a)
> x<-
c(10,24,19,27,10,23,18,27,24,15,25,25,17,10,10,14,13,22,25,23,22,20,18,14,21,12,20,23,12,25,22)
> n<-length(x) # size of variable
> n
[1] 31
>
> M <- mean(x) # mean of x
> M
[1] 19.03226
>
> S <- sqrt(var(x)) # std dev of x
> S
[1] 5.576641
>
> alpha = 0.13 # level of significance( 87% confidence
interval)
> z <-qnorm(1-(0.13/2)) # z score for l.o.s.
> z
[1] 1.514102
>
> se= S / sqrt(n) # standard error
> se
[1] 1.001594
>
> ME <- z*se # Margin of Error
> ME
[1] 1.516516
>
>
> left <- M-ME # Lower confidene limit
> right <- M+ ME # upper confidence limit
>
> CI <- c( left,right)
> CI
[1] 17.51574 20.54877
b)
we are 87 % confident that the mean quality of studies on the treatment on Alzheimer's disease is somewhere between 17.52 and 20.55.
c) a lower confidence level is that you get a narrower, more precise confidence interval.
Answer:- The confidence interval would become narrower.
d)
> library(mosaic)
> RNGkind(sample.kind = "Rejection");
> set.seed(33507);
> B =do(1000)*mean(resample(x,31));
>
>
> a=B[,1] # subsetting to a vector
>
> n<-length(a) # size of variable
> n
[1] 1000
>
> M <- mean(a) # mean of x
> M
[1] 19.04826
>
> S <- sqrt(var(a)) # std dev of x
> S
[1] 1.026724
> se= S / sqrt(n) # standard error
> se
[1] 0.03246785
>
> ME <- z*se # Margin of Error
> ME
[1] 0.04915963
>
>
> left <- M-ME # Lower confidene limit
> right <- M+ ME # upper confidence limit
>
> CI2 <- c( left,right)
> CI2
[1] 18.99910 19.09742
>
19 <= u <= 19.10
***************** only code***************
x<-
c(10,24,19,27,10,23,18,27,24,15,25,25,17,10,10,14,13,22,25,23,22,20,18,14,21,12,20,23,12,25,22)
n<-length(x) # size of variable
n
M <- mean(x) # mean of x
M
S <- sqrt(var(x)) # std dev of x
S
alpha = 0.13 # level of significance( 87% confidence
interval)
z <-qnorm(1-(0.13/2)) # z score for l.o.s.
z
se= S / sqrt(n) # standard error
se
ME <- z*se # Margin of Error
ME
left <- M-ME # Lower confidene limit
right <- M+ ME # upper confidence limit
CI <- c( left,right)
CI
library(mosaic)
RNGkind(sample.kind = "Rejection");
set.seed(33507);
B =do(1000)*mean(resample(x,31));
a=B[,1] # subsetting to a vector
n<-length(a) # size of variable
n
M <- mean(a) # mean of x
M
S <- sqrt(var(a)) # std dev of x
S
se= S / sqrt(n) # standard error
se
ME <- z*se # Margin of Error
ME
left <- M-ME # Lower confidene limit
right <- M+ ME # upper confidence limit
CI2 <- c( left,right)
CI2
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13
22
35
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ethnography
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Group of answer choices
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Group of answer choices
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qualitative study
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Group of answer choices
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phenomenology
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Group of answer choices
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Group of answer choices
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