Quiz 2 - Statistics & Probability

It is a process in making decisions in evaluating claims about a population.

• alternative hypothesis

• hypothesis testing      

• null hypothesis 

• test statistic

This assumes that there is no change, no difference, no relationship, or the independent variable has no effect on the dependent variable.

• alternative hypothesis

• hypothesis testing 

• null hypothesis          

• test statistic

What error would occur when the the null hypothesis is rejects when it is true?

• Type I 

•  Type II  

• Type III 

• Type IV

The following are phrases used for one-tailed test except

• above   

• below 

•        equal    

• decreased

Null and alternative hypotheses are statements about:

• population parameters  

• sample parameters.

• sample statistics

• it depends - sometimes population parameters and sometimes sample statistics.

What region in a graph where the range of values leads the researcher to accept the null hypothesis?

• acceptance    

• critical    

• rejection       

• significance

It is the boundary of the rejection region and non-rejection region.

• acceptance value

• critical value

• rejection value

• test value

This is a right-tailed test.

                                  

• H_o = parameter = specific value

  H_a = parameter < specific value

• H_o = parameter = specific value

  H_a = parameter > specific value

• H_o = parameter = specific value

  H_a = parameter ≠ specific value   

• H_o = parameter = specific value

  H_a = parameter = specific value

ABC health research laboratory uses a 1% error on their study. Formulate an alternative hypothesis.

• H_{a :} ABC health research laboratory studies do not use a 1% error.

• H_{0 :} ABC health research laboratory studies do not use a 1% error.

• H_{a :} ABC health research laboratory studies uses a 1% error.

• H_{0 :} ABC health research laboratory studies uses a 1% error

A criminal was sentenced guilty of a crime he was framed up. What sort of an error did the judge make, and why?

• Type I, because their sets of evidence are true when it's actually false

• Type I, because their sets of evidence are false when it's actually true.

• Type II, because their sets of evidence are false when it's actually true.

• Type II, because their sets of evidence are true when it's actually false