Category: Statistics

Interpret the scatterplot Answer the prompt questions in the attached rubric
There is also a video attached to this rubric “The Happy Planet”
There is not a required length for this paper as long as all the required information is present.

Scenario
Smart businesses in all industries use data to provide an intuitive analysis of how they can get a competitive advantage. The real estate industry heavily uses linear regression to estimate home prices, as cost of housing is currently the largest expense for most families. Additionally, in order to help new homeowners and home sellers with important decisions, real estate professionals need to go beyond showing property inventory. They need to be well versed in the relationship between price, square footage, build year, location, and so many other factors that can help predict the business environment and provide the best advice to their clients.
Prompt
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?
You can use the following tutorial that is specifically about this assignment. Make sure to check the assignment prompt for specific numbers used for national statistics and/or square footage. The video may use different national statistics or solve for different square footage values.

Four discussion questions/posts. The textbook used is Essentials of Statistics for the Behavioral Sciences by Gravetter, F. J., Wallnau, L. B., Forzano, L. B., & Witnauer, J. E. (2021). Essentials of statistics for the behavioral sciences (10th ed.). Cengage. ISBN-13: 9780357365298. Read Chapters 1 and 2 in Essentials of Statistics for the Behavioral Sciences. Review Chapters 1 and 2 PowerPoint presentations. A substantive post is 150 words minimum, incorporates information from the course materials/readings or personal experience, and adds something new to the conversation that others can learn from. 
DQ1: Why is it important to learn statistics in the study of psychology? Give three examples to support your answer. Include in your answer how descriptive and inferential statistics are used in psychology?
You may use your textbook to support your reasoning.
DQ2: What career are you pursuing/doing? How is statistics important in your field? Make sure to be as specific as possible. (pursuing: Behavioral Health Science/counseling and doing: teacher Assistant)
DQ3: This is a two-part discussion question. Each part needs to be completed to earn full points. Throughout your academic career you have read and learned about numerous scientific experiments and discoveries; some of these were empirical studies. Select an empirical study related to a science concept you learned about in high school or from Intro to Psychology (e.g. Pavlov’s dogs, Mendel and genetics). The concept should be one you found fascinating. Part 1: Share why you selected the concept. Part 2: Find two empirical studies related to that concept and for each, identify on what scale they measured their variables of interest: nominal, ordinal, interval or ratio. Why did you come to this conclusion? (Make sure you are including an APA citation for each article!)
DQ4: Creating an actual survey that is effective for gathering the correct data can take a long time. What are some of the key things that need to be considered as you create one?
ADDITIONAL RESOURCES
Gravetter, F. J., Wallnau, L. B., Forzano, L. B., & Witnauer, J. E. (2021). Essentials of statistics for the behavioral sciences (10th ed.). Cengage. ISBN-13: 9780357365298. Read Chapters 1 and 2
Review “Frequency Distribution” from the WolframMathWorld website. https://mathworld.wolfram.com/FrequencyDistribution.html
Review “Summarizing Distributions,” by Lane, from Online Statistics Education: An Interactive Multimedia Course of Study. https://onlinestatbook.com/2/summarizing_distributions/summarizing_distributions.html

You will be taking an exam on May 22, 2024. The exam will be taken on Canvas from 4 to 7 p.m. A username and password will be provided to log into the exam. You will need to submit proof of work when submitting the exam. There are six questions unless the professor changes them on exam day.

It is a lab report using SPSS and t-test. The experiment was done indivitually using computers  we had to recognise faces and objects.

Respond to these statistics videos. The minimum word count to get credit for this post is 200 words which is a sentence or two about what you thought about each video.



https://www.youtube.com/watch?v=uzlioK5UzQ0

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