Calculate Type II error probability

7 A ten-sided spinner has edges numbered \(1,2,3,4,5,6,7,8,9,10\). Sanjeev claims that the spinner is biased so that it lands on the 10 more often than it would if it were unbiased. In an experiment, the spinner landed on the 10 in 3 out of 9 spins.

1. Test at the \(1 \%\) significance level whether Sanjeev's claim is justified.
2. Explain why a Type I error cannot have been made.
   In fact the spinner is biased so that the probability that it will land on the 10 on any spin is 0.5 .
3. Another test at the \(1 \%\) significance level, also based on 9 spins, is carried out. Calculate the probability of a Type II error.
   If you use the following lined page to complete the answer(s) to any question(s), the question number(s) must be clearly shown.

8 The four sides of a spinner are \(A , B , C , D\). The spinner is supposed to be fair, but Sonam suspects that the spinner is biased so that the probability, \(p\), that it will land on side \(A\) is greater than \(\frac { 1 } { 4 }\). He spins the spinner 10 times and finds that it lands on side \(A 6\) times.

1. Test Sonam's suspicion using a \(1 \%\) significance level.
   Later Sonam carries out a similar test at the \(1 \%\) significance level, using another 10 spins of the spinner.
2. Calculate the probability of a Type I error.
3. Assuming that the value of \(p\) is actually \(\frac { 3 } { 5 }\), calculate the probability of a Type II error.
   If you use the following lined page to complete the answer(s) to any question(s), the question number(s) must be clearly shown.

6 A biscuit manufacturer claims that, on average, 1 in 3 packets of biscuits contain a prize offer. Gerry suspects that the proportion of packets containing the prize offer is less than 1 in 3 . In order to test the manufacturer's claim, he buys 20 randomly selected packets. He finds that exactly 2 of these packets contain the prize offer.

1. Carry out the test at the \(10 \%\) significance level.
2. Maria also suspects that the proportion of packets containing the prize offer is less than 1 in 3 . She also carries out a significance test at the \(10 \%\) level using 20 randomly selected packets. She will reject the manufacturer's claim if she finds that there are 3 or fewer packets containing the prize offer. Find the probability of a Type II error in Maria's test if the proportion of packets containing the prize offer is actually 1 in 7 .
3. Explain what is meant by a Type II error in this context.

4 It is not known whether a certain coin is fair or biased. In order to perform a hypothesis test, Raj tosses the coin 10 times and counts the number of heads obtained. The probability of obtaining a head on any throw is denoted by \(p\).

1. The null hypothesis is \(p = 0.5\). Find the acceptance region for the test, given that the probability of a Type I error is to be at most 0.1 .
2. Calculate the probability of a Type II error in this test if the actual value of \(p\) is 0.7 .

8 The proportion of left-handed adults in a country is known to be \(15 \%\). It is suggested that for mathematicians the proportion is greater than \(15 \%\). A random sample of 12 members of a university mathematics department is taken, and it is found to include five who are left-handed.

1. Stating your hypotheses, test whether the suggestion is justified, using a significance level as close to \(5 \%\) as possible.
2. In fact the significance test cannot be carried out at a significance level of exactly \(5 \%\). State the probability of making a Type I error in the test.
3. Find the probability of making a Type II error in the test for the case when the proportion of mathematicians who are left-handed is actually \(20 \%\).
4. Determine, as accurately as the tables of cumulative binomial probabilities allow, the actual proportion of mathematicians who are left-handed for which the probability of making a Type II error in the test is 0.01 .

8 The random variable \(R\) has the distribution \(\mathrm { B } ( 14 , p )\). A test is carried out at the \(\alpha \%\) significance level of the null hypothesis \(\mathrm { H } _ { 0 } : p = 0.25\), against \(\mathrm { H } _ { 1 } : p > 0.25\).

1. Given that \(\alpha\) is as close to 5 as possible, find the probability of a Type II error when the true value of \(p\) is 0.4 .
2. State what happens to the probability of a Type II error as
   1. \(p\) increases from 0.4,
   2. \(\alpha\) increases, giving a reason.

4. A proportion \(p\) of letters sent by a company are incorrectly addressed and if \(p\) is thought to be greater than 0.05 then action is taken.
Using \(\mathrm { H } _ { 0 } : p = 0.05\) and \(\mathrm { H } _ { 1 } : p > 0.05\), a manager from the company takes a random sample of 40 letters and rejects \(\mathrm { H } _ { 0 }\) if the number of incorrectly addressed letters is more than 3 .

