# Statistics for IT– Worldwideasy – 02

Through this Statistics lesson, you Identifying different types of data, Describing the data presented as a list, Describing the discrete data presented in a table, Describe continuous data presented by a group frequency.

##### RAW DATA

Data that does not collect raw data is collected
Statistically organized.

##### ARRAYS

An array is a set of raw number data
The order of ascent or descent of magnitude.

#### Range

The biggest and the difference between
The smallest number is called the range
Data.

#### Data

The first step is to summarize the quantitative data
To determine whether the data is discrete
Continuous.

### Discrete data – Frequency Table

A frequency table is arranging in order. The collected data are in chronological order. Their magnitude is a relative frequency.

### Grouped frequency table

• Class gap – A symbol that defines a class of 60-62 The given table is called the class interval.
• Class Limits – The end numbers, 60 and 62, are called class limits the smaller number (60) is the lower class limit, and the larger number (62) is the upper-class limit.
• Open Class Intervals – A class interval that, at least theoretically, has either
no upper-class limit or no lower class limit indicated is called an open class interval.
• Class Boundaries – If heights are recorded to the nearest inch, the class interval 60–62 theoretically includes all measurements from 59.5000 to 62.5000 in. These numbers, 59.5 and 62.5, are called class boundaries, the smaller number (59.5) is the lower class boundary and the larger number
(62.5) is the upper-class boundary.
• The size, or width, of a class gap – The size or width of a class gap The difference between lower and upper class Is the boundary and is also known as the class Width, class size or class length.If all class intervals in a frequency distribution. Of equal width, this common width is indicated
C. In such a case c is equal to the difference Between two or two successful lower class boundaries Successful upper class boundaries.
• Classmark – The classmark is the midpoint of the class gap Obtained by adding bottom and top Class boundaries and division by 2.

### The Frequency Polygon

If another way to represent the same dataset Using a frequency polymer.
A graph showing the frequency polymer Data using points connecting lines
Designed for frequencies at midpoints of. Classes. Frequencies represented score.

### The Ogive

Ogive is a graph that represents. Cumulative frequencies for classes
There is a frequency distribution.

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# Statistics for IT– Worldwideasy – 01

Today we hope to focus on a different topic. This is very important for people who are educated. Statistics for it is the topic here. Let’s find out now.

## Introduction to Statistics

Collection science, organization, presentation, analysis and
Interpret data to assist in making more effective decisions and Used to summarize and analyze statistical analysis.
The data is then processed into useful decision-making information

## Types of statistics

• Detailed Statistics – Methods of Organizing, Summarizing, and Presenting data in an informative manner.
• Guessing Statistics – Methods used to determine something About a population on a sample basis.

## Inferential Statistics

• Estimation
• Hypothesis testing

## Sampling

A sample should have similar characteristics
As the population it represents.

Sampling methods can be :

• random
• nonrandom

Random sampling methods,

• Simple random sample
• Stratified sample
• Cluster sample
• Systematic sample

Descriptive Statistics,

1. Collect data
2. Present data
3. Summarize data

#### Statistical data

• Collect data relevant to the problem being studied. This usually the most difficult, expensive, and time-consuming part.
• Statistical data are usually obtained by counting or measuring items.
• The variable is an item of interest that can be taken in a variety of ways Numerical values.
• A constant has a fixed numeric value.

### Data Collection Methods

• Interviews
• Questionnaires
• Survey
• Observation

• Qualitative
• Quantitative

## Qualitative Data

Quality data is usually described in words Letters. They are not as widely used as quantitative data This is because most numerical techniques do not apply Quality data. For example, it makes no sense to Find a normal hair color or blood type.

## Quantitative Data

Quantitative data are always numbers and they are Results of calculating or measuring the characteristics of a population. this data can be divided into two Subgroups:

• Discrete
• Continuous

## Types of variables

The numerical scale of measurement

• Nominal
• Ordinal
• Interval
• Ratio

## Data presentation

This has used 6 methods for data presentation.

• Histogram
• Frequency polygon
• Ogive
• Pie Chart
• Bar chart
• Time Series Graph

#### Histogram

Graphically used frequently. Current time interval and rate data Often used interval and Rate data. Shown from adjacent bars There are a numerical range In summary Arbitrarily selected frequencies Class values.

#### Frequency polygon

Another common method is The gap presented graphically And rate data.
To create a frequency Marks the frequency of the polymer On the vertical axis and Values ​​of variability Measured on the horizontal axis, Like a histogram. If the purpose of the presentation Comparing with others Distribution, frequency The polygon provides a good stuff Summary of data.

#### Ogive

A graph of a cumulative Frequency distribution. For a relative frequency, This can be used to turn.

#### Pie Chart

Pie note is an effective method. Percentage display Divides data by category. Relative sizes are useful. The data must be components.

#### Bar chart

Nominal submission And average scale data. Uses one column to represent Frequency for each category. The bars are usually positioned With their base vertically Located on the horizontal axis.

#### Time Series Graph

Time series graph It is a data graph measured over time. The horizontal axis here This graph represents Time limits and Shows the vertical axis Numerical values Corresponds.