Category: Statistics

need you to log into my account and complete the low score and I started assignment, review or tests

Language – R
Dataset – The dataset originates from the Hotel Booking demand datasets
available from Kaggle https://www.kaggle.com/datasets/abdulmannann/hotel-bookingdataset-csv
Submission Requirements:
• The project should be completed in Rmarkdown and should be compiled as PDF documents.
• For all parts, both the source file (.Rmd) and the PDF file should be submitted and will be marked.
• The source files (.Rmd) should be able to be compiled, so ensure that all relevant supplementary files (e.g. data files) are uploaded. When you compile your source file, the data file/s should be located in the same directory as your source file.
• The specific requirements for each part of the project are detailed in the coming sections.
• Submissions which contain large quantities of unnecessary code, output or text will be penalized.
Question 1 Dataset (20 marks)
(a) Background information about the problem/dataset (approx 150 – 250 words) (6 marks)
Marking Criteria
• The context of the problem/dataset is clearly described.
• All sources are appropriately referenced.
(b) Description of dataset, including (8 marks)
• Source/Location (e.g. url)
File type (e.g. csv)
• List of variables (description and type)
• Screenshot of dataset
• Type of data cleaning expected
Marking Criteria
• The dataset is described clearly and all elements listed above are included.
(c) 3 proposed research questions/objectives (6 marks)
Marking Criteria
• Questions/objectives are appropriate and clearly stated, and can be answered using data in the
dataset sourced.
Notes
• There may not be any R commands required in this question.
Question 2 Data Import and Cleaning (20 marks)
Explain and perform the steps required to import, clean and tidy your dataset. This may include, but is not limited to, the following tasks:
• importing the data
• tidying the variable names
• ensuring the data follows the three rules of “Tidy Data”
• creating new variables
• changing the format or type of variables
• renaming variables
Marking Criteria
• Rmd/Qmd file can run without error on any computer.
• All data cleaning etc. is reproducible.
• All data import/cleaning/tidying tasks are completed in R using tidyverse functions (where available).
• The required data import/cleaning/tidying tasks have been successfully completed.
• For all data import/cleaning/tidying tasks, appropriate explanations, code and output/results are
included in the PDF file.
• Only necessary code and output are included in the Rmd/Qmd and PDF files.
Question 3 Data Analysis/Report (60 marks)
(a) For each question/objective from Question 1 (c), write at most 2 pages (including graphs, tables, etc. and approx 200 words) to address the following: (45 marks)
• State the question/objective
• Describe the analysis undertaken and show the results.
• The analysis must include at least one graph and some summary statistics.
• At least one objective/research question must include a statistical model/method (e.g. t-test, linear regression, etc.).
• Discuss the results of the analysis
Note: Professionally formatted reports do not usually contain code or raw output. Therefore, this section of the PDF file should not contain any R code or raw output. Use chunk options like echo = FALSE and results = “hide”, functions like kableExtra::kable and xtable::xtable to create nicely formatted tables, and in-text R commands like ` r mean() ` to refer to results.
Marking Criteria
• Appropriate graphs and summary statistics are chosen and correctly used to answer each question/objective.
• Figures have appropriate titles and labels.
• Numerical results are rounded appropriately.
• An appropriate statistical model/method is chosen and applied correctly to answer at least one question/objective.
• All analysis is reproducible and included in the RMarkdown/Quarto file.
• The analysis shown PDF file is nicely formatted and does not include any R code or raw output.
• The results are discussed clearly, and correct and insightful comments are made.
(b) Conclusion (0.5-1 page) (10 marks)
Summarize your findings and discussion implications and limitations of your analysis, and opportunities for future work.
Marking Criteria
• Findings are summarized and the implications are discussed.
• Limitations of the analysis are discussed.
• Opportunities for future work are identified.
(c) Presentation (5 marks)
The report should be professionally presented and well-written.
Marking Criteria
• The report does not have any spelling and grammatical errors.
• The report is professional presented and well-written.
Notes
• All sources must be referenced.

Enclosed, will fine two parts of statistic assignments needed to be completed part one
quentions needed answered, use quention as subheadings, gave in depth answer, gave
examples as well fellowed both instructions as well the grading rubric. Part two of the
statistic assignment, completing:
Quantitative Analysis: Variables, Z Scores, Population, and Output Assignment also, followed the
instructions gaving and grade ruric.

