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Below is a result from a factorial experiment on the effect of fertilizer types  A and B, watering amount  low, medium, and high, and watering frequency  low and high  on growth of a particular plant. The outcome is measured in the total growth in heights after 4 weeks.
a) (5 points) Using the deviation coding, create a model matrix for the first 12 rows of the data. Include the intercept column and all interaction terms.

Hey there, I need help from an R programming homework solver on which R function can be used to get the descriptive statistics of a dataset. What I want is to get the descriptive statistics of each column in the dataset. Descriptive statistics that I need are the measures of central tendency and the maximum and minimum.I would appreciate it if a Statistics homework help expert would lend a hand.

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I am a statistics student. In our class we always fit a regression model to a dataset. Our lecture encourages us to use the R for such assignments. But there are things that I do not know their importance on the resulting regression table that I need you and R programming homework solve to help me with. What is the use of the adjusted Rsquared? I would really appreciate help from a Statistics homework help expert

I need Statistics homework help in a R programming homework solver to help me understand what is in the code. I found it on a website explaining how to plot the frequency of the missing values. On my side, it's hard to understand what the code does. Can you explain to me step by step what is happening in the code below?
getting table with missing values
df < read.table("https://archive.ics.uci.edu/ml/machinelearningdatabases/horsecolic/horsecolic.data")
df < data.frame(apply(df, 2, function(x) { ifelse(x=='?', NA, x)} ))add thresholding to function
missing_percentages < function(frame, color, cutoff_condition) {
res < apply(frame,2,pMiss)
par(mar=c(2,3,5,2))
mp < barplot(res, main='missing data by percentage\n', ylab='percentage missing (%)', col=ifelse(res >= cutoff_condition, color,'steelblue'), xaxt='n')
text(mp, par("usr")[3], labels = names(res), srt = 45, adj = c(1.1,1.1), xpd = TRUE, cex=.7)
}

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