## How do you calculate BMI in C++?

How do you calculate BMI = mass (lb) x 703/ (height(in))squared in C++. I entered: cout << “weight(lbs)”; cin >> lbs; cout << “height”; cin >> height >> in; BMI = ((lbs) * 703)/pow(height(in)), 2);

**How do you calculate BMI using code?**

Design a BMI Calculator using JavaScript

- Formula: BMI = (weight) / (height * height)
- Approach: BMI is a number calculated from an individual’s weight and height.
- Example:
- Output:

**How do you calculate BMI pseudocode?**

PROGRAMMING[1] – Graded project one Pseudo code BMI=weightX703/height2 Begin Declare X=703 Declare BMI Input weight Input | Course Hero.

### How do you write a BMI report?

The formula is BMI = kg/m2 where kg is a person’s weight in kilograms and m2 is their height in metres squared. A BMI of 25.0 or more is overweight, while the healthy range is 18.5 to 24.9.

**How do I calculate my BMI and BMR?**

BMI and BMR Formulas How to calculate BMI is rather simple. BMR is measured in kJ and BMI is measured by dividing mass/height that is kg/m2 as a unit of measurement. BMR formula is based on the energy units spent so ideally if say, you have to lose 1kg of fat then you need to burn 3500 calories.

**How do you calculate BMI in Visual Basic?**

BMI can be calculated using the formula weight/( height )2, where weight is measured in kg and height in meter. If you only know your weight and height in lb and feet, then you need to convert them to the metric system.

## What is pseudo code and example?

Pseudocode is an artificial and informal language that helps programmers develop algorithms. Pseudocode is a “text-based” detail (algorithmic) design tool. The rules of Pseudocode are reasonably straightforward. All statements showing “dependency” are to be indented. These include while, do, for, if, switch.

**What is pseudocode data structure?**

In computer science, pseudocode is a plain language description of the steps in an algorithm or another system. It typically omits details that are essential for machine understanding of the algorithm, such as variable declarations and language-specific code.

**What is the BMI equation?**

Formula: weight (lb) / [height (in)]2 x 703 Then, calculate BMI by dividing weight in pounds (lb) by height in inches (in) squared and multiplying by a conversion factor of 703.

### Is BMI the same as BMR?

To summarise, BMI stands for Body Mass Index and is related to your height and weight. Whereas BMR, or RMR, represents the amount of calories your body requires to perform essential functions.

**What is the average BMR for a 42 year old woman?**

Typically about 60% of our total energy needs come from resting metabolism (see above), but this varies greatly depending on our activity level. The average BMR for an American woman is about 1,400 calories, while for a man its about 1,800.

**What are data visualization tools and how do they work?**

By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data. In the world of Big Data, data visualization tools and technologies are essential to analyze massive amounts of information and make data-driven decisions.

## What are some of the best data visualization examples from history?

Data is beautiful: 10 of the best data visualization examples from history to today. 1. Napoleon March Map. Visualization by: Charles Joseph Minard. Learn more: Wikipedia. In 1812, Napoleon marched to Moscow in order to conquer the 2. 1854 Broad Street Cholera Outbreak Map. 3. Causes of

**What makes a good visualization?**

A good visualization tells a story, removing the noise from data and highlighting the useful information. However, it’s not simply as easy as just dressing up a graph to make it look better or slapping on the “info” part of an infographic.

**How to use logistic regression to model the probability of diabetes?**

To put it simple, logistic regression can be used to model the probability of diabetes. The key concept of logistic regression is the logit, the natural logarithm of odds ratio. In the above equation, Pᵢ is the probability of diabetes for patient i. β is the coefficients of LR model, while x is the features of data sample i.