Categories
R

In this quiz, we will evaluate different charts for Univariate, single feature.

In this quiz, we will evaluate different charts for Univariate, single feature.
1. Apply all code on the dataset you selected from last week (through those in the discussion board)
2. Complete, similar to the sample attached, all the codes in chapter 3 from the attached book.
(the attached includes only a sample), complete 5 different charts minimum
3. Submit both your R script code and also report file showing the results from all Rstudio GUIs
4. Make sure to include all 4 Rstudio screens
NOTE: Below are the attachments for your reference, & also below is the attached previous weeks work.

Categories
R

Provide in the plain text R commands (or software of your choice) that finds/sol

Provide in the plain text R commands (or software of your choice) that finds/solves the following: A study investigates the distribution of annual income for heads of households living in public housing in Chicago. For a random sample of size 30, the annual incomes (in thousands of dollars) are in the Chicago data file.
Based on a descriptive graphic, describe the shape of the sample data distribution. Find and interpret point estimates of the population mean and standard deviation.
Construct a 95% confidence interval for μ, using R software (or software of your choice). 2.The Anorexia data file contains results for the cognitive behavioral and family therapies and the control group. Using data for the 17 girls who received the family therapy: Conduct a descriptive statistical analysis using graphs and numerical summaries. Construct a 95% confidence interval for the difference between the population mean weight changes for the family therapy and the control. Datasets needed are at Index of Datasets
Useful functions in R to solve problems in this assignment: read.table, hist, t.test

Categories
R

Use R You are a data Scientist working for a sports team. You want to assess the

Use R
You are a data Scientist working for a sports team. You want to assess the improvement (or not) of 10 players’ running speed.You have been supplied with two vectors of data: Speed of players before doing a certain practice, and their speed after it.
Your task is to calculate the following metrics:
 Improvement for each player
 Improved players – the number of the players that improved
 Unimproved players – the number of the players that did not improved
 Best improver – The player whose speed increased the most
 Least improver – The player whose speed decreased the most
The file with the vectors is available on week 2 in blackboard.#Data
SpeedAfter <- c(145, 76, 86, 91, 80, 81, 114, 97, 103, 143 )
SpeedBefore <- c(120, 56, 123, 120, 86, 64, 32, 58, 69, 166 )

Categories
R

Provide in the plain text R commands (or software of your choice) that finds/sol

Provide in the plain text R commands (or software of your choice) that finds/solves the following:
A study investigates the distribution of annual income for heads of households living in public housing in Chicago. For a random sample of size 30, the annual incomes (in thousands of dollars) are in the Chicago data file.
Based on a descriptive graphic, describe the shape of the sample data distribution. Find and interpret point estimates of the population mean and standard deviation.
Construct a 95% confidence interval for μ, using R software (or software of your choice).
2.The Anorexia data file contains results for the cognitive behavioral and family therapies and the control group. Using data for the 17 girls who received the family therapy:
Conduct a descriptive statistical analysis using graphs and numerical summaries.
Construct a 95% confidence interval for the difference between the population mean weight changes for the family therapy and the control.
Datasets needed are at Index of Datasets
Useful functions in R to solve problems in this assignment: read.table, hist, t.test

Categories
R

You are a data Scientist working for a sports team. You want to assess the impro

You are a data Scientist working for a sports team. You want to assess the improvement (or not) of 10 players’ running speed.You have been supplied with two vectors of data: Speed of players before doing a certain practice, and their speed after it.
Your task is to calculate the following metrics:
 Improvement for each player
 Improved players – the number of the players that improved
 Unimproved players – the number of the players that did not improved
 Best improver – The player whose speed increased the most
 Least improver – The player whose speed decreased the most
The file with the vectors is available on week 2 in blackboard.#Data
SpeedAfter <- c(145, 76, 86, 91, 80, 81, 114, 97, 103, 143 )
SpeedBefore <- c(120, 56, 123, 120, 86, 64, 32, 58, 69, 166 )

