Can we use GoogleEarth Pro application to map forest areas?

I am a Ph.D nursing student. I am analyzing my data, 845 samples for normality test. I found that my dependent variable and independent variables are not normal distribution. According to central limit theorem, can I ignore assumption of normality for that sample, 845? Most of statistical books say, "large enough sample" but they do not mention how much sample is called large enough sample. Some books say, greater than equal above 30 sample can violate the normality according to Central Limit Theorem.

I plan to analyze the data using SEM, regression analysis. I would like to know please can I analyze the data using SEM even the data is not normal? May I get your suggestions. Thank you so much.

Dear research gate team,

My scientific Ph.D. work on acoustic retrofit in multistorey residential buildings against outdoor noise (road traffic noise in particular) has come to a deadend, due to financial reasons to purchase an acoustic simulation software, therefore, i am cornered and running out of time for my final thesis presentation at the end of this year.

I seek help in this prestigious platform, hoping to find somebody who is of course time-available and willing to help me throughout this difficult period, to produce a simple noise map for the case study i am investigating, using SoundPlan (essential or noise) software.

The attached files present an example of the needed noise maps.

Thank you.

Dear everyone,

When I using the rda function in r, I met this question. As you can see in the figure, there are a lot of deep blue points which refers to the species. But I would like remain only the sites point (samples). ggord is used because the 95% confidence interval circle for grouping is needed.

The R script is below:

library("devtools")

library("vegan")

library(ggord)

asv_vir=read.table("...")

env_log10=read.table("...")

asv1_vir <- decostand(t(asv_vir), "hellinger")

asv_vir.rda.f <- rda(asv1_vir ~., env_log10)

group=factor(c(rep('BS','12'),rep('AS','9')))

ggord(asv_vir.rda.f, grp_in=group,repel=TRUE, vec_ext=0.7, cols=c('red','cyan'), arrow=0.3,size=3, obslab=FALSE,ellipse = TRUE, hull = TRUE)+ theme_classic()

The species data I think will be asv_vir.rda.f$CCA$v.

Please feel free to have any discussions and suggestions!

Thank you for your time.

Many organization told that 4 samples, another 08 samples.....like that every agency have their on number during soil testing. My question is that Ideally, how many soil samples should take from one hectare during soil testing.

We know the generalized linear models (GLMs) are a broad class of models. When fitting GLMs in R, we need to specify which family function to use from a bunch of options like gaussian, poisson, binomial, quasi, etc. I would like to have your advice regarding how to determine the optional family function used for GLM fitting in R. Thanks!

I am writing a manuscript in MS Word 2016 and I am managing references with Mendeley plugin. I would like my in text citations to be highlighted with a different colour (e.g. blue) but I do not want to do it manually one by one. Is there a way to set this up automatically for every citation in the text?

R is usually said to be the single-threaded software by default. Therefore, one sometimes needs too much time to run some heavy codes. However, there are some packages available in R which allow to run on a multiple thread on the CPU. My question is how to utilize multiple cores in a machine? I would be appreciated if anyone can share his or her experience with the multi-core computations using R.