CHAPTER 7 - HYPOTHESIS TESTING Flashcards
Statistical Hypothesis
Is an assumption about a population parameter. This is a statement that cannot be accepted to be true unless proven.
Hypothesis Testing
Refers to the formal procedures used by statisticians to reject or not reject the statistical hypothesis.
Hypothesis Testing
Is a second form of statistical inference.
Null Hypothesis
Denoted by Ho, is usually the hypothesis that sample observations result purely from chance
Alternative Hypothesis
Denoted by Hi or Ha,is the hypothesis that sample observations are influenced by some non-random cause.
The null hypothesis
Will always state that the parameter equals the value specified in alternative hypothesis (Hi)
Type 1 error
Occurs when we reject a true null hypothesis.
Type 2 error
Occurs when we don’t reject a false null hypothesis.
Types of Alternative Hypothesis
1.Directional or predictive
2.Non-Directional or non-predictive
If the alternative hypothesis contains the less-than inequality symbol (<) the hypothesis is
Left-Tailed test
If the alternative hypothesis, contains the greater-than inequality symbol (>), the hypothesis test is
Right-Tailed test
One-tailed test
A test of statistical hypothesis where the region of rejection is only one side of the sampling distribution.
Two-tailed test
A test of statistical hypothesis where the region of rejection is on both side of the sampling distribution.
Once the null and alternative hypothesis are stated, the next step is to randomly sample the population and calculate a
Test statistic
If the test statistics value is inconsistent with the null hypothesis we rejected the null hypothesis and
Infer that the alternative hypothesis is true
Type 1 error
Occurs when we reject a true null hypothesis
Type 2 error
Occurs when we don’t reject a false null hypothesis.
P-value
Provides measure of how much statistical evidence exists to support the alternative hypothesis. This measure can be weighed in relation to the other factors, especially the financial ones.
P-value
Is a probability of observing a test statistic at least as extreme as the one computed given that the null hypothesis is true.
If p-value is between 1% and 5%,
there is a strong evidence that supports the alternative hypothesis.
If P-value is between 5% and 10%
There is a weak evidence to support the alternative hypothesis.
If p-value exceeds 10%
There is no evidence that supports the alternative hypothesis.
If the p-value is less that a, we judge the p-value
Small enough to reject the null hypothesis
If the p-value is less than a
We do not reject the null hypothesis
Steps in Hypothesis testing
1.Formulate the null and alternative hypothesis
2.Determine the level of significance of the study
3.Determine the critical value of the test statistics
4.Compute the value of the test statistics
5.Make decision
Reject the null hypothesis if the absolute computed value of the test statistics is greater than the absolute critical value.
Otherwise, Do not reject Ho
