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# We Helped With This R Programming Homework: Have A Similar One?

SOLVED

Category | Programming |
---|---|

Subject | R | R Studio |

Difficulty | Undergraduate |

Status | Solved |

More Info | Statistic Homework Answers |

## Short Assignment Requirements

Hey, I need this hw in 24 hours.I am a business major.So,it is not going to be in engineer level hw.

## Assignment Image

..ooo Turkcell ?
12:50
ieu.blackboard.com
Assignment 2 - Exploratory.
Analytics
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For this assignment you may use the data set
from the previous assignment or choose a new
one. In doing all of the following operations,
record the R commands as an R notebook and
submit the ".Rmd" file along with the data set file.
1. Explore a single variable: Exploratory
analysis of a single variable answers the
question "how is the distribution of this
variable?". Choose a variable from your
data set and draw its histogram,
preferably using ggplot2 library.
2. Many statistical methods rely on the
assumption that a variable is normally
distributed. Use the shapiro.test function
to test normality of the variable you have
visualized in question 1. If you want you
can check out an example at
https://www.sheffield.ac.uk/polopoly_fs/1.5
karadimitriou-normalR.pdf
3. Explore two variables: This exploratory
analysis answers the question "how the
two variables are correlated?" Choose two
variables from the data set, one of which
is the variable you have used in questions
1&2. Draw a plot of the two variables.
Then comment on the relation between
the two variables, I.e do you think the two
are strongly correlated? Positively or
negatively correlated?
D

## Assignment Image

..ooo Turkcell ?
12:50
ieu.blackboard.com
%92
4. Explore three variables: This analysis aims
to analyse the question "how does the
relation of variables A and B are regulated
by the third variable C?". An example is the
Diet variable regulating the relation
between Weight and Time variables in the
ChickWeight dataset. Choose a third
variable from your data set and produce a
visualization (e.g. 'facet' in ggplot2) that
exposes the interaction of three variables.
The third variable should be a rank or
categorical variable. If there's no such
variable in your data set then you may
need to produce one, e.g. by assigning
categories to ranges. For example if the
third variable is "age" (not categorical), you
can produce a new variable "age.range"
which has string values such as "18-25",
"25-35", etc.
5. Comme on the regulatory effect of the
third variable in question 4. For example
do you think all or some categories have a
more clear/strong correlation than what
you have seen in the drawing for question
3?
6. Think of a business question that can be
posed onto your data set of choice.
Comment (but not conduct) the
exploratory analysis necessary to answer
the question. Which variables and which
relations should be explored?
D