Business research method
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Business research method Presentation Transcript

  • 1. Business Research MethodologyMBA : 2nd SemesterPresented by :Shantayya.S.G
  • 2. Basic Concepts in HypothesesTesting Meaning of Hypothesis Testing Null Hypotheses & Alternate Hypotheses Type I & Type II Errors One Tailed & Two Tailed Test Steps in formulating Hypotheses Testing
  • 3. What is Hypothesis testing Hypothesis is the making an assumption about thepopulation parameter. OR A set of logical and statistical guidelines used to makedecisions from sample statistics to populationcharacteristics.For example:The customer loyalty of brand A is better than brand B.
  • 4. Null Hypothesis(Ho): The null hypothesis (H0) refers to a hypothesized testingnumerical value or range of values of the populationparameter. Specific statement about a population parameter made forthe purposes of argument. States the assumption to be tested, is a status quo. Is always about a population parameter, not about a samplestatistic.
  • 5. Example of Ho: In a clinical trial of a new drug, the nullhypothesis might be that the new drug is nobetter, on average, than the current drug. Wewould writeH0: there is no difference between the two drugson an average.
  • 6. Alternate Hypothesis(HA) An alternatives hypothesis (H1) is the logical oppositeof the null hypothesis. Represents all other possible parameter values exceptthat stated in the null hypothesis. Challenges the status quo. Hypothesis that is believed (or needs to be supported)by the researcher –a research hypothesis.
  • 7. Example of HAIn the clinical trial of a new drug, the alternativehypothesis might be that the new drug has a differenteffect, on average, compared to that of the current drug.We would writeHA: the two drugs have different effects, on average.orHA: the new drug is better than the current drug, onaverage.The result of a hypothesis test:‘Reject H0 in favour of HA’ OR ‘Do not reject H0’
  • 8. Type I Error: If the null hypothesis is true and we reject it is calledtype I error. Rejected H0 because the results occurred by chance Conclude that there is a significant effect, even thoughno true effect exists Probabilities of Type 1 error called – alpha ( )Determined in advance, typically 5%
  • 9. Type II Error: If the null hypothesis is false and we accept it is calledtype II error. Accept H0 even though it is not true Conclude that there is no significant effect, eventhough a true difference exists Probabilities of Type II error called – beta ( )
  • 10. Type I Error & Type II ErrorAccept H0 Reject H0Correct Decision Type I ErrorType II Error Correct DecisionHo (True)Ho (False)
  • 11. One Tail Test:Rejection of null hypothesis for significant deviationfrom the specified value Ho in one direction (tail) ofthe curve of sampling distribution is called one tailedtest.For example:Boll pen better then ink pen .
  • 12. Two Tailed Test:Rejection of null hypothesis for significant deviationfrom the specified value Ho in both the direction (tail)of the curve of sampling distribution is called twotailed test.Foe example:A product is manufactured by a semi-automaticmachine. Now, assume that the same product ismanufactured by the fully automatic machine.This will be two-sided test, because the nullhypothesis is that “the two methods used formanufacturing the product do not differsignificantly.
  • 13. Steps in Hypotheses Testing1. Formulation of the null and alternate hypothesis2. Definition of a test statistic3. Determination of the distribution of the teststatistic4. Definition of critical region of the test statistic5. Testing whether the calculated value of the teststatistic falls within the acceptance region.
  • 14. 1: Formulation of H0 The Null hypothesis assumes a certain specific valuefor the unknown population parameter. Defined as an inequality – greater than or less than. For example, if the mean of a population isconsidered, then H0: μ ≤ μ0 H0: μ = μ0 H0: μ ≥ μ0
  • 15. 2: Formulation of Ha The alternate hypothesis assigns the values to thepopulation parameter that is not contained in the nullhypothesis. For example, Ha: μ > μ0 Ha: μ ≠ μ0 Ha: μ < μ0 The null hypothesis is accepted or rejected on the basisof the information provided by the sample.
  • 16. 3: Definition of a Test Statistic A test statistic must be defined to test the validity ofthe hypothesis. The test statistic is computed from sampleinformation. A number calculated to represent the match between aset of data and the expectation under the nullhypothesis
  • 17. 4: Determination of thedistribution of the test statistic The probability distribution of the test statisticdepends on the null hypothesis assumed, theparameter to be tested, and the sample size.Commonly used ones are the Normal, “t”, Chi-squareand F-distributions.
  • 18. 5: Definition of the critical regionfor the test statistic The set of values of the test statistic that leads to therejection of H0 in favour of Ha is called the rejectionregion or critical region. Depends upon whether the testing is one-sided ortwo-sided.
  • 19. 6: Decision rule A decision rule is used to accept or reject the null hypothesis. P- valueP < αReject the null hypothesisStatistically significant Test statisticTest statistic (calculated value) < Table value of αAccept H0Statistically insignificant