Chapter 9 Hypothesis Testing 9.1 The Language of Hypothesis Testing.
Testing of Hypothesis
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Testing of Hypothesis Business Research Methods Testing of Hypothesis 1
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Testing of Hypothesis
Transcript of Testing of Hypothesis
Testing of Hypothesis
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Testing of Hypothesis
Business Research Methods
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Introduction
There are four interrelated components that influence the conclusion Sample size Effect size or the salience of the treatment relative to
the noise in measurement Alpha level or a significance level Power or the odd that you will observe a treatment
effect when it occursGiven values for any three of these
components, it is possible to compute the value of the fourth
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Testing of Hypothesis
A statement of prediction is called hypothesisWe have two types of hypothesis
Null Hypothesis (H0) Alternate Hypothesis (H1)
Null Hypothesis usually refers to the “no difference” or “no effect” case
Usually in management research we expect that our treatments and programs will make a difference
So, typically, our theory is described in the alternative hypothesis
α or significance level is chance you can take while confidence level (β) is power behind your statement.
α = 1 – β e.g. if one can take a chance of 5%for his statement; it means he is 95% confident to his statement
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Type I and Type II Error
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Two types of error can be expected when we accept of reject the hypothesis
Type I Error: When we reject the Null Hypothesis when it is true
Type II Error When we accept the Null Hypothesis when it is false
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Probability Distribution and Normal Distribution in Testing of Hypothesis
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Probability distribution is classified in two Discrete
It allows to take only a limited number of values Continuous
The variable under consideration is allowed to take any value within a given range
A value of, x, from a normal distribution specified by a mean m and a standard deviation s can be converted to a corresponding value of z, in a standard normal distribution with the transformation z = │X- µ│/s
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Testing of Hypothesis
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Two Tail TestOne Tail Test
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Hypothesis Testing of Proportion
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In case of qualitative phenomena, we have data on the basis of presence of absence of an attribute (s)
With such data the sampling distribution may take the form of binomial probability distribution whose mean would be equal to n*p and standard deviation equal to √npq
Means proportion of success = npStandard deviation of the proportion of success = √pq/nZ = p – q / s
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Questions
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A sample of 400 male students is found to have a mean height of 67.47 inches. Can it be reasonably regarded as a sample from a large population with mean height 67.39 inches and standard deviation 1.30 inches? Test at 5% level of significance.
Raju restaurant near the railway station at Falna has been having average sales of 500 tea cups per day. Because of the development of bus stand nearby, it expects to increase its sales. During the first 12 days after the start of the bus stand, the daily sales were as under:
550, 570, 490, 615, 505, 580, 570, 460, 600, 580, 530, 526
On the basis of this sample information, can one conclude that Raju Restaurant’s sales have increased? Use 5% level of significance.
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