A) The critical value at α = 0.05 will be 1.645 since the critical value does not fall within the rejection region we reject the null hypothesis
B) A type II error occurs when we fail to reject the null hypothesis and a type II error is also known as an error of omission and the consequence of this type of error is that a false negative result is produced.
Given data :
Amount paid for upgrade = $100
Percentage of customers needed = 25% = 0.25
Sample size ( n ) = 72
Number willing to pay $100 = 19
significance level ( α ) = 0.05
A) Prove that 25% of the company's customers are willing to purchase the upgrade
Null hypothesis ( H0 ) : p = 0.25
Alternate hypothesis ( H₁ ) : p > 0.25
α = 0.05
Ρ = 19 / 72 = 0.26
To determine the hypothesis to reject or accept
perform Test statistic : Z = [tex]\frac{P - p }{\sqrt{\frac{p(1-p)}{n} } }[/tex]
= ( 0.26 - 0.25 ) / [tex]\sqrt{0.25 * 0.75} / 72[/tex]
= 0.01 / 0.0026
Z- score = 0.499
The critical value at α = 0.05 will be 1.645 since the critical value does not fall within the rejection region we reject the null hypothesis
B) A type II error occurs when we fail to reject the null hypothesis and a type II error is also known as an error of omission and the consequence of this type of error is that a false negative result is produced.
Learn more about Type II error : https://brainly.com/question/7278657?section=related_q
