Question

1) Give an example of a type I error.

2. Give an example of a type II error.

3. What type of t-test would you use when the same group is tested twice at different time points?

Answer #1

**Solution :**

1. Type I error is the "False Positive" error. For example, when a defendant is not guilty, but was declared guilty by the jury or judges. The probability of this error is denoted by Alpha.

2. Type II error is the “False Negative" error. Building on the
above example, a defendant is guilty, but was declared as innocent
by the jury or judges. The probability of this error is denoted by
Beta.

.

3. A Paired sample t-test compares means from the same group at
different times (say, one year apart).

So, a paired sample t-test should be used.

**Let me know in the comment section if anything is not
clear. I will reply ASAP!
If you liked the answer, please give an upvote. This will be quite
encouraging for me.Thank-you!**

1. Provide a real world example of a Type I error. 2. Explain
what a critical value is, and explain how it is used to test a
hypothesis. 3. Explain what a p-value is, and explain how it is
used to test a hypothesis. 4. How do we decide whether to use a z
test or a t test when testing a hypothesis about a population
mean?

Provide a real world example of a Type I error.
2. Explain what a critical value is, and explain how
it is used to test a hypothesis.
3. Explain what a p-value is, and explain how it is
used to test a hypothesis.
4. How do we decide whether to use a z test or a t
test when testing a hypothesis about a population mean?

1. When would you use an Independent t-test? Give an example
of the type of research question.

Which of the following statements is true?
1.Type I error refers to β, or the probability that we conclude
treatments are not different from each other when in reality the
treatments are different from each other
2.Type II error refers to α, or the probability that we conclude
the treatments are different from each other when in reality the
treatments are not different.
3.Type II error refers to β, or the probability that we conclude
treatments are not different from...

(1 point)
Type I error is:
A. Deciding the null hypothesis is true when it is
false
B. Deciding the alternative hypothesis is true
when it is false
C. Deciding the null hypothesis is false when it
is true
D. Deciding the alternative hypothesis is true
when it is true
E. All of the above
F. None of the above
Type II error is:
A. Deciding the null hypothesis is false when
it is true
B. Deciding the alternative hypothesis...

Question 1 : The answers listed below are characteristics of a
Type I error EXCEPT for one. Select the characteristic that is not
for Type I error
a) upsetting status quo for falsehood
b) a 'missed opportunity'
c) reject null hypothesis with null is true
question 2: The answers listed below are characteristics of a
Type II error EXCEPT for one. Select the characteristic that is not
for Type II error
a) do not reject null hypothesis when it is...

What is the difference between Type 1 and Type II error? How is
Type I error related to α? How is Type II error related to
power?

For the given significance test, explain the meaning of a Type I
error, a Type II error, or a correct decision as specified. A
health insurer has determined that the "reasonable and customary"
fee for a certain medical procedure is $1200. They suspect that the
average fee charged by one particular clinic for this procedure is
higher than $1200. The insurer performs a significance test to
determine whether their suspicion is correct using α = 0.05. The
hypotheses are:
H0:...

Consider the following statements.
(i) If a hypothesis is tested at the 5% significance level with
a given data set, then there is a lower chance that the null
hypothesis will be rejected than if that same hypothesis is tested
at the 1% significance level with the same data set.
(ii) P(Type I Error) + P(Type II Error) =
1.
(iii) If a hypothesis test is performed at the 5% significance
level, and if the alternative hypothesis is actually true,...

Typically, when we decrease the probability of a type I error
for a hypothesis test, we:
decrease the probability of a type II error
increase the probability of a type II error

ADVERTISEMENT

Get Answers For Free

Most questions answered within 1 hours.

ADVERTISEMENT

asked 2 minutes ago

asked 27 minutes ago

asked 40 minutes ago

asked 1 hour ago

asked 1 hour ago

asked 1 hour ago

asked 2 hours ago

asked 2 hours ago

asked 2 hours ago

asked 2 hours ago

asked 2 hours ago

asked 2 hours ago