Statistics for IT– Worldwideasy – 05

Statistics for that. Here you have, Applying the basic calculation principle. Calculation of percussion. Calculation of Comb Combinations. Distinguish combinations against per induction. Can be done.

Fundamental CountingPrinciple -Statistics

Can be used here Determine the number of possible consequences
When there are two or more symptoms. and Can be used here Determine the number of possible consequences When there are two or more symptoms.

Motivation is a provision. In a specific order.

Permutations – Statistics

To find the number of triggers here Items, we can use basic. By the principle of calculation or by factorial notation.

Combinations

Is a combination of Items not ordered are a material arrangement.

Because the order is not important Combinations, there are fewer combinations. Than inductions. Combinations A “subset” of triggers.

In mathematics, a combination is a selection of items from a collection, the order of selection is not important (unlike inductions). For example, give three fruits and say one apple, one orange, and one pear, three combinations of two can be extracted from this set: apple and pear Apples and oranges; Or pears and oranges. More formally, the k-combination in an S set is a subset of the k-specific elements in S. If the set has the element n, the number of k-combinations is equal to the two-dimensional coefficient.

See the below examples and get the idea,

Next, we meet with a very wide-ranging lesson. Until then, keep these lessons in mind.

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Statistics for IT– Worldwideasy – 04

Statistics for that. Expansion Summarize data using median trend measurements such as the mean. Mean, mode, and midrange. Describe data using variability measurements such as range, variability, and so on. Identify the location of a data value in a dataset using various measurements, such as percentages, decimals, and quarters in Statistics.

Measures in Statistics

Measures in Central Tendency in Statistics

• A measure of centripetal tendency is a detailed statistic. Describes the average or average value of a set of points.
• There are three common measures of central tendency,
• mean
• median
• mode
• When raw data is organized it helps to display it. The form of a table showing the frequency (e) with each data Item (x) occurs. Such a table is called a frequency table.
• However, this may be the case when a large range of data is involved. Breaking down data into smaller groups first is beneficial. In which case, the resulting table is called a group Frequency table.

Mean (Arithmetic Mean)

• The average calculation of mean numbers “middle” Is the value of a set of numbers. Add up all the numbers to calculate it. Then divide how There are many numbers.
• The arithmetic mean or abbreviated mean of an N group.

THE ARITHMETIC MEAN COMPUTED FROMGROUPED DATA IN STATISTICS

Assumes a procedure for finding the mean for group data. That the mean of all raw data values ​​in each class is the same Takes the middle point of the class. In reality, this is not true. The average of the raw data values ​​for each class will not be average. The same as the midpoint. However, using this procedure From some Will give an acceptable approximation of the mean.
Values ​​fall above the midpoint and other values ​​fall below For each class, the midpoint and the midpoint represent Assessing all values ​​in the class.

Ex: Miles Run per Week

The Median

The mean is half of a dataset. Before you can find this out, the data must be arranged in order. Then The dataset is ordered, which is called the data array. Mean Will fall between a certain value or two in the dataset.

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Statistics for IT– Worldwideasy – 03

Statistics for it. Expanding the amount given in Sigma notation to a clear amount through this statistics lesson. Write a clear sum of S sigma notation. A clear pattern for individual terms. Using rules to handle money is expressed in Ig sigma notation. Explained.

Sigma Notation for Statistics

• Sigma notation is a method used to write a long sum in a Short path.
• For example, we often like to summarize a number of terms 1 + 2 + 3 + 4 + 5 or a 1 + 4 + 9 + 16 + 25 + 36 There is a clear pattern to the numbers.
• More generally, we have u1, u2, u3,. . . , Otherwise we can write the sum of these numbers as u1 + u2 + u3 +. . . + un.
• This is an abbreviated form of writing that allows ur to represent the general term and put it in sequence.

See the Below example forget some idea.

Writing a long sum in sigma notation – Statistics

Statistics – We have been given a long sum of money and suppose we want to declare. It is from Sigma numbering. How should we do this?

See below example,

Rules for use with sigma notation

• In general, we can write if we add a constant n time.
• Suppose we have a fixed time collection.
• But from this calculation, we can see that the result is the same.
• Suppose we have the sum of k and a constant. Give us this.
• But from this calculation, we can see that the result is the same.
• If a and c are constants, and f (k) and g (k) are the functions of k.

See the below example for more knowledge,

I hope you have gained a great deal of knowledge from this section. Stay with us often so you can gain a very broad knowledge. See you soon in another lesson!

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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.