# MGEB12H3 Chapter Notes - Chapter 9: Null Hypothesis, Alternative Hypothesis, Statistical Parameter

by OC993160

Department

Economics for Management StudiesCourse Code

MGEB12H3Professor

Ataollah MazaheriChapter

9This

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Hypothesis Testing: can be used to determine whether a statement about the value of a population

parameter should or should not be rejected.

- Null hypothesis

- Alternative hypothesis

Usually set up to see if enough evidence can reject the null while to accept the alternative.

Answering in statistics world:

- NEVER actually prove the null or alternative based on statistics, only have enough evidence to

support the null/alternative.

o HOWEVER, there is always a chance of error, even with enough evidence.

- ONLY conclude or object alternative

o ONLY If evidence from sample is strong enough to reject the null, you accept the

alternative

o Other-wise, you do not accept alternative, but do not prove null, only strong evidence to

support null.

Null hypothesis: H0, is a tentative assumption about a population parameter.

- Easiest way to identify a null: = sign ie. More or equal, or, less or equal

Alternative hypothesis: Ha, is the opposite of what is stated in the null hypothesis.

Usually the research hypothesis should be expressed as the alternative hypothesis.

- Thus, if evidence is high to support the research hypothesis: null is rejected while alternative is

accepted

i.e. testing the validity of a claim

- claim: null

- usually test for the alternative, so if high enough we can accept alternative and reject the

null or conclude with unknown/inconclusive

Null and Alternative Hypothesis about a Population Mean, µ

- µ0 is the hypothesized value of the population mean

*just write = for H0 redundant if include less or more than

*assume the null is accepted at =

- Attempt to reject null when assuming it is correct

o Cannot do a formal test if null is not assumed correct

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