$ First create this new metric as a continuous variable, saving it to a new array column

$($numeric$).$

b$)$ To create categories based on the Weight$/$height metric add another new column to your

array $($text based$),$ then use a case statement to break this variable into categories of your own

$3$

design. You could then use these groups in a stacked column chart $($added to the legend$)$ or as

the rows or columns in

c$)$ To further analyze subjects add another new column to your array $($numeric$).$ Alter your

INSERT INTO statement to load this new column with the results of an NTILE$(4)$ statement $($that

pulls the columns from the database$)$ to create quartiles based on this metric. We need to

check if the quartiles based on this health predictor are more insightful than the groups that we

made with the CASE statement. Note: place the NTILE statement within the INSERT INTO

@Array SELECT statement.

d$)$ Analyze the data using these metrics and categories, and provide your analysis. Please do not

complete this assignment in one sitting, rather give some thought to your analysis and insights.

The difference between the grades B and an A is depth and insight. Try to make some

inferences based on the available data, such as people in group $1$ of the weight$/$height metric

did the best on the treadmill test, and subjects in group $4$ of the height$/$weight metric did the

worst on the treadmill test$).$

$3.$ The medical directors at the clinic are questioning the predictive validity of the treadmill

stress test to identify subjects that are at risk for heart conditions. The treadmill stress test

requires subjects get on a treadmill and walk until their heartrate peaks and they need to stop.

According to conventional wisdom when the subject$$s peak heart rate is more than $85\%$ of the

average maximum heart rate for their age group, then a blockage may be occurring in the

subject$$s heart.

a$)$ Create a column of your own design that categorizes the subjects into groups based on their

treadmill results. Perform some research into the dataset using these categories.

b$)$ finally use an NTILE$(4)$ statement to create quartiles based on this metric. Perform some

research into the dataset using these categories. Note: place the NTILE statement within the

INSERT INTO @Array SELECT statement.

e$)$ Analyze the data using these metrics and categories, and provide your analysis.

$4.$ One of the young doctors at the clinic discounted claims of an America$$s obesity epidemic

and claimed that the BMI scale is outdated and is not a valid predictor of heart health. Using

the metrics created $($and perhaps others of your own design$)$ analyze the treadmill data

$($Treadmill $\%$ of Maximum heart rate$),$ and whether there is a $$correlation$$ with BMI,

WeightHeight ratio, or other metric or grouping that you can envision.

$5.$ The same doctor that is questioning the BMI scale made the claim that many people now are

large yet still aerobically very healthy $($strong cardio$-$vascular systems$)$ as evidenced by low

treadmill results $($much lower peak heart rate than then $85\%$ cut$-$off$).$ Another doctor claimed

that they may believe this demographic change but not for subjects over $30$ or $35$ years old$\mathrm{.}3$

design. You could then use these groups in a stacked column chart $($added to the legend$)$ or as

the rows or columns in

c$)$ To further analyze subjects add another new column to your array $($nume