Faculty of Dentistry

Assignment topic: Descriptive Statistics

Course Title: Statistics

Course Code: SGS116

Submitted to: Dr. Ahmed Refaat

Prepared by: Moustafa Elsayed – 180065

Descriptive statistics are numbers that used to describe or summarize data in ways that are meaningful and useful or brief descriptive coefficients that summarize a given data set, which can be either a representation of the entire population or a sample of it.

There are four noteworthy kinds of descriptive statistics:

1. Measures of frequency:

In statistics, the frequency is the number of times that an event repeats itself. the importance of frequency analysis can be summarized in dealing with the quantity of events (frequency) and dissects measures of central tendency, dispersion, percentiles, etc.

2. Measures of central tendency:

It is a solitary measure that tries to depict the arrangement of information through an esteem that speaks to the focal position incorporate that information index. Most well-known measures of central tendency used for frequency analysis are mean, median and mode. While the mean is the normal estimation of the information collection, the median is the center value (a perception which has an equivalent number of lying above and underneath it) in the information collection. Mode is the esteem that happens extremely number circumstances in an information index

3. Measures of dispersion or Variation:

These mirror the spread or fluctuation of information inside an informational collection. Most prominent measures scattering utilized for recurrence investigation are variance, range, and deviation. Of while standard deviation had been around for quite a while and had been utilized by others with various names (I mean blunder by Gauss); Karl Pearson first utilized the expression standard deviation in 1894. The change was first utilized by Ronald Fisher in 1919.

4. Measures of percentile values:

A percentile value demonstrates what percent of qualities in an information index fall underneath a specific percent frequency analysis regularly utilizes percentile values like quartiles, percentiles and so on. While the tenth percentile value demonstrates the 10% of the perceptions fall beneath it in an informational collection, it is likewise called the first decile (where the informational collection is isolated into 10 deciles at interims of 0% each). Likewise, the 25th,50th, and 75th percent additionally called the first, second and third quartile separately (where the informational collection is partitioned into 4 quartiles at intervals of 25% each).

There are four types of variables:

1.Quantitative variable:

The quantitative variable is measured numerically. With estimations of quantitative components, you can incorporate and subtract, get a significant case and increase and separate, “Age” is a quantitative variable.

2.Qualitative/Categorical variables:

These take into consideration order in view of some trademark. With an estimation of qualitative/categorical factors, you cannot do things like increase, subtract and parcel and get a significant outcome. In the past illustration, “sexual orientation” as an include as either male or female qualitative/categorical variable gender was classified.

3.Discrete variable:

The descriptive variable is a quantitative variable with a limited (predetermined) number of characteristics. For instance, envision you moved six-sided bite the dust four times and measured how many times you rolled an even number. What are your conceivable results? (0,1,2,3,4)

4.Continuous variable:

The continuous variable is a quantitative variable with a vast number of qualities. Take temperature, for instance, temperature take esteems, for example, 90 degrees, 90.02 degrees or 90.05557253 degrees. In the past illustration, we were restricted to a limited number of qualities (you couldn’t roll 1.5 even numbers) which is the thing that made it discrete.

Importance of descriptive statistics:

Descriptive statistics are imperative in light of the fact that on the off chance that we basically displayed our crude information it is hard to envision what the data was which showing up, particularly if there was a considerable measure of it. Descriptive statistics, therefore, empowers us to display the information in a more significant manner which permits an easier understanding of the information.