1. Find the size of this test.
2. Find the probability of a Type II error in the case where \(p\) is in fact 0.10 Table 1 below gives some values, to 2 decimal places, of the power function of this test. \begin{table}[h]

   \(p\)	0.075	0.100	0.125	0.150	0.175	0.200	0.225
   Power	0.35	\(s\)	0.75	0.87	0.94	0.97	0.99

   \captionsetup{labelformat=empty} \caption{Table 1}
   \end{table}
3. Write down the value of \(s\). A visiting consultant uses an alternative system to test the same hypotheses. A sample of 15 letters is taken. If these are all correctly addressed then \(\mathrm { H } _ { 0 }\) is accepted. If 2 or more are found to have been incorrectly addressed then \(\mathrm { H } _ { 0 }\) is rejected. If only one is found to be incorrectly addressed then a further random sample of 15 is taken and \(\mathrm { H } _ { 0 }\) is rejected if 2 or more are found to have been incorrectly addressed in this second sample, otherwise \(\mathrm { H } _ { 0 }\) is accepted.
4. Find the size of the test used by the consultant. \section*{Question 4 continues on page 8} For your convenience Table 1 is repeated here \begin{table}[h]

   \(p\)	0.075	0.100	0.125	0.150	0.175	0.200	0.225
   Power	0.35	\(s\)	0.75	0.87	0.94	0.97	0.99

   \captionsetup{labelformat=empty} \caption{Table 1}
   \end{table} Figure 1 shows the graph of the power function of the test used by the consultant. \begin{figure}[h]
   \includegraphics[alt={},max width=\textwidth]{8dfc721d-4782-4482-9976-11189370f3b7-07_1712_1673_660_130} \captionsetup{labelformat=empty} \caption{Figure 1}
   \end{figure}
5. On Figure 1 draw the graph of the power function of the manager's test.
   (2)
6. State, giving your reasons, which test you would recommend.
   (2)

Jeevan thinks that a six-sided die is biased in favour of six. In order to test this, Jeevan throws the die 10 times. If the die shows a six on at least 4 throws out of 10, she will conclude that she is correct.

1. State appropriate null and alternative hypotheses. [1]
2. Calculate the probability of a Type I error. [3]
3. Explain what is meant by a Type II error in this situation. [1]
4. If the die is actually biased so that the probability of throwing a six is \(\frac{1}{3}\), calculate the probability of a Type II error. [3]

A proportion \(p\) of letters sent by a company are incorrectly addressed and if \(p\) is thought to be greater than 0.05 then action is taken. Using H\(_0\): \(p = 0.05\) and H\(_1\): \(p > 0.05\), a manager from the company takes a random sample of 40 letters and rejects H\(_0\) if the number of incorrectly addressed letters is more than 3.

1. Find the size of this test. [2]
2. Find the probability of a Type II error in the case where \(p\) is in fact 0.10 [2]

Table 1 below gives some values, to 2 decimal places, of the power function of this test.

\(p\)	0.075	0.100	0.125	0.150	0.175	0.200	0.225
Power	0.35	\(s\)	0.75	0.87	0.94	0.97	0.99

Table 1

1. Write down the value of \(s\). [1]

A visiting consultant uses an alternative system to test the same hypotheses. A sample of 15 letters is taken. If these are all correctly addressed then H\(_0\) is accepted. If 2 or more are found to have been incorrectly addressed then H\(_0\) is rejected. If only one is found to be incorrectly addressed then a further random sample of 15 is taken and H\(_0\) is rejected if 2 or more are found to have been incorrectly addressed in this second sample, otherwise H\(_0\) is accepted.

1. Find the size of the test used by the consultant. [3]

Question 4 continues on page 8 \includegraphics{figure_1}

1. On Figure 1 draw the graph of the power function of the manager's test. [2]
2. State, giving your reasons, which test you would recommend. [2]

Dewi, a candidate in an election, believes that 45% of the electorate intend to vote for him. His agent, however, believes that the support for him is less than this. Given that \(p\) denotes the proportion of the electorate intending to vote for Dewi,

1. state hypotheses to be used to resolve this difference of opinion. [1]

They decide to question a random sample of 60 electors. They define the critical region to be \(X \leq 20\), where \(X\) denotes the number in the sample intending to vote for Dewi.

1. 1. Determine the significance level of this critical region.
   2. If in fact \(p\) is actually 0.35, calculate the probability of a Type II error.
   3. Explain in context the meaning of a Type II error.
   4. Explain briefly why this test is unsatisfactory. How could it be improved while keeping approximately the same significance level? [8]