Category: R

Introduction: Provide a concise overview of the concepts of parametric tests, un

Introduction: Provide a concise overview of the concepts of parametric tests, univariate tests for normality, and hypothesis testing.
Dataset Selection: Identify and describe a dataset suitable for applying these tests. Explain your reasons for choosing it.
Parametric Test Application: Conduct a parametric test on your selected dataset. Include all steps and any Python or R code you used.
Univariate Test for Normality Application:Perform a univariate test for normality on your dataset. Again, include all steps and any Python or R code used.
Results and Conclusion: Summarize your test results. Were your hypotheses confirmed or rejected? What conclusions can you draw about the population from your sample?
Submission Format: Your submission should be a maximum of 500-600 words (excluding Python/R code). Submit your assignment in APA format as a Word document or a PDF file. Include your written analysis and any tables or visualizations that support your findings. If you used any software for your calculations (like R, Python, Excel), please include your code or formulas as well. Include an APA-formatted reference list for any external resources used.

Please help me with these questions related to R. And provide the answer in R ma

Please help me with these questions related to R. And provide the answer in R markdown PDF file. Thank you!
Study of Teenage Gambling in Britain
The teengamb dataset contains a survey conducted to study teenage gambling in Britain. The dataset has 47 observations and five variables:
sex: 0 = male, 1 = female
status: Socioeconomic status score based on parents’ occupation
income: income in pounds per week
verbal: verbal score in words out of 12 correctly defined
gamble: expenditure on gambling in pounds per year
Use the following statement to access the data: data(teengamb, package= “faraway”)
Question 1
Make sure to convert any categorical variable to a factor.
Create a regression with gamble as the outcome variable and sex, status, income, and verbal as predictors.
Hint: See Lesson 3, Slide 48.
Question 2
Create a standardized residuals vs. fitted plot. Do you think the variance is constant?
Hint: See Lesson 6, Slide 11.
Question 3
Create a Quantile-Quantile plot and a histogram based on the standardized residuals. Does the distribution of residuals look normal?
Hint: Go to Lesson 6, Slide 28.
Question 4
Print all the standardized residuals.
Are there any observations with standardized residuals greater than 3 or smaller than -3? If so, which ones? What are their standardized residuals?
Hint: Use the rstandard function
Question 5
Identify points with leverages that are at least two times the average leverage.
Did you find any points? If so, which points did you find?
Hint: Go to Lesson 6, Slide 22.
Question 6
Detect outliers using studentized residuals. Use the Bonferroni correction.
Did you detect any outliers? If so, show the studentized residual of any outlier you found.
Hint: Go to Lesson 6, Slide 40.
Question 7
Show the values of any outlier observation you found in question 6 (i.e., show the entire row of each such observation).
Hint: Assuming that observation 5 is an outlier, you can use teengamb[5,]Question 8
Use Cook’s distances to search for influential points. Does any point have a Cook’s distance above 0.5?
Hint: See Lesson 6, Slide 48.
Question 9
Create a half normal plot of the Cook’s distances. Which four observations have the highest Cook’s distances?
Hint: See Lesson 6, Slide 48.

Please help me with these questions related to R. And provide the answer in R ma

Please help me with these questions related to R. And provide the answer in R markdown PDF file. Thank you!

A store sells two types of toys, A and B. The
store owner pays $8 and $14 for e

A store sells two types of toys, A and B. The
store owner pays $8 and $14 for each one unit
of toy A and B respectively. One unit of toys A
yields a profit of $2 while a unit of toys B yields
a profit of $3. The store owner estimates that no
more than 2000 toys will be sold every month
and he does not plan to invest more than
$20,000 in inventory of these toys. How many
units of each type of toys should be stocked in
order to maximize his profit?
ex2 transportation problem

1. Provide the code that parallelizes the following:
library(MKinfer) # Load pa

1. Provide the code that parallelizes the following:
library(MKinfer) # Load package used for permutation t-test
# Create a function for running the simulation:
simulate_type_I <- function(n1, n2, distr, level = 0.05, B = 999,alternative = "two.sided", ...) { # Create a data frame to store the results in: p_values <- data.frame(p_t_test = rep(NA, B),p_perm_t_test = rep(NA, B),p_wilcoxon = rep(NA, B)) for(i in 1:B) { # Generate data: x <- distr(n1, ...) y <- distr(n2, ...) # Compute p-values: p_values[i, 1] <- t.test(x, y, alternative = alternative)$p.value p_values[i, 2] <- perm.t.test(x, y,alternative = alternative,R = 999)$perm.p.value p_values[i, 3] <- wilcox.test(x, y,alternative = alternative)$p.value } # Return the type I error rates: return(colMeans(p_values < level)) } 2. Provide the code that runs the following code in parallel with 4 workers (with mclapply): lapply(airquality, function(x) { (x-mean(x))/sd(x) })

Data
Obtain time series data on the price of a commodity. ** I will send the da

Data
Obtain time series data on the price of a commodity. ** I will send the data
Analysis
(1) Transform the data if necessary. (2) Plot the data and tabulate the descriptive statistics. Comment on your observations. (3) Conduct ARIMA modelling. (4) Appraise the adequacy of the results and apply appropriate diagnostic procedures. Which model gives the best ‘fit’? (5) Forecast the commodity price using appropriate forecasting techniques and evaluate your forecast. Select the best model for forecasting. (6) Compare your methods and findings with those of other empirical studies on this topic.

