Q1. Define/outline the following:
a. the difference between a ‘one-tailed test’ and a ‘two-tailed
test’.
b. the importance...
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Advance Math
Q1. Define/outline the following:
a. the difference between a ‘one-tailed test’ and a ‘two-tailedtest’.
b. the importance of sample size in the context of OLSregression.
*c. four different types of data structures and discuss theirpotential usefulness and application in finance.
d. the OLS assumptions
e. Correlation is not causation. Briefly discuss.
(c. is the part I'm confused most about)
Answer & Explanation
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a Differences Between Onetailed and Twotailed TestThe fundamental differences between onetailed and twotailedtest is explained below in pointsOnetailed test as the name suggest is the statisticalhypothesis test in which the alternative hypothesis has a singleend On the other hand twotailed test implies the hypothesistest wherein the alternative hypothesis has dual endsIn the onetailed test the alternative hypothesis isrepresented directionally Conversely the twotailed test is anondirectional hypothesis testIn a onetailed test the region of rejection is either on theleft or right of the sampling distribution On the contrary theregion of rejection is on both the sides of the samplingdistributionA onetailed test is used to ascertain if there is anyrelationship between variables in a single direction ie left orright As against this the twotailed test is used to identifywhether or not there is any relationship between variables ineither directionIn a onetailed test the test parameter calculated is more orless than the critical value Unlike twotailed test the resultobtained is within or outside critical valueWhen an alternative hypothesis has sign then a twotailedtest is performed In contrast when an alternative hypothesis has or sign then onetailed test is carried outd The Seven Classical OLS AssumptionsAssumption 1 The regression model is linear in the coefficientsand the error termThis assumption addresses the functional form of the model Instatistics a regression model is linear when all terms in themodel are either the constant or a parameter
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