Here is an experiment:

As a college student and active individual in this experiment, I love activities and want to lose weight. I decided to test the effectiveness of three exercise routines $($gym workouts, cycling, and playing badminton$)$ for weight loss in a week.

Setup:

Variable of Interest: Weight loss of a college student.

Independent Variables:

Exercise methods: Gym workouts, Cycling, Playing Badminton

Duration of Exercise: $1$ week

Data Collection:

Measure the initial weight before starting the experiment.

Collect daily measurements.

Type of exercise, duration, and intensity.

Regular diet or changes in diets $($if possible$)$

Data Analysis:

Calculate the mean weight loss for each exercise routine group by averaging the daily weight loss measurements.

Variance Calculation: using the provided algorithm. Subtract each weight loss measurement from the mean, square the differences, sum them up$,$ and divide by the total number of measurements.

Outcome Analysis:

Analyze the mean and variance of weight loss for each exercise routine group. Consequently, I can determine the effectiveness of each exercise routine in weight loss in one week.

In this part of the project, you need to create the flowchart of the algorithms. You should use the results of the computational thinking pillar of decomposition to design your flowchart. Your flowchart should have two major parts:

$1.$ Calculating the mean of the measurements in each of the experimental condition

$2.$ Calculating the variance of the measurements

For the first part, the algorithm can be described like this:

$$ Create a variable to hold the sum of all measurements in each of the experimental conditions.

$$ Divide the sum by the total number of measurements in the condition to get the mean value.

In the second part, the algorithm the algorithm can be described like this:

$$ Calculate the mean value.

$$ Calculate the deviations from the mean by subtracting the mean from each data point.

$$ Square each deviation obtained in the previous step.

$$ Calculate the sum of squared deviation by adding up all the squared deviations.

$$ Calculate the variance by dividing the sum of squared deviations by the total number of data points.