Category: Statistics

Terms of Statistics

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Common Terms of Statistics

1. Population:
Totality of individuals or objects about which information is required is known as population.
e.g. population of patients of hepatitis , students of MBA classes at RYK campus etc…

2. Sample:
A small part of the population which is selected to investigate the properties of the population is known as sample.

3. Variable:
A characteristics which changes from individual to individual or object to object is known as variable.
e.g. height of students, income of people, weight of potatoes etc…

Variables are sub-divided into two categories:

3.1 Quantitative Variable:
Any variable which can be measured numerically is known as Quantitative variable.
e.g. income, speed, distance, temperature etc…

Quantitative variable are further divided into two types:

3.1.1 Discrete Variable:
A variable which can assume a finite number of values is known as discrete variable.
e.g. no. of leaves, no. of children etc…

3.1.2 Continuous Variable:
A variable which can have any value in a given interval [a,b] is known as continuous variable. Therefore the number of possible values of a continuous variable is infinite.
e.g. height, weight, distance etc…

3.2 Qualitative Variable:
Any variable which can’t be measured numerically is known as Qualitative variable. It is also known as “Attribute”.
e.g. smoking habit, religion, eye color, etc…

4. Constant:
A characteristic which does not change its value from individual to individual and object to object is called a constant.
OR “A variable which have only one value is called constant.”

5. Measurement Error:
The difference between the actual value (True) and the response we get (Recorded) is measurement error. It may be positive or negative.

5.1. Random Error:
If error is due to human mistake or the direction of error is not the same that it’s said to be a Random Error.
e.g. reading error, human mistake in measurement etc…

5.2 Systematic Error:
If the direction of the error in all data is same then it is called a systematic error.
e.g. Machine error, scale error etc…

Statistical Data

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Methods of collecting Statistical Data

1. Complete Enumeration:
If the required information is obtained from each and every unit in the population then this is known as complete enumeration.

2. Sample Survey:
If the required information is obtained from only a part of the population (sample units) then this is known as sample survey.

DATA Types

1. Primary Data:
The data which is originally collected and have not gone through any statistical process is known as primary or raw data.

Procedures to collect primary data

1.1 Direct Personal Investigation:
In this method, the required information is obtained directly from the individual or object concerned.

1.2 Indirect Investigation:
If the required information involves sensitive information, people may not give the correct information or refuse to respond at all. In such case the required information is obtained from people close to the person concerned.

1.3 Questionnaire Method:
In this method, a questionnaire which consist questions relevant to required information is give to the people with the request to return the filled questionnaire within a give period.
This method is used for area where educated people live.

1.4 Collection through Enumerators:
In large scale surveys, trained enumerators are used to obtain the required information.

2. Secondary Data:
The data which have been already collected and have undergone through any statistical treatment is known as secondary data.

Sources of secondary data:

2.1 Official Sources:
Examples are Ministry of Agriculture, federal bureau of statistics etc…

2.2 Semi-Official Sources:
State Bank of Pakistan, WAPDA, HEC etc…

2.3 Private Organizations:
NGO’s, Chamber of Commerce, Banks etc…

Classification

“The process of dividing the observations into groups or classes is known as classification.”

Why we need to classify?

Let suppose we have result of 10,000 students with us. We can’t remember the marks obtained by all students. Now what If someone asks how was the result? How many students did pass? How many were failed? What were the average marks?
To answer these questions we have to summarize our data or we can say classify it. Then we can easily answer the asked questions.

Frequency Distribution:

“A table listing all the values or groups of values of variable along with number of observations of each value or group of value is known as frequency distribution.”

Steps to construct Frequency Distribution:

1. Find the range of the data
2. Decide the number of classes; approx number of classes = 1+3.3 log10 n
3. Obtain class interval size by dividing the range by number of classes.
4. Form the classes such that the smallest and the largest observations are covered.
5. Distribute original data into classes by tally marks.

Introduction to Statistics

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Business Statistics

What is Statistics?

In general, “numerical facts or information collected about a person, a group of persons, an institution, a province etc… is known as statistics”.
e.g. The statistics of Javed Miandad, the statistics of an automobile company etc…

“Statistics is defined as the plural of statistic.”
Statistic: Any numerical value such as mean, median, mode, variance etc… calculated from sample data is known as statistic.

As a subject, Statistics is defined as “the collection of methods used to collect, summarize and analyze the information to draw conclusions and make decisions.”

Branches of Statistics

Statistical methods are divided into two broad categories:

1. Descriptive Statistics:
It is branch of statistics which consist of methods of summarizing and presenting data in such a way that main features of the data become apparent.
Frequency Distribution, charts, measures of location, measures of dispersion etc…

2. Inferential Statistics:
The branch of statistics which consist of methods of analyzing the data and draw conclusions from it. The process of hypothesis testing is part of infrential statistics.