[R] data analysis. R

Sun Mar 22 05:27:51 CET 2009

thx for ur fast responds.
but sorry for asking stupid, i am a turn beginner of R (just trying it out
<3 months, and i am taking my first course about it)
so, to tackle this questions,
i was told to use "nested design", "blocking"....method, does this terms
sounds familiar to you?
could you actually show me how would u attempt this problem?
(a) Determine if insulation in the house effects the average gas
consumption.
(b) How much extra gas is used when there is no insulation? Provide an
interval estimate as well as a point estimate.

i just got confused by the backgroud information.
"We are interested in looking at the effect of insulation on gas
consumption. The average outside temperature (degrees celcius) was also
measured."

so how should my model looks like?
i dont even know what should be my explanatory/response variables...

thx in advance

Gabor Grothendieck wrote:
> 
> This works with the example.  If the real data is different it may not
> work.  To run the example below just copy and paste it into R.
> To run with the real data replace textConnection(Lines) with
> "insulation.txt" everywhere.
> 
> Lines <- "Before insul    After insul.
> temp    gas     temp    gas
> -0.8    7.2    -0.7    4.8
> -0.7    6.9    0.8    4.6
> 0.4    6.4    1.0    4.7
> 2.5    6.0    1.4    4.0
> 2.9    5.8    1.5    4.2
> 3.2    5.8    1.6    4.2
> 3.6    5.6    2.3    4.1
> 3.9    4.7    2.5    4.0
> 4.2    5.8    2.5    3.5
> 4.3    5.2    3.1    3.2
> 5.4    4.9    3.9    3.9
> 6.0    4.9    4.0    3.5
> 6.0    4.3    4.0    3.7
> 6.0    4.4    4.2    3.5
> 6.2    4.5    4.3    3.5
> 6.3    4.6    4.6    3.7
> 6.9    3.7    4.7    3.5
> 7.0    3.9    4.9    3.4
> 7.4    4.2    4.9    3.7
> 7.5    4.0    4.9    4.0
> 7.5    3.9    5.0    3.6
> 7.6    3.5    5.3    3.7
> 8.0    4.0    6.2    2.8
> 8.5    3.6    7.1    3.0
> 9.1    3.1    7.2    2.8
> 10.2  2.6    7.5    2.6
>                8.0    2.7
>                8.7    2.8
>                8.8    1.3
>                9.7    1.5"
> 
> nfld <- count.fields(textConnection(Lines))
> data.lines <- readLines(textConnection(Lines))
> data.lines <- ifelse(nfld == 2, paste("NA NA", data.lines), data.lines)
> my.data <- read.table(textConnection(data.lines), header = TRUE, skip = 1)
> 
> 
> 
> 
> On Sat, Mar 21, 2009 at 8:13 PM, UBC <cheong0618 at hotmail.com> wrote:
>>
>> so i am having this question
>> what should i do if the give data file (.txt) has 4 columns, but
>> different
>> lengths?
>> how can i read them in R?
>> any idea for the following problem?
>>
>>
>> Gas consumption (1000 cubic feet) was measured before and after
>> insulation
>> was put into
>> a house. We are interested in looking at the effect of insulation on gas
>> consumption. The
>> average outside temperature (degrees celcius) was also measured. The data
>> are included in
>> the file "insulation.txt".
>>
>> (a) Determine if insulation in the house effects the average gas
>> consumption.
>> (b) How much extra gas is used when there is no insulation? Provide an
>> interval estimate
>> as well as a point estimate.
>>
>> heres the content in "insulation.txt"  (u can just copy and paste it to
>> the
>> notepad so can be read in R)
>>
>> Before insul    After insul.
>> temp    gas     temp    gas
>> -0.8    7.2    -0.7    4.8
>> -0.7    6.9    0.8    4.6
>> 0.4    6.4    1.0    4.7
>> 2.5    6.0    1.4    4.0
>> 2.9    5.8    1.5    4.2
>> 3.2    5.8    1.6    4.2
>> 3.6    5.6    2.3    4.1
>> 3.9    4.7    2.5    4.0
>> 4.2    5.8    2.5    3.5
>> 4.3    5.2    3.1    3.2
>> 5.4    4.9    3.9    3.9
>> 6.0    4.9    4.0    3.5
>> 6.0    4.3    4.0    3.7
>> 6.0    4.4    4.2    3.5
>> 6.2    4.5    4.3    3.5
>> 6.3    4.6    4.6    3.7
>> 6.9    3.7    4.7    3.5
>> 7.0    3.9    4.9    3.4
>> 7.4    4.2    4.9    3.7
>> 7.5    4.0    4.9    4.0
>> 7.5    3.9    5.0    3.6
>> 7.6    3.5    5.3    3.7
>> 8.0    4.0    6.2    2.8
>> 8.5    3.6    7.1    3.0
>> 9.1    3.1    7.2    2.8
>> 10.2  2.6    7.5    2.6
>>                8.0    2.7
>>                8.7    2.8
>>                8.8    1.3
>>                9.7    1.5
>>
>>
>>
>> thx and any ideas would help.
>> --
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>> http://www.nabble.com/data-analysis.-R-tp22641912p22641912.html
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>>
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>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
> 
> 

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