Part 1: Understanding Data and Measurement (15 points)
Data and Information Hier

Part 1: Understanding Data and Measurement (15 points)
Data and Information Hierarchy (5 points): Describe the difference between data, information, knowledge, and wisdom, explaining the hierarchical relationship among them. Provide a specific, real-world example to illustrate each level of the hierarchy.
Variables and Measurement Scales (10 points): Explain the different types of variables (nominal, ordinal, interval, and ratio), and describe the associated scales of measurement. Provide a specific example of each type of variable and explain why it is classified as such.
Part 2: Descriptive Statistics and Bivariate Analysis (30 points)
Frequency Distribution and Summary Measures (15 points): Select a dataset (this could be publicly available data or a dataset from your workplace). Create a frequency distribution for a chosen variable, calculate common summary measures (mean, median, mode, range, variance, and standard deviation), and provide a short interpretation of these measures.
Bivariate Analysis (15 points): With the same dataset or a different one, conduct a bivariate analysis that includes both an association between two qualitative variables and a correlation between two quantitative variables. Interpret your findings.
Part 3: Probability and Distributions (30 points)
Probability (10 points): Discuss the basic rules of probability, conditional probability, and Bayes’ theorem. Illustrate your discussion with unique examples.
Random Variables and Probability Distributions (20 points): Define discrete and continuous random variables. Give a real-world example of each and describe the associated probability distribution for each variable.
Part 4: Sampling Techniques (20 points)
Sampling (20 points): Define and differentiate random and non-random sampling. Discuss how to determine an appropriate sample size for a given study. Include an illustrative example from a real or hypothetical research study.
Submission Format:
The assignment should be approximately 2,000 words. The focus should be on the quality and depth of your responses, rather than meeting a strict word count.
Cite your sources in-text and on the reference page in APA format.
Write in a clear, concise, and organized manner; demonstrate ethical scholarship in accurate representation and attribution of sources.

Part 1: Understanding Data and Measurement (15 points)
Data and Information Hier

Part 1: Understanding Data and Measurement (15 points)
Data and Information Hierarchy (5 points): Describe the difference between data, information, knowledge, and wisdom, explaining the hierarchical relationship among them. Provide a specific, real-world example to illustrate each level of the hierarchy.
Variables and Measurement Scales (10 points): Explain the different types of variables (nominal, ordinal, interval, and ratio), and describe the associated scales of measurement. Provide a specific example of each type of variable and explain why it is classified as such.
Part 2: Descriptive Statistics and Bivariate Analysis (30 points)
Frequency Distribution and Summary Measures (15 points): Select a dataset (this could be publicly available data or a dataset from your workplace). Create a frequency distribution for a chosen variable, calculate common summary measures (mean, median, mode, range, variance, and standard deviation), and provide a short interpretation of these measures.
Bivariate Analysis (15 points): With the same dataset or a different one, conduct a bivariate analysis that includes both an association between two qualitative variables and a correlation between two quantitative variables. Interpret your findings.
Part 3: Probability and Distributions (30 points)
Probability (10 points): Discuss the basic rules of probability, conditional probability, and Bayes’ theorem. Illustrate your discussion with unique examples.
Random Variables and Probability Distributions (20 points): Define discrete and continuous random variables. Give a real-world example of each and describe the associated probability distribution for each variable.
Part 4: Sampling Techniques (20 points)
Sampling (20 points): Define and differentiate random and non-random sampling. Discuss how to determine an appropriate sample size for a given study. Include an illustrative example from a real or hypothetical research study.
Submission Format:
The assignment should be approximately 2,000 words. The focus should be on the quality and depth of your responses, rather than meeting a strict word count.
Cite your sources in-text and on the reference page in APA format.
Write in a clear, concise, and organized manner; demonstrate ethical scholarship in accurate representation and attribution of sources.

I have attached the instructions below and the rmd with the cvs file is in the l

I have attached the instructions below and the rmd with the cvs file is in the link below. Thank you for helping me.
The link to rmd file: https://drive.google.com/drive/folders/1A5-7HJgp0u…

I attached the instructions below and the rmd with the cvs file is in the link b

I attached the instructions below and the rmd with the cvs file is in the link below. Thank you for helping me.
The link to rmd file: https://drive.google.com/drive/folders/1A5-7HJgp0u…