Hello All, I am doing mixed methods for my dissertation and need help with my quant data. Background: I am running an educational intervention and have a control group (standard class) and an experimental group (extended class). Control has 41 students and experimental has 44 students. Note: The following is BACKGROUND info only. We can discuss if I chose the correct tests and how to run them later. Data: 1) A pre and post survey with 28 Likert scale questions (data has already been cleaned up and 37 students did both pre and post in control and 32 students in experimental). I believe I need to run a multiple linear regression and want to control for gender, race, and socioeconomic status. I do need to reverse score half of the questions, but I wanted to wait to do that. 2) Exam scores for 4 different exams taken throughout the semester. I have the exam scores for each student individually. Want to look at the changes throughout the semester between control and experimental. I believe I need to conduct a mixed ANOVA and again control for the same covariates as above. Data has also already been cleaned up and covariates as been assigned to each participant. 3) Assignment completion rate. This one gets messy. Almost each week during the semester, there are different assignments due throughout the week. During the entire semester I took data on how many students turned in those assignments on time for both control and experimental. There are 4 different assignment categories. My committee wants me to run the data three different ways: a) ALL participants are counted from start to finish b) Students who officially or unofficially drop (stop coming to class/exams) are taken out of the data AS they drop out c) Participants are only the students who did the entire course I have created an excel sheet with each one of these scenarios for both control and experimental group (except for “c” as the semester is finishing this week) so 3 excel sheets for both groups. Again, I believe mixed ANOVA. This will not have the covariates as this is a group completion and not individual. I am an extremely fast learner and good with computers so I want to hire someone who will help me set up my data for SPSS, make sure I have the right tests, help me run them, and help me read the results. I do want someone who REALLY knows that they are doing. I need a statistical/SPSS expert please as I am a bit of perfectionist and so is my committee 😊. Message me if interested and background info about yourself.

This is going to be a simple and quick analysis work.

Very simple calculations to do. Data is not big and simple analysis to be done.

Job Description: We are seeking a highly skilled Quantitative Analyst to join our team in developing and implementing advanced pricing models for structured notes. The successful candidate will play a crucial role in analyzing and quantifying the risk associated with various structured notes, helping our clients make informed investment decisions. Key Responsibilities: - Develop and implement sophisticated pricing models for structured notes, incorporating advanced statistical methods and financial modeling techniques. - Conduct in-depth research on structured note pricing methodologies, staying up-to-date with the latest academic and industry developments. - Perform data analysis and statistical modeling to identify key risk factors and drivers of structured note performance. - Design and execute Monte Carlo simulations, historical stress testing, and scenario analysis to assess the probability of barrier breaches for structured notes. - Construct and calibrate volatility surface models to capture the implied volatility of underlying assets across different strike prices and maturities. - Implement copula-based dependency modeling to accurately capture the joint behavior of multiple underlying assets in a structured note. - Conduct risk sensitivity analysis to determine the impact of changes in key risk factors on the probability of barrier breaches. - Collaborate with sales to ensure the effective integration of pricing models into the company's offerings. - Communicate complex quantitative concepts and model results to both technical and non-technical stakeholders in a clear and concise manner. - Continuously monitor and validate pricing models, making necessary adjustments based on market conditions and performance data. Required Skills and Qualifications: - Advanced degree (Master's or Ph.D.) in a quantitative field such as Mathematics, Physics, Financial Engineering, or a related discipline. - Strong understanding of structured notes, options pricing, and financial derivatives. - Proficiency in programming languages such as Python, R, or C++, with experience in quantitative libraries like NumPy, SciPy, and QuantLib. - Expertise in statistical modeling, machine learning, and data analysis techniques. - Knowledge of stochastic calculus, partial differential equations, and numerical methods. - Familiarity with financial data sources, such as Bloomberg, Reuters, or FactSet. - Excellent problem-solving skills and the ability to think creatively to deveStrong attention to detail and a commitment to producing high-quality, accurate results. - Excellent written and verbal communication skills, with the ability to explain complex concepts to diverse audiences. - Ability to work independently and collaborate effectively in a team environment. Preferred Qualifications: - Prior experience in pricing structured notes or similar financial instruments. - Knowledge of volatility surface modeling, copula-based dependency modeling, and risk sensitivity analysis. - Experience with parallel computing and optimization techniques for efficient model execution. If you are a passionate and skilled Quantitative Analyst looking to make a significant impact in the world of structured note pricing, we would love to hear from you. Please submit your resume, along with a cover letter highlighting your relevant experience and qualifications, to be considered for this exciting opportunity.lop innovative pricing solutions.

