Data analysis

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Instructions are in the attached file.

Link to Statistics Interactives:

[login to view URL] (Links to an external site.)Links to an external site.

Code for Data Analysis:

In addition to the provided code I recommend the following for Part 4:

R for Basic Summary Statistics and Visual Displays

R for t procedures for Means

R Video Tutorial for a t test (Links to an external site.)Links to an external site.

In R go to File< New Script (New Document on MAC) – A new script window will pop up. You should write all of your code in a script window and not directly in the console.

The R code can be uploaded directly into R by copying and pasting everything below R Code DA3.

Note: Any time you see # this means that R will not read what follows. I will use this to make comments about the following command.

R Code DA3

# R code and explanation for part 4 DA#3.

# Read in the [login to view URL] file.

lensdata = [login to view URL]([login to view URL](), header = TRUE)

# Look at the lensdata dataset. Look for the variable names.

head(lensdata) # gives first 6 rows of the data and variable names.

names(lensdata) # gives variable names.

# Make an appropriate visual display for lens thickness.

# Recall hist() or boxplot()

# Add a title.

# Add color and other aesthetics if you like.

# See week 3 lessons.

# Calculate the mean and standard deviation. mean() and sd()

# Perform a t test using the [login to view URL]() command.

# The format is [login to view URL](data, mu = mu_0, alternative = "alt")

# where data is a quantitative variable mu_0 is the hypothesized mean,

# and alt is either less, greater or not equal (default).

# Code for Part 5. For your Information.

# You don't have to run this section.

# Upload student data set

st314data = [login to view URL]([login to view URL](), header = TRUE)

# creates a side by side boxplot with customized axes.

boxplot(st314data$GamingHours ~st314data$International,

col = c("lightgreen", "dodgerblue"),

axes = FALSE, horizontal = TRUE,

main = "Comparison of Gaming Hours between

International and US ST314 Students", xlab = "Hours per Week")

axis(2, at = c(1,2), c("International", "US"))

axis(1, at = seq(0,90,5))

# Calculate means, sd and sample size by group

aggregate(st314data$GamingHours~st314data$International, data = st314data, mean)

aggregate(st314data$GamingHours~st314data$International, data = st314data, sd)

aggregate(st314data$GamingHours~st314data$International, data = st314data, length)

# two sample t test

[login to view URL](st314data$GamingHours~st314data$International)

Excel Python R 编程语言 统计分析 统计学

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