Categories
R

Use R You are a data Scientist working for a sports team. You want to assess the

Use R
You are a data Scientist working for a sports team. You want to assess the improvement (or not) of 10 players’ running speed.You have been supplied with two vectors of data: Speed of players before doing a certain practice, and their speed after it. Your task is to calculate the following metrics:
 Improvement for each player
 Improved players – the number of the players that improved
 Unimproved players – the number of the players that did not improved
 Best improver – The player whose speed increased the most
 Least improver – The player whose speed decreased the most
The file with the vectors is available on week 2 in blackboard.#Data
SpeedAfter <- c(145, 76, 86, 91, 80, 81, 114, 97, 103, 143 )
SpeedBefore <- c(120, 56, 123, 120, 86, 64, 32, 58, 69, 166 )

Categories
R

You are a data Scientist working for a sports team. You want to assess the impro

You are a data Scientist working for a sports team. You want to assess the improvement (or not) of 10 players’ running speed.You have been supplied with two vectors of data: Speed of players before doing a certain practice, and their speed after it. Your task is to calculate the following metrics:
 Improvement for each player
 Improved players – the number of the players that improved
 Unimproved players – the number of the players that did not improved
 Best improver – The player whose speed increased the most
 Least improver – The player whose speed decreased the most
The file with the vectors is available on week 2 in blackboard.#Data
SpeedAfter <- c(145, 76, 86, 91, 80, 81, 114, 97, 103, 143 )
SpeedBefore <- c(120, 56, 123, 120, 86, 64, 32, 58, 69, 166 )

Categories
R

We will be using data visualization within a tool for this course. Please downlo

We will be using data visualization within a tool for this course. Please download and install R (CRAN) onto your PC.
There are two items that must be downloaded for this course: R and RStudio. Required!
If you are using a computer with a Windows operating system, make sure that when you download base R, you download Rtools, as well.
Verify this by attaching ONLY the screenshots to display your completion of the R software installation. Also, note (in one short paragraph- that is at least three sentences in length) how the installation went and if you encountered any issues. If you did, how were they solved?
Once you complete installation, make your own report to repeat code attached. Make sure to create your own screen shots and report.
Every screenshot in the report should show all 4 Rstudio screens.
NOTE: i need 2-3 paragraphs for how the installation went & if any issues please mention the same, the screen shots should show all th Rstudio screens. Please make sure you download R & Rstudio as it is a compulsion

Categories
R

We will be using data visualization within a tool for this course. Please downlo

We will be using data visualization within a tool for this course. Please download and install R (CRAN) onto your PC.
There are two items that must be downloaded for this course: R and RStudio. Required!
If you are using a computer with a Windows operating system, make sure that when you download base R, you download Rtools, as well.
Verify this by attaching ONLY the screenshots to display your completion of the R software installation. Also, note (in one short paragraph- that is at least three sentences in length) how the installation went and if you encountered any issues. If you did, how were they solved?
Once you complete installation, make your own report to repeat code attached. Make sure to create your own screen shots and report.
Every screenshot in the report should show all 4 Rstudio screens.
NOTE: i need 2-3 paragraphs for how the installation went & if any issues please mention the same, the screen shots should show all th Rstudio screens. Please make sure you download R & Rstudio as it is a compulsion

Categories
R

We will be using data visualization within a tool for this course. Please downlo

We will be using data visualization within a tool for this course. Please download and install R (CRAN) onto your PC.
There are two items that must be downloaded for this course: R and RStudio. Required!
If you are using a computer with a Windows operating system, make sure that when you download base R, you download Rtools, as well.
Verify this by attaching ONLY the screenshots to display your completion of the R software installation. Also, note (in one short paragraph- that is at least three sentences in length) how the installation went and if you encountered any issues. If you did, how were they solved?
Once you complete installation, make your own report to repeat code attached. Make sure to create your own screen shots and report.
Every screenshot in the report should show all 4 Rstudio screens.
NOTE: i need 2-3 paragraphs for how the installation went & if any issues please mention the same, the screen shots should show all th Rstudio screens.