We conducted a survey of 160 car dealerships across the United States that are using our software. We asked them 16 questions - see attached survey screenshots - but would like your help to understand the patterns and trends in the data. Other than basic pie charts per question, we're looking for themes or trends across the dataset. 1.) What are the major differences between the dealerships that exclusively sell Hyundai from those that exclusively sell Genesis? 2.) What can we tell from our meetings with General Managers vs. sales reps and sales staff? 3.) What do we know about the 8 active users when compared with those who ever heard of our software? 4.). Eleven people didn't log into our software when we were there onsite. Are there any patterns or insights about these individuals? 5.) Some people were indifferent at the end of our meeting, what do we know about them? 6.) Are there any correlations between those who preferred certain features vs. others? (you'll need to add "all of the above" since that was the overwhelming response in the other category.) Again, there are just my ideas, but I'm really looking for you - a very intellectually curious statistician to take the lead here and help me "know what I don't know." Let's start with 2 hours of your time, reading the data set and replying with a list of topics - like the ones above - that you'll solve for. Then, I'd like your deliverable to be a series of slides with an observation in the header, followed by the proof points, data set or data visualization in the body of the slide. It'd be amazing if we can work together and then in the end, you could produce 12-15 slides, each with a thoughtful insight such as 1-6 above. Also, don't worry about making the slides look nice, I will have a graphic designer clean them up. I would like your help so that we can finish by Sunday, April 21. How does that sound? Thanks again. -John

We are seeking a Junior Survey Analysis Specialist to join our team. In this role, you will be responsible for analyzing survey data and providing actionable insights to our clients. The ideal candidate should have a strong background in statistical analysis, data visualization, and survey methodology. You should also have excellent attention to detail and the ability to work independently. This is a great opportunity for someone who is looking to gain experience in survey research and analytics. Responsibilities: - Analyze survey data using statistical software - Create visually appealing data visualizations - Generate reports summarizing survey findings - Collaborate with clients to understand their research objectives Requirements: - Bachelor's degree in Statistics, Market Research, or a related field - Proficiency in statistical analysis software (e.g., SPSS, R) - Strong analytical and problem-solving skills - Excellent written and verbal communication skills - Attention to detail and ability to meet deadlines

Dr. Giese is a top Board-Certified Plastic Surgeon. She is known by the media as a body contouring and anti-aging expert, with appearances on Dr. Oz, Fox News, ABC, and NBC. Dr. Giese has also conducted groundbreaking fat research at Georgetown University in conjunction with the NIH. You can visit her website for more information if you like: www.sharongiesemd.com She is writing an observational study, on FDA approved GLP-1 drugs and their effect on weight loss for a non-obese population. She has collected data on her patients over the last two years. We have an opportunity to help her analyze the data and make both statistical observations and graphs for her study. This is a paid position, and she imagines it would be around 15 hours of work. Attached is her abstract from a year ago, where the population size was around 30. We now have about 150-200 patients. Thank you for your time in reading this. We are excited to hear back from you soon. The Office of Dr. Sharon Giese

We are looking for a skilled survey analysis expert to assist us in analyzing survey data. The ideal candidate will have experience in survey design, data collection, and statistical analysis. Your responsibilities will include cleaning and organizing survey data, conducting descriptive and inferential statistical analysis, and generating insightful reports.

We're looking for someone who can perform a cluster analysis on Qualtrics data from a survey conducted with a little over 123 physicians who put in 363 patient charts. The data is in: StatsIQ Using Qualtrics Clustering Analysis You tell us how long you think it will take after an intro meeting to discuss with the team. We'll pay your hourly rate.

We are seeking a skilled professional to assist with data analysis and interpretation from a research project. The main tasks include reading and understanding the data, and explaining the box plots and analysis results. The ideal candidate should possess expertise in data analysis and interpretation, as well as strong communication skills to clearly explain complex data concepts. Attention to detail and the ability to interpret data visualizations is crucial for this role. The chosen candidate will work closely with our team to provide insightful and accurate analysis of the research data. Skills required: - Data analysis - Data interpretation - Communication - Attention to detail