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BUSINESS RESEARCH METHODSLECTURE: 6

3After studying this session you would be able to

Understand and infer results from data in order to answer the associational and differential research questions using different parametric and non parametric tests.understand implement and interpret the chi-square, phi and cramers Vunderstand, implement and interpret the correlation statisticsunderstand, implement and interpret the regression statisticsunderstand, implement and interpret the T-test statisticsLesson Objectives4Non parametric test.Chi square /Fisher exactPhi and cramers vKendall tau-bParametric testCorrelationPearson correlationSpearman correlationRegressionSimple regressionMultiple regressionT-TestOne-sample T-testIndependent sample T-testPaired sample T-testLesson OutlineInferential StatisticsInferential statistics are used to make inferences (conclusions) about a population from a sample based on the statistical relationships or differences between two or more variables using statistical tests with the assumption that sampling is random in order to generalize or make predictions about the future.

Inferential StatisticsInferential statistics are used

To test some hypothesis either to check relationship between variables (two/more) or to compare two groups to measure the differences among them. To generalize the results about a population from a sampleTo make predictions about the future.To make conclusions

Some basics about inferential statistics!Statistical significance (The p value)Statistical significance test is the test of a null hypothesis Ho which is a hypothesis that we attempt to reject or nullify. i.e.Ho =There is no relationship /Difference between variable 1 and variable 2

p value > 0.05 Ho is accepted and H1 is rejected.p value < 0.05 Ho is rejected and H1 is accepted.

8 Confidence IntervalConfidence interval is a range of values constructed for a variable of interest so that this range has a specified probability of including the true value of the variable. The specified probability is called the confidence level, and the end points of the confidence interval are called the confidence limits.

It is one of the alternatives to null hypothesis significance testing (NHST).

9The effect size (weak, moderate or strong)Effect size is the strength of the relationship between the independent variable and the dependent variable, and/or the magnitude of the difference between levels of the independent variable with respect to the dependent variable. 0No effectNo relationship>0 0.33Small effectWeak relationship>0.33 0.70Medium/typical effectModerate relationship>0.70