Key Concepts in Health, Nutrition, and Statistics

Food and Nutrition

Food is the act of providing sustenance to the human body, while nutrition encompasses the physiological processes by which the body receives, transforms, and utilizes the chemical components in food.

Inherited Diseases

• Hemophilia
• Huntington's disease
• Cystic fibrosis
• Color blindness
• Phenylketonuria

Measures of Dispersion

Measures of dispersion indicate how close the data are to the average.

Vaccines

Vaccines are preparations containing killed or attenuated microorganisms. They are introduced into our bodies to produce antibodies that kill the organism, providing immunity.

Common Pathogens

Pathogens such as bacteria and fungi are the most common causes of infectious diseases.

Health and Disease

Health is a state of complete physical, mental, and social well-being. Disease is an altered state of health in a living being.

Most Important Measure of Dispersion

The most useful and important measure of dispersion is the standard deviation.

Mean

The sum of all data divided by the total number of data is called the mean.

Measurement for Quantitative Variables

The mean is a measurement used only for quantitative variables.

Mode

The value of the variable that occurs most often is called the mode.

Measures of Central Tendency

The measures of central tendency are the mean, median, and mode.

Range

The difference between the highest and lowest values of a statistical variable is called the range.

Mean Deviation

The arithmetic mean of the deviations of each data point from the central value is called the mean deviation.

Variance

The average of squared deviations from the mean is called the variance.

Absolute Cumulative Frequency

The amount of data that takes a value less than or equal to a given value is called the absolute cumulative frequency.

Qualitative Variables

When data from statistical variables are qualities or modalities, they are called qualitative variables.

Dispersion and Data Spread

Measures of dispersion give us an idea of how far away the mean values are and allow us to determine which of two distributions is less scattered.

Coefficient of Variation

The coefficient of variation relates the mean and standard deviation and allows us to compare distributions with different means.

Sample Size

The number of elements in a sample of the population or part of it taken to do a study is called the sample size.

Modal Interval

When data are grouped into intervals, the interval with the highest absolute frequency is called the modal interval.

Discrete Variables

Variables that take values in a finite set of numbers are called discrete variables.

Representative Sample

For a sample to be representative, randomness and uniformity should be taken into account.

Types of Samples

According to the property under consideration, the types of samples chosen are random, systematic, and stratified.

Types of Quantitative Variables

Among quantitative variables, the types that can be distinguished are discrete and continuous.

Continuous Variables

Variables that can take any value within a range are called continuous variables.

Histograms

The statistical graph used to represent frequencies of variables for which data are collected at intervals is the histogram.

Bar Chart

The statistical graph used to represent frequencies of qualitative and quantitative variables in a coordinate axis system is the bar chart.

Frequency Polygons

The statistical diagram obtained by joining the midpoints of the upper segments of the rectangles of the histogram is called the frequency polygon.

Pie Chart

The statistical chart that represents frequencies of any type of variable is the pie chart.

Randomness

Randomness means that the elements of the sample must be chosen so that any element of the population has an equal chance of being selected.

Homogeneity

Homogeneity means that the elements of the population should have similar conditions.

Sample Size and Error

The size of a sample should be adjusted according to the acceptable risk of error.

Centralization Measures

Measures of centralization indicate the values around which sample data or population data are distributed.

Population

The population is the set of all elements that are studied.

Sample

The sample is the part of the population that we study, and the conclusions drawn from the study will apply to the total population.

Variance

The variance is the mean of the squared deviations from the mean.