Activities: Task 1 Load the data: data(Soils) Task: Draw a simple design of the experiment. Identify your variables, Develop a research Title, Research Questions and Hypothesis. Task: Describe the Soils dataset using the following functions where necessary in R Studio str() class() levels() names() head() tail() Notes: Task: The summary() function is convenient. We can describe all of the variables in a data frame using the function on our data frame object. It gives a set of descriptive statistics, depending on the type of variable: . . summary(mydata) We can apply the summary() function to a single variable: In case we just need the summary statistic for a particular variable in the dataset, we can use In case of a Numerical Variable -> Gives Mean, Median, Mode, Range and Quartiles. summary(mydata$VariableName) We can use many functions on subsets of data, using indexing. Which rows are included in the following summary function summary(mydata[1:3,"VariableName"]) Task: Calculate the following Descriptive Statistics in R Studio using the appropriate functions for each quantitative continuous variables and by groups/categories and where applicable applicable for qualitative data • minimum In case of a Factor Variable -> Gives a table with the frequencies. In case of Factor + Numerical Variables -> Gives the number of missing values. In case of character variables -> Gives the length and the class. ● maximum . . mean . ● median mode first quartile third quartile . mode range 2 of 3
Activities: Task 1 Load the data: data(Soils) Task: Draw a simple design of the experiment. Identify your variables, Develop a research Title, Research Questions and Hypothesis. Task: Describe the Soils dataset using the following functions where necessary in R Studio str() class() levels() names() head() tail() Notes: Task: The summary() function is convenient. We can describe all of the variables in a data frame using the function on our data frame object. It gives a set of descriptive statistics, depending on the type of variable: . . summary(mydata) We can apply the summary() function to a single variable: In case we just need the summary statistic for a particular variable in the dataset, we can use In case of a Numerical Variable -> Gives Mean, Median, Mode, Range and Quartiles. summary(mydata$VariableName) We can use many functions on subsets of data, using indexing. Which rows are included in the following summary function summary(mydata[1:3,"VariableName"]) Task: Calculate the following Descriptive Statistics in R Studio using the appropriate functions for each quantitative continuous variables and by groups/categories and where applicable applicable for qualitative data • minimum In case of a Factor Variable -> Gives a table with the frequencies. In case of Factor + Numerical Variables -> Gives the number of missing values. In case of character variables -> Gives the length and the class. ● maximum . . mean . ● median mode first quartile third quartile . mode range 2 of 3
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
Related questions
Question
plz follow the instructions in the 2 doc and plz run it in r studio
plz answer all the questions (in red) .. thank u
uses this link to accesz the soil data
![3:45
BI03211 Worksheet 1- Descriptive Statistics 2022-2
КА
Ку
Activities: Task 1
Load the data:
data(Soils)
Task: Draw a simple design of the experiment. Identify your variables,
Develop a research Title, Research Questions and Hypothesis.
Task: Describe the Soils dataset using the following functions where
necessary in R Studio
str()
class()
levels()
names()
head()
tail()
.
.
Notes:
Task: The summary() function is convenient. We can describe all of the
variables in a data frame using the function on our data frame object. It gives
a set of descriptive statistics, depending on the type of variable:
summary(mydata)
We can apply the summary() function to a single variable: In case we just
need the summary statistic for a particular variable in the dataset, we can use
● maximum
In case of a Numerical Variable -> Gives Mean, Median, Mode, Range
and Quartiles.
In case of a Factor Variable -> Gives a table with the frequencies.
In case of Factor + Numerical Variables -> Gives the number of missing
values.
In case of character variables -> Gives the length and the class.
summary(mydata$VariableName)
We can use many functions on subsets of data, using indexing. Which rows
are included in the following summary function
summary(mydata[1:3,"VariableName"])
Task: Calculate the following Descriptive Statistics in R Studio using the
appropriate functions for each quantitative continuous variables and by
groups/categories and where applicable applicable for qualitative data
minimum
. mean
.
.
median
mode
first quartile
third quartile
0
mode
range
=
|||
00
0:0
2 of 3
O
r
||](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F7ae7799c-b751-4473-bea9-1903e57718a0%2F5686de40-1b1a-4c31-8003-0de8aaad1fb4%2F75zl1j_processed.jpeg&w=3840&q=75)
Transcribed Image Text:3:45
BI03211 Worksheet 1- Descriptive Statistics 2022-2
КА
Ку
Activities: Task 1
Load the data:
data(Soils)
Task: Draw a simple design of the experiment. Identify your variables,
Develop a research Title, Research Questions and Hypothesis.
Task: Describe the Soils dataset using the following functions where
necessary in R Studio
str()
class()
levels()
names()
head()
tail()
.
.
Notes:
Task: The summary() function is convenient. We can describe all of the
variables in a data frame using the function on our data frame object. It gives
a set of descriptive statistics, depending on the type of variable:
summary(mydata)
We can apply the summary() function to a single variable: In case we just
need the summary statistic for a particular variable in the dataset, we can use
● maximum
In case of a Numerical Variable -> Gives Mean, Median, Mode, Range
and Quartiles.
In case of a Factor Variable -> Gives a table with the frequencies.
In case of Factor + Numerical Variables -> Gives the number of missing
values.
In case of character variables -> Gives the length and the class.
summary(mydata$VariableName)
We can use many functions on subsets of data, using indexing. Which rows
are included in the following summary function
summary(mydata[1:3,"VariableName"])
Task: Calculate the following Descriptive Statistics in R Studio using the
appropriate functions for each quantitative continuous variables and by
groups/categories and where applicable applicable for qualitative data
minimum
. mean
.
.
median
mode
first quartile
third quartile
0
mode
range
=
|||
00
0:0
2 of 3
O
r
||
Transcribed Image Text:7:19.
BI03211 Workshee...2022-2023 (1).pdf - Read-only
●
●
mode
●
first quartile
third quartile
mode
range
standard deviation
● variance
interquartile range
● coefficient of variation
Histograms for each data set (by categories/groups/
treatments)
KV
summary()
tapply()
lapply()
Other Useful functions
Task: Also install and load the following
age {pastecs) and use the
function stat.desc() and coef.var to also examine measures within your
datasets.
by()
table()
sort()
go
Using your graph and table tools plot appropriate graphs and summary/
contingency tables (Hisograms/boxplots/bargraphs/Scatter plots/tables) to
help in presenting and describing your results.
00
What are your conclusions for each variable and categories/groups/blocks/
treatments in soil data set.
Produce a report including your R scripts, Results and conclusions in a word
document. Please include: (vour full name and USI and Name Dent
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