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This final part is where you pull together everything that you have learned so far in class and demonstrate how it relates to your selected topic. This submission requires you to use your Week 2 Project Part A submission and analyze your findings from a statistical perspective. Instructions Your final project should include Part A and all of the following: Sampling: A careful description of how the samples were obtained. Be very specific. Include sample sizes, the population of interest, and a description of the sample. Also, include a copy of the survey if you used one. Data: The actual data and a summary of the counts. Descriptive Statistics: Any descriptive statistics relevant to your project should be included. You are required to give the mean, mode, median, and standard deviation of your data (2 sets if you are doing 2 means). At least two graphs (such as box plots, scatter plots, stem-and-leaf, histograms, etc.) should be part of your project. The graphs can be a way to summarize descriptive statistics. Hypotheses testing: Show your hypothesis test and discuss any conclusions they suggest State the hypotheses you will test and formally write them in proper notation Give the results (reject, fail to reject) and explain what that means in a practical way. Conclusion: Discuss the weaknesses of your study. To what population do you feel comfortable extrapolating your results? Why? Give suggestions for further work in the area of your topic. Be sure to reference the situation as you discuss your conclusion. (this is a great time to seek out similar published research on your topic, is yours in line with those results? If not why do you think that is? Explain what leads you to the conclusion(s) that you have drawn. What would you change if you started this project again? What considerations would you include? Include any areas of caution that a reader or user of your work should be aware of as they make decisions. Was the sample random, was the sample large enough, etc? References in APA format. Rubric Project Submission B Rubric (Final) Project Submission B Rubric (Final) Criteria Ratings Pts This criterion is linked to a Learning OutcomeSample and Target PopulationClear description of sampling method, size, population, and description of sample (with survey if applicable) 10 pts Mastery Clear description of sampling method, size, population, and description of sample (with survey if applicable) 7 pts Competent Sample and population identified with few errors, or sampling method brief and/or not descriptive enough for clarity. 3 pts Beginning Understanding Sample or Population is either absent or incorrect, or description is absent. 0 pts Missing No direct discussion about the sample, population, and sampling method. 10 pts This criterion is linked to a Learning OutcomeDataComplete data set and summary of counts 10 pts Mastery Complete data set and summary of counts 7 pts Competent Data set and summary of counts with minimal errors. 3 pts Beginning Understanding Data set or summary of counts missing or substantially inaccurate. 0 pts Missing Data set not included. 10 pts This criterion is linked to a Learning OutcomeMean, Median, Mode, and Standard DeviationCorrectly calculated mean, mode, median, and standard deviation 20 pts Mastery Correctly calculated mean, mode, median, and standard deviation with accompanying work or calculations. 15 pts Competent Correctly calculated mean, mode, median, and standard deviation 10 pts Developing Competency Mean, mode, median, and standard deviation calculated with some errors. 5 pts Beginning Understanding Mean, mode, median, or standard deviation calculated with substantial errors or individual measurements are missing. 0 pts Missing No mention of mean, median, mode, and standard deviation. 20 pts This criterion is linked to a Learning OutcomePictorial RepresentationsTwo correct graphs summarizing descriptive statistics 10 pts Mastery Two correct graphs summarizing descriptive statistic that are clear in their presentation. 7 pts Competent Two correct graphs summarizing descriptive statistic 3 pts Beginning Understanding Unclear graphs summarizing descriptive statistics, or one missing. 0 pts Missing Both graphs are not present. 10 pts This criterion is linked to a Learning OutcomeHypothesis TestCorrectly calculated hypothesis test 20 pts Mastery Correctly calculated hypothesis test thoroughly with conditions met and proper handling of null-hypothesis. 15 pts Competent Correctly calculated hypothesis test 10 pts Developing Competence Calculated hypothesis test but there are missing components critical to the test. 5 pts Beginning Understanding Calculated hypothesis test but has substantial errors. 0 pts Missing No hypothesis test included. 20 pts This criterion is linked to a Learning OutcomeConclusionsConclusion discusses weaknesses and confounding variables 20 pts Mastery Conclusion discusses weaknesses and confounding variables clearly. Also addresses plans for how to improve if the project were to be done again. 15 pts Competent Conclusion discusses weaknesses and confounding variables 10 pts Developing Competency Conclusion discusses weaknesses and confounding variables but is unclear or has some slightly erroneous conclusions. 5 pts Beginning Understanding Conclusion discusses weaknesses and confounding variables are unclear and has erroneous conclusions. 0 pts Missing No conclusion present. 20 pts This criterion is linked to a Learning OutcomeCraftsmanshipReference(s) using APA format 10 pts Mastery Reference(s) using APA format done correctly and with excellent organization/presentation. 8 pts Competent Reference(s) using APA format with minor errors but still well organized. 5 pts Beginning Understanding Reference(s) with major mistakes, or weak organization. 0 pts Missing No references or poor organization 10 pts Total Points: 100

