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

Data

  • 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.