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8.8. SUPPLEMENTARY MATERIALS 1) - levin-and-rubin-solution-manual 2) =MsQKG4Cu3xwC 8.9. ASSIGNMENTS In sample of 100 TV viewers, 330 watched a particular programme. Find 99 per cent confidence limits for TV viewers who watch this programme. 8.10. REFERENCE BOOKS 1) Agarwal, B.L. ‘Basic Statistics’, Wiley Eastern Ltd., New Delhi. 2) Chance, W., ‘Statistical methods for Decision’ Irwin Inc., Homewood. 3) Gopikuttam, G., ‘Quantitative Methods and Operations Research’, Himalaya Publishing House, Bombay. 4) Gupta, S.P., ’Statistics Methods’, Sultan Chand and Co., New Delhi 5) Levin , R., ‘Statistics for Management’, Prentice Hall of India, New Delhi, 1984. 6) Reddy, C.R., ‘Quantitative Methods for Management Decision’, Himalaya Publishing House, Bombay, 1990. 8.11. LEARNING ACTIVITIES Out of 20,000 customer’s ledger accounts, a sampl e of 500 accounts was taken to test the accuracy of posting and balancing where in 40 mistakes was found. Assign limits within which the number of defective cases can be expected to lie at 95 per cent confidence. 8.12. KEY WORDS 1) Population and sample. 2) Parameter and statistics. 3) Sampling techniques. 4) Probability sampling. 5) Non probability sampling. 6) Sample and distribution.
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84 LESSON 9 HYPOTHESIS TESTING 9.1. INTRODUCTION To be fruitful the decision, one should collect random sample for or against some point of view of proposition. Such point of view or proposition is termed as hypothesis. Hypothesis is a proportion which can be put to test to determine validity (Goode and Hatt). A hypothesis, in statistical parlance, is a statement about the nature of a population which is to be tested on the basis of outcome of a random sample. 9.2. OBJECTIVE The main aim of this Lesson is to study the Basics of Hypothesis testing. After going through this Lesson you should be able to understand Hypothesis, null hypothesis, alternative hypothesis, type I error and type II error 9.3. CONTENTS 9.3.1. Testing Hypothesis 9.3.2. Test of Significance 9.3.1. TESTING HYPOTHESIS The testing hypothesis involves five steps which are as: a. Hypothesis formulation The formulation of a hypothesis about population parameter is the first step in testing hypothesis. The process of accepting or rejecting a null hypothesis on the basis of sample results is called testing of hypothesis. The two hypothesis in a statistical test are normally referred to: i. null hypothesis ii. Alternative hypothesis Reasoning for possible rejection of proposition is called null hypothesis. In other words, it asserts that there is no true difference in the sample and the population and that the difference found is accidental and unimportant arising out of fluctuations of sampling. Hence the word, null means invalid, void or amounting to nothing. The decision-marker should always adopt the null attitude regarding the outcome of the sample.
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