Open the Heart Rate Excel Data Set and identify the quantitative variables. Make sure the data is sorted by category (e.g.male-at-rest, female-at-rest, etc.). Use the Data Analysis tools of Excel to construct 95% and 99% confidence intervals for all 8 categories of the sorted quantitative variables. Excel will calculate the margin of error given as the “confidence interval” in the output. Use this margin of error to create your 8 confidence intervals by both adding and subtracting it from the sample mean (calculated in unit 3). This creates a range of values that is the confidence interval. Create a Word document, and use your calculated results to explain what the confidence intervals tell us. What do these confidence intervals tell us about our heart rate data? How would you interpret the 95% and 99% intervals for resting heart rate? Compare the 99% and 95% intervals and explain why one is larger than the other even though we use the same sample mean value. ADDITIONAL INSTRUCTIONS: Your assignment should be typed into a Word or other word-processing document, formatted in APA style. The assignments must include Running head A title page with Assignment name Your name Professor’s name Course Include references used to completet assignment

Hello, please help me solve these question in lab 3 exercise by using R, these questions related to longitudinal analysis. I also provide the solution code for these question, please do it in different way so I can understand it better. Thank you. All the needed document is attached below.

Hello, I hope this message finds you well. I have an assignment, and I need your help. I have attached the files. 1. The instructions to do the assignment. 2. Examples. The like for the book include chapters 1, 2, and 3. https://drive.google.com/file/d/1a2iw4LWY8U6xRkhrk... Your support in refining and perfecting the assignment would mean a lot to me. Please let me know if you need any additional information or clarification. (Note: please be careful if you will be using AI tools because that is not allowed by my professor; please check AI Detector and Plagiarism)

Hello. I was hoping that you would be able to assist me with this week's assignment and it only need to be between 350-700 words. I have attached the Assignment and Requirements, Chapters, the Call Time Analysis, and the Call Time Data (Excel Spreadsheet). Thank you

Lab 2: Describing Data using graphing and frequency table In this assignment, you will practice analyzing univariate data (e.g., single variable at a time) by interpreting frequency, percentage, and cumulative distributions of nominal and ordinal variables. For this lab, we will use 2019 Monitoring the Future Survey data from 12th graders in U.S. schools. You downloaded this dataset previously. If you have not downloaded the dataset yet, please refer to the previous information for instructions on how to access and download the dataset. Please answer each of the following questions in full. For some you will type your answers (please use full sentences with proper grammar). For others, you will copy screenshots or provide key information from your SPSS output. Please ALSO attach or submit your SPSS output with every assignment! You will lose 5 points if the SPSS output is not uploaded with the assignment submission. These assignments should be completed individually, and each person must submit an independent lab assignment. You are encouraged to discuss the labs with your peers/group, but each student should write up their answers independently. UPDATE FROM THE PROFESSOR: Please use V2101 for the ever smoke variable. Do NOT use V2101D please. Thank you!

write a statistical report, simple question, no AI and no plagiarism, and follow details on uploaded files

nstructions In this exercise we will: Learn how to create a scatterplot. Use the scatterplot to examine the relationship between two quantitative variables. Learn how to create a labeled scatterplot. Use the labeled scatterplot to better understand the form of a relationship. In this activity we explore the relationship between weight and height for 81 adults. We will use height as the explanatory variable. Weight is the response variable. We will then label the men and women by adding the categorical variable gender to the scatterplot. We will see if separating the groups contributes to our understanding of the form of the relationship between height and weight. Instructions Click on the link corresponding to your statistical package to see instructions for completing the activity, and then answer the questions below. Excel | TI Calculator Question 1: Describe the relationship between the height and weight of the subjects. To describe the relationship write about the pattern (direction, form, and strength) and any deviations from the pattern (outliers). So far we have studied the relationship between height and weight for all of the males and females together. It may be interesting to examine whether the relationship between height and weight is different for males and females. To visualize the effect of the third variable, gender, we will indicate in the scatterplot which observations are males and which are females. https://s3-us-west-2.amazonaws.com/oerfiles/Concepts+in+Statistics/assignments/scatterplot5lbd/scatterplot5lbd_ti0.html

Hello. I was hoping that you would be able to assist me with this week's discussion question and it only need to be 175 words. I have attached the DQ, and the Chapters. Thank you

1) Explain why factorial designs with two or more independent variables (or factors) can induce errors when interpreting data. Give an example. 2) Explain how the ANOVA impacts a Type I error. How might a Type I error change when comparing groups two at a time using the t-test for independent groups?