I’ve included the instructions along with an example. NOTE: my topic is different from the example. Here is also a link -that the professor gave us- that can help you with this assignment: http://alexcasteel.com/courses/edco-745/data-screening-assignment/
My topic is: The effect of depression on academic achievement in teenagers

The research department of an appliance manufacturing firm has developed a new bimetallic thermal sensor for its toaster. The new bimetallic thermal sensor can sense the temperature of the bread and move the lever arm to activate the switch. The research department claims that the new bimetallic thermal sensor will reduce appliance returns under the one-year full warranty by 2%-6%. To determine if the claim can be supported, the testing department selects a group of the toasters manufactured with the new bimetallic thermal sensor and a group with the old thermal sensor and subjects them to a normal year’s worth of wear. Out of 250 toasters tested with the new bimetallic thermal sensor, 8 would have been returned. Seventeen would have been returned out of the 250 toasters with the old thermal sensor. As the manager of the appliance manufacturing process, use a statistical procedure to verify or refute the research department’s claim.
Instructions
Create 8-10 slides, including a cover and a sources list, for a presentation to the director of the manufacturing plant in which you:
Summarize the problem with the appliance manufacturing firm’s toaster.
Propose the statistical inference to use to solve the problem. Support your decision using a scholarly reference.
Develop a flowchart for the proposed statistical inference, including specific steps.
Compute all statistical calculations.
Determine if you can verify or refute the research department’s claim.
Provide three quality resources. Choose sources that are credible, relevant, and appropriate. Cite each source listed on your source page at least once within your assignment. For help with research, writing, and citation, access the library or review library guides.
This course requires the use of Strayer Writing Standards (SWS). The library is your home for SWS assistance, including citations and formatting. Please refer to the Library site for all support. Check with your professor for any additional instructions.
The specific course learning outcome associated with this assignment is:
Develop recommendations to improve business processes using statistical tools and analysis.
View Rubric

A jar contains six red marbles, four green marbles, and five yellow ones.
a) Determine the number of ways in which any three marbles can be selected.
(3 marks)
b) Determine the number of ways to select four marbles where two are red and two are yellow. (3 marks)
c) Determine the number of ways in which six marbles can be selected where two are red, two are green, and two are yellow. (3 marks)

You will be working on the Semester Project throughout the term in parts as Project Part Assignments. Additional information can be found on the Semester Project Information page. You will get feedback from your instructor on the parts of the project in the Project Parts as listed. Use that feedback to improve that portion of the project.
Project Part 1: Systematic Sample of your chosen Data Set
1) Choose 1 Data Set from the Data Sets for Project Parts and the Semester Project page.
2) Create a Systematic Sample with 35 values.
Use your birth month as the starting value in Row 1, then use your birthdate as your nth value. An example with additional details is the Data Sets.
3) Write at least 2 quality sentences explaining which Data Set you used, what your starting number was, your nth value, and how you did it, so that any other person would be able to obtain the same results.
4) List your 35 values in the order they were collected.
When working on each part of the Semester Project the Best Practice is to type the information onto the appropriate slide of the Template Download Template, remove the directions, and then copy and paste your work and results into the text submission area of the assignment.
You may submit the project part as a text submission, Word Document, or PowerPoint Slide from the Template (only that slide!) Do not submit your work as an embedded image in one of those files. Images cannot be accepted for these assignments. (File Types allowed: .doc,.docx, ppt., pptx)
my birth month 06 birth day 08

