$(56$ points$)$ You are managing a weight loss intervention at a rural health clinic, where you are targeting overweight or obese individuals to participate in WeightWatchers and attend monthly group sessions for six months, where weigh$-$ins will happen. WeightWatchers provides a daily point allotment for a participant to meet their weight loss goals. Participants log their food on an app, and all food items are converted to a number of points. At the end of six months, you have an Excel file that includes the following columns and patient data you recorded throughout the six months. All $132$ participating patients have an ID$,$ height, and baseline weight recorded, but if they missed any of the subsequent sessions $(2-6),$ then they have no data recorded for that month.

Column

Column Name

$($Variable Name$)$

Format

Notes

A

PatientID

Numeric

Always $10$ digits

B

Height

Numeric

Measured in meters

C

Weight$1$

Numeric

Weight in kilograms at session $1($baseline$)$

D

Weight$2$

Numeric

Weight in kilograms at session $2$

E

Weight$3$

Numeric

Weight in kilograms at session $3$

F

Weight$4$

Numeric

Weight in kilograms at session $4$

G

Weight$5$

Numeric

Weight in kilograms at session $5$

H

Weight$6$

Numeric

Weight in kilograms at session $6$

a$.(6$ points$)$ Body mass index is calculated as height in meters divided by weight in kilograms squared $($BMI $=$ m $/$ kg$2).$ A body mass index of $30$ or more is considered obese. List the steps you would do in Excel to calculate the prevalence of obesity at baseline. Be specific.

b$.(6$ points$)$ One of the short$-$term outcomes of your weight loss program is $$average weight loss of $1\mathrm{.}36$ kg per month across all participants$.$ Describe how you would approach figuring out if your participants met this outcome between baseline and session $2.$

c$.(6$ points$)$ You want to set up a tool to monitor the average weight loss per month across all participants, so you can ensure you are meeting the short$-$term outcome described in $($b$).$ Describe the tool you would design$/$utilize and what anomaly or outlier would flag you to dig deeper.

d$.(6$ points$)$ You are interested in using participants$$ data from all sessions to predict their weight at session $7.$ Describe what analysis method you would use to answer this question and why.

e$.(6$ points$)$ Your boss asks you, $$is there a significant difference in height between obese and non$-$obese participants?$.$ Describe what analysis method you would use to answer this question and why.

f$.(10$ points$)$ The long$-$term goal of this weight loss program is to reduce the obesity prevalence by $20\%$ among the participant population. Describe the steps you would use to answer the following question from hospital leadership: $$so$,$ did the program work in the long term?$$ using data from the electronic medical record $($i$.$e$.,$ not limited to the data you collected in the Excel file, but data that will be collected in the future$).$ Be specific.

g$.(10$ points$)$ Develop a draft report with at least two data visualizations $($that are appropriate for the data in the prompt and use data visualization principles covered in this course$)$ using fake data for the short$-$term outcome described in $($b$)$ and the long$-$term goal described in $($f$)$ that you could share with leadership.

h$.(6$ points$)$ Provide an explanation for the two data visualizations chosen for the draft report in $($f$).$ Why did you choose those visualizations for those data? What data visualization principles did you apply?