Page 384 - DECO504_STATISTICAL_METHODS_IN_ECONOMICS_ENGLISH

Unit 30: Types of Hypothesis: Null and Alternative, Types of Errors in Testing Hypothesis and Level of Significance
Dilfraz Singh, LPU

Unit 30: Types of Hypothesis: Null and Alternative, Types of Notes

Errors in Testing Hypothesis and Level of Significance

CONTENTS
Objectives
Introduction
30.1 Null and Alternative Hypothesis
30.2 Types of Errors in Testing Hypothesis
30.3 The Level of Significance
30.4 Summary
30.5 Key-Words
30.6 Review Questions
30.7 Further Readings

Objectives

After reading this unit students will be able to:
• Explain Null and Alternative Hypothesis.
• Know the Types of Errors in Testing Hypothesis.
• Discuss the Level of Significance.
Introduction

In unit 29 we showed how a sample could be used to develop point and interval estimates of population
parameters. In this unit we continue the discussion of statistical inference by showing how hypothesis
testing can be used to determine whether a statement about the value of a population parameter
should or should not be rejected.
In hypothesis testing we begin by making a tentative assumption about a population parameter. This
tentative assumption is called the null hypothesis and is denoted by H . We then define another
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hypothesis, called the alternative hypothesis, which is the opposite of what is stated in the null
hypothesis. We denote the alternative hypothesis by H . The hypothesis testing procedure uses data
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from a sample to assess the two competing statements indicated by H and H .
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This unit shows how hypothesis tests can be conducted about a population mean and a population
proportion. We begin by providing examples of approaches to formulating null and alternative
hypotheses.
30.1 Null and Alternative Hypothesis

(a) Null Hypothesis: The null hypothesis asserts that there is no real difference in the sample and
the population in the particular matter under consideration and that the difference found is
accidental and unimportant arising out of fluctuations of sampling. The null hypothesis
constitutes a challenge and the function of the experiment is to give the facts a chance to refute
or fail to refute this challenge.
For example, if we want to find out whether the new vaccine has benefited the people or not,
the null hypothesis, shall be set up saying that “the new vaccine has not benefited the people”.
The rejection of the null hypothesis indicates that the differences have statistical significance
and the acceptance of the null hypothesis indicate that the differences are due to chance.

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