About: In this assignment, you will be looking at statistical output for the ANOVA. The objective is to apply your understanding of how the ANOVA and hypothesis testing works to tell us whether we have a significant relationship between our variables. You will analyze provided data and write a report explaining the populations, variables, which one is the independent and dependent variable, and the results of the ANOVA hypothesis test.
Directions: Select ONE scenarios provided after the directions and complete the following report for your scenario.
Introduction (100 words minimum)
Explain what the independent and dependent variable is in your scenario
Provide the Null and Research hypothesis as based on the two variables provided
Methods (50 words minimum)
Descriptive Statistics: describe the observable differences between the groups (in other words compare their means)
State and briefly explain the f-statistic results (F-statistic and p-value in particular)
NOTE: YOU DO NOT HAVE TO CALCULATE ANY VALUES, ALL VALUES ARE PROVIDED IN THE STATISTICAL OUTPUT
3. Results (100 words minimum)
Interpret the results by explaining where there is a statistically significant relationship or not.
Make sure to state whether we accept or reject the null hypothesis.
Make sure to explain whether this means the two variables are statistically related or not.
4. Discussion (100 words minimum)
Provide some thoughts and considerations on why we obtained the results
Consider at least two additional variables that can explain the results
Clearly and fully explain how the additional variables can affect the results
Word Count: Your report should be about 350 words minimum! Include your word count at the end of your post.
Scenarios: Similar to our previous lab, here are some scenarios of various statistical outputs involving the ANOVA. Select ONE of the following to complete your assignment
ANOVA Lab Scenario 1: Days of Poor Mental Health by Religiousness
ANOVA Lab Scenario 2: Hours of TV by Level of Happiness
ANOVA Lab Scenario 3: Hours of Household Chores by Race
ANOVA Lab Scenario 1: Days of Poor Mental Health by Religiousness
About: In this scenario the researcher is interested in seeing if there is a difference in days of poor mental health between people of different religious levels
The groups that were examined were: Very religious, Moderately Religious, Slightly Religious, and Not Religious at All
Here are their results!
Statistical Output Begins
Descriptive Statistics: Days of Poor Mental Health by Level of Religiousness
Level of Religiousness
N
Mean
Std. Deviation
Very religious
199
2.90
6.680
Moderately religious
585
3.82
7.208
Slightly religious
463
4.50
8.166
Not religious at all
643
5.74
8.400
F-statistic Output
Type of Variation
df
Mean Square
F-statistic
Sig. Level
Between Groups
3
589.560
9.645
p < .001 Within Groups 1886 61.128 Source: General Social Survey, 2022 Directions: 1. If you decide to select this scenario, complete the instructions for lab analysis #2 based on these outputs. 2. Take a picture of the data output, copy and paste it, or keep both the scenario window open and the lab analysis assignment open ANOVA Lab Scenario 2: Hours of TV by Level of Happiness About: In this scenario the researcher is interested in seeing if there is a difference in hours of TV Watching per day between people of different happiness levels The groups that were examined were:Very Happy, Somewhat Happy, Not Too Happy Here are their results! Statistical Output Begins Descriptive Statistics: Days of Poor Mental Health by Level of Religiousness Happiness Level N Mean Hours of TV Standard Deviation very happy 521 2.90 2.869 pretty happy 1358 3.48 3.504 not too happy 459 3.47 3.384 F-statistic Output Type of Variation df Mean Square F-statistic Sig. Level Between Groups 3 68.366 6.095 p = .002 Within Groups 1886 11.216 Source: General Social Survey, 2022 Directions: 1. If you decide to select this scenario, complete the instructions for lab analysis #2 based on these outputs. 2. Take a picture of the data output, copy and paste it, or keep both the scenario window open and the lab analysis assignment open ANOVA Lab Scenario 3: Hours of Household Chores by Race About: In this scenario the researcher is interested in seeing if there is a difference in hours of household chores between people of different racial groups The groups that were examined were: White, Black, Other Here are their results! Statistical Output Begins Descriptive Statistics: Days of Poor Mental Health by Level of Religiousness Happiness Level N Mean Hours of Household Chores Standard Deviation White 804 9.90 hours 10.095 Black 1849.66 15.488 Other 127 11.46 11.252 F-statistic Output Type of Variation df Mean Square F-statistic Sig. Level Between Groups 2 149.8 1.175 p = .309 Within Groups 1112 127.4 Source: General Social Survey, 2022 Directions: 1. If you decide to select this scenario, complete the instructions for lab analysis #2 based on these outputs. 2. Take a picture of the data output, copy and paste it, or keep both the scenario window open and the lab analysis assignment open

You have been recently hired as a junior analyst by D.M. Pan Real Estate Company. The sales team has tasked you with preparing a report that examines the relationship between the selling price of properties and their size in square feet. You have been provided with a Real Estate Data Spreadsheet spreadsheet that includes properties sold nationwide in recent years. The team has asked you to select a region, complete an initial analysis, and provide the report to the team.
Note: In the report you prepare for the sales team, the response variable (y) should be the listing price and the predictor variable (x) should be the square feet.
Specifically you must address the following rubric criteria, using the Module Two Assignment Template:
Generate a Representative Sample of the Data
Select a region and generate a simple random sample of 30 from the data.
Report the mean, median, and standard deviation of the listing price and the square foot variables.
Analyze Your Sample
Discuss how the regional sample created is or is not reflective of the national market.
Compare and contrast your sample with the population using the National Summary Statistics and Graphs Real Estate Data PDF document.
Explain how you have made sure that the sample is random.
Explain your methods to get a truly random sample.
Generate Scatterplot
Create a scatterplot of the x and y variables noted above. Include a trend line and the regression equation. Label the axes.
Observe patterns
Answer the following questions based on the scatterplot:
Define x and y. Which variable is useful for making predictions?
Is there an association between x and y? Describe the association you see in the scatter plot.
What do you see as the shape (linear or nonlinear)?
If you had a 1,800 square foot house, based on the regression equation in the graph, what price would you choose to list at?
Do you see any potential outliers in the scatterplot?
Why do you think the outliers appeared in the scatterplot you generated?
What do they represent?
https://learn.snhu.edu/d2l/le/content/1612807/viewContent/33022711/View

What is the standard deviation (s) of the following set of scores?
12
25
6
9
16
13
11
10
8
7
6
14
16
12
11
23
Group of answer choices
7
5.49
5
3.36
What is the range of the following set of scores?
13.7
53.2
4.1
9.3
52.1
32.5
22.9
41.5
23.0
15.5
1.9
33.2
Group of answer choices
39.6
50.2
51.3
9
What is the variance (s2) of the following set of scores?
12
25
6
9
16
13
11
10
8
7
6
14
16
12
11
23
Canadian Adults with kidney disease were selected to participate in a survey regarding their views on cannabis use. The survey asked participants to rank on a scale of 1-5 (1, definitely would not; 5, definitely would) whether they would try cannabis for various symptoms.
Collister, D., Herrington, G., Delgado, L., & Whitlock, R. (2023). Patient views regarding cannabis use in chronic kidney disease and kidney failure: a survey study. Nephrology Dialysis Transplantation, 38(4), 922–931. https://doi-org.ezproxy1.lib.asu.edu/10.1093/ndt/gfac226
What category/scale of measurement is this?
Group of answer choices
ratio
ordinal
nominal
interval
Which of the following are nominal data? (choose one or more)
Group of answer choices
two categories of exposure to a treatment (exposed and unexposed)
three categories (low, medium, high) of heart rate ranges
five categories of race
four categories of satisfaction (low, somewhat satisfied, satisfied, very satisfied)
three streets (Dove, Raven, Hawk) in a neighborhood
Given the following data, what is the correlation between income and education?
Income
Education
$36,577
11
$54,365
12
$33,542
10
$65,654
16
$45,765
11
$24,354
7
$43,233
12
$44,321
12
$23,216
9
$43,454
12
$64,543
14
$43,433
13
$34,644
12
$33,213
10
$55,654
15
$76,545
16
$21,324
10
$17,645
10
$23,432
9
$44,543
15
Group of answer choices
.87
.75
.90
.42
Researchers study the relationship between hours spent playing video games and GPA. They find that as the number of hours spent playing video games increases, GPA decreases. What type of relationship is this?
Group of answer choices
No relationship
Positive relationship
Negative relationship
In this scatterplot:
x axis = scale of income inequality
y axis = patents per million population
Which of statement(s) is(are) TRUE? (choose one or more)
Group of answer choices
This scatterplot shows an indirect relationship
Countries with greater income inequality are less innovative (have less patents per million population)
Countries with greater income inequality have greater innovation (have more patents per million population
This scatterplot shows a direct relationship
Which of the following correlations would be interpreted as a strong relationship based upon our textbook? (choose one or more)
Group of answer choices
.50
.70
.60
.80
What is the possible range of values for a correlation coefficient?
Group of answer choices
0 to 100
–.01 to .01
–1.0 to 1.0
0 to 1.0
Given the following data, what is the correlation between age and length of sentence?
Respondent
Age (x)
Length of Sentence (months)
1
14
80
2
15
65
3
15
155
4
20
192
Average
16
123
Group of answer choices
.65
.79
-.58
-.87
A perfect negative correlation would be represented by Pearson’s r of -1.
Group of answer choices
True
False