

Receive articles by email
Archives
Categories

Recent Posts
 5 self management skills to get success
 Null hypothesis and Alternative hypothesis
 Meaning, testing and types of hypothesis
 Properties and importance of normal distribution
 Types of sampling
 Types of errors in statistics
 Error in Statistics and its reasons
 Advantages and disadvantages of sample method
 Meaning and principles of sampling
 Primary and secondary data, their differences and advantages
Top Posts & Pages
 4 types of consumer buying behavior
 4 types of dividend policy
 Concept, objectives, scope, importance of Human resource planning
 5 Stages of consumer buying decision process
 3 Types or Kinds of Capital budgeting
 Methods of wage payment
 Determinants of consumer buying behavior
 7 factors affecting compensation
 Types of working capital
 Nature, objectives and scope of human resource management
Meta
Null hypothesis and Alternative hypothesis
Let us discuss the difference between null and alternative hypothesis:
Null hypothesis
The hypothesis we want to test or a hypothesis of no difference is called null hypothesis. It is denoted by H_{o. }for example if we want to test that the population mean is equal to 400, we can write H_{O}: µ : 400 and we read it as “ the null hypothesis is that the population mean is equal to 400.
1) Null hypothesis is expressed in equality like H_{O}: µ = µ_{O Continue reading →}
Posted in Business Statistics
Leave a comment
Meaning, testing and types of hypothesis
Meaning of hypothesis:
It is a quantitative statement about population. It is some assumption or statement which may or may not be true about a population, which we want to test on the basis of evidence of random sample.
Testing of hypothesis:
There is an element of risk of taking wrong decisions at the time of taking of decision. For example when a company launched a new product then they are interested to find out that it is going to be a big product in the market or not. It is here the modern theory of probability play an important role in decisionmaking which helps in arriving at a particular decision which is known as a testing of hypothesis. The theory of testing of hypothesis was initiated by J. Neyman and E. S. Pearson. They use statistical techniques to arrive at a particular decision; in this sample size is fixed in advance.
There is another technique derived by Abhram Wald called Sequential Testing in which sample size is not fixed.
Types of hypothesis:
There are 2 types of hypothesis:
a) Simple hypothesis
b) Composite hypothesis
If the hypothesis completely specifies the population then it is simple otherwise it is composite.
I hope you understood the meaning, testing and types of hypothesis.
Posted in Business Statistics
Leave a comment
Properties and importance of normal distribution
Meaning of Normal distribution or law of error
Binomial and passion distribution are discrete probability distribution. But normal probability distribution commonly called normal distribution. It is theoretical distribution for the continuous variable. The normal distribution was first discovered by English mathematician De Moivre in 1733.later it was rediscovered by Karl Gauss in 1809 and in 1812 by Laplace. Normal distribution is also called Gaussian distribution or Gaussian law of error as this theory describes the accidental error of measurements. Continue reading
Types of sampling
Sampling is mainly divided into two types; probability or random sampling and non probability or non random sampling. In other words, Sampling methods are broadly classified into probability or random sampling and non probability or non random sampling. Let us discuss them one by one:
1) Probability or random sampling: Under the probability or random sampling, each and every unit of the universe has an equal chance of being selected. It is the best technique based on the law of statistical regularity. Continue reading
Types of errors in statistics
Errors in statistics or any statistical investigation can be broadly classified in two types:
a) Sampling errors and b) non sampling errors
a) Sampling errors: Even after taking care in selecting sample, there may be chances that true value is not equal to the observed value because estimation is based upon a part of the population not on the whole. Hence sampling give rise to certain errors known as sampling errors. Continue reading
Error in Statistics and its reasons
Definition Error in Statistics:
Error in statistics means the difference between true value and the estimated value. It is different from the mistakes which may be done while making calculations or observations. Continue reading
Posted in Business Statistics
Leave a comment