If the null hypothesis is rejected, the researcher concludes that there is sufficient evidence to believe that the difference between the sample statistic and the hypothesized parameter is due only to chance? a. trueb. falsec. unknownd. indeterminate

b. False.

See explanation below.

Step-by-step explanation:

b. False.

When we have a significant result that means where represent the p value for the test and the significance level assumed at the begin of the hypothesis test.

For this case we have a null hypothesis and an alternative hypothesis for a parameter of interest let's say , and using the test we conclude thar we reject the null hypothesis, so on this case we need to have that , so then that means that we have a significant difference.

And when we have this situation we can't say that the difference between the sample statistic and the hypothesized parameter is just due to chance, since we are obtaining singificant results that are showing difference between the two values on statistical terms

(23*2)-12=x     x=34

step-by-step explanation: