We wish to test an effect of a drug that claimed to improves the patients with 90% of chance. The drug is given to 20 patients and we observed the number Y of people who improved. The hypothesis is Ho: p=0.9 vs II: p<0.9. Use the rejection region RR= {y≤17) and answer question a-e. b) State type I error using Y and p. Find a. State type II error using Y and p.
We wish to test an effect of a drug that claimed to improves the patients with 90% of chance. The drug is given to 20 patients and we observed the number Y of people who improved. The hypothesis is Ho: p=0.9 vs II: p<0.9. Use the rejection region RR= {y≤17) and answer question a-e. b) State type I error using Y and p. Find a. State type II error using Y and p.
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a b and c please
![Credit Card Balance Data
A data frame with 400 observations on a number of variables.
• Income: Income in $1,000's
. Limit: Credit limit
. Rating: Credit rating
. Cards: Number of credit cards
Age: Age in years
. Education: Education in years
• Own: A factor with levels No and Yes indicating whether the individual owns a home
. Student: A factor with levels No and Yes indicating whether the individual is a student
• Married: A factor with levels No and Yes indicating whether the individual is married
• Region: A factor with levels East, South, and West indicating the individual's geographical location
Balance: Average credit card balance in $.
library(tidyr)
library (ISLR2)
dat <- drop_na (Credit)
head(dat)
**
Income Limit Rating Cards Age Education Own Student Married Region Balance
##1 14.891 3606 283
2 34
11 No
Yes South
Yes Weat
## 2 106.025 6645
##3 104.593 7075
## 4 148.924 9504
##5 55.882 4897
483
514
681
357
## 6 80.180 8047 569
x1 <- x1[x1>0]
x2 <- x2[x2>0]
x1 <- dat $Balance [dat$Student=="Yes"]
x2 <- dat $Balance [dat$Student=="No"]
Frequency
03
par (nfrow-c (2,1))
hist(x1, main="Student", breaks-30)
hist(x2, main="Non-student", breaks-30)
Frequency
3 82
4 71
3 36
0 15
2 68
4 77
0
Use the following R code separate Balance for Student and Non-student and create histogram of Balance
for Student and Non-student. We wish to compare mean Balance of Student and Non-student group.
podo
0
500
15 Yea
11 No
11 Yes
16 No
10 No
500
Student
X1
No
Yes
No
No
No
No
1000
x2
ubddp.
Non-student
durupp...cm
1000
No West
No
West
Yes South
331
No South 1151
333
903
580
964
1500
1500
2000](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F1b2e65f2-c472-45bf-885c-00dffce84016%2F43f42527-aad6-40b9-8315-b1a32e28aa35%2Foevot46_processed.png&w=3840&q=75)
Transcribed Image Text:Credit Card Balance Data
A data frame with 400 observations on a number of variables.
• Income: Income in $1,000's
. Limit: Credit limit
. Rating: Credit rating
. Cards: Number of credit cards
Age: Age in years
. Education: Education in years
• Own: A factor with levels No and Yes indicating whether the individual owns a home
. Student: A factor with levels No and Yes indicating whether the individual is a student
• Married: A factor with levels No and Yes indicating whether the individual is married
• Region: A factor with levels East, South, and West indicating the individual's geographical location
Balance: Average credit card balance in $.
library(tidyr)
library (ISLR2)
dat <- drop_na (Credit)
head(dat)
**
Income Limit Rating Cards Age Education Own Student Married Region Balance
##1 14.891 3606 283
2 34
11 No
Yes South
Yes Weat
## 2 106.025 6645
##3 104.593 7075
## 4 148.924 9504
##5 55.882 4897
483
514
681
357
## 6 80.180 8047 569
x1 <- x1[x1>0]
x2 <- x2[x2>0]
x1 <- dat $Balance [dat$Student=="Yes"]
x2 <- dat $Balance [dat$Student=="No"]
Frequency
03
par (nfrow-c (2,1))
hist(x1, main="Student", breaks-30)
hist(x2, main="Non-student", breaks-30)
Frequency
3 82
4 71
3 36
0 15
2 68
4 77
0
Use the following R code separate Balance for Student and Non-student and create histogram of Balance
for Student and Non-student. We wish to compare mean Balance of Student and Non-student group.
podo
0
500
15 Yea
11 No
11 Yes
16 No
10 No
500
Student
X1
No
Yes
No
No
No
No
1000
x2
ubddp.
Non-student
durupp...cm
1000
No West
No
West
Yes South
331
No South 1151
333
903
580
964
1500
1500
2000
Transcribed Image Text:We wish to test an effect of a drug that claimed to improves the patients with 90% of chance. The drug is
given to 20 patients and we observed the number Y of people who improved.
The hypothesis is
Ho: p=0.9 vs II: p<0.9.
Use the rejection region RR= {y <17) and answer question a-e.
a)
b)
d)
State type I error using Y and p.
Find a.
State type II error using Y and p.
Find the rejection region {y <c) with a 0.01.
For the rejection region in e), find ß
B
when p=0.6.
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