Tips and Tricks.
Statistical analysis is a mathematical science, the practice of evaluating and understanding quantitative data. Statistical analysis will make sense of indexes such as standard deviation, and note outliers. The analysis of the data may aid in decision-making in the face of uncertainty.
Quantitative data is represented as numbers, and therefore may be presented in graph format. This simplifies the explanations and visualizations of the data’s meaning. The graph alone will show a positive or negative correlation, a bell curve, or no correlation at all.
Statistics require a population to be studied, and statistical analysis is commonly used regarding census data organized by governments, sociology and medicine.Hire Statistical Analysers
We are conducting a pretest-posttest (repeated measures) study with three between-subjects conditions and one continuous covariate. We have found significant interaction effects and are trying to decompose these interactions by looking at paired t-test results. However, we also want to include the covariate in our t-test analyses and are not sure how to do this in SPSS.
My name is Arumugam Thanumalaya MD, a Physician based in US. we have created a software, which diagnoses illnesses, by asking a bunch of pertinent questions, based on there complaints, which an experienced physician would [login to view URL] question is weighted, and based on the answers, the software will diagnose. We are planning to test this software in the real world, with a bunch of Patients...
I am working on the subject ' Trend-following and Risk parity strategy for asset allocation'. So, I want to do some empirical studies to see whether a combination of Trend-following strategy and Risk-parity strategy provide a better return compared to the 60/40 strategy (equity and bond). Moreover, I want to compare both strategies separately. More explanation to come..
Aim is to identify weather estimated weight based thrombolysis ( usually TPA drug is given as 0.9mg/kg) is predictor of actual weight based thrombolysis and if this alters stroke outcomes including intracerbral Haemorraghe , functional independence, mortality. I would appreciate help in statistical methods for this systematic review and meta analysis. The trials are mainly observational.
Renko is a charting pattern which is used in charting platforms which helps in price analysis and it's movements. Renko is a time independent chart and does not affected by time factor. It only plots it charts according to price actions. But whenever we give certain timeframe for eg- 10min,30min,1hr in the base chart the renko bricks do get affected. And i want to make this thing in python.
The task is to write a 15-page tutorial, i.e., about 4500 words, on Structural Equation Modeling (SEM). The tutorial needs to include three examples (or otherwise advised by the writer) that would help the beginners or readers or students in working on SEM. The tutorial may include the use of R, Python, SPSS, or other such statistical applications. The information provided in the tutorial must no...
To find the relation between Internet banking and customer satisfaction Use regression and correlation method for finding the relation between Customer satisfaction (Dependent variable) and Independent variable
i want someone to do this verification technique
I have a short Likert Scale questionnaire (12 Questions) measuring 5 variables. I want to find : 1- P-value 2- Validity 3- Reliability 4- Writing the analysis of the data for the collected data the number of participants is 30 the data are in Excel file
Hi, everyone. I need someone to solve 4 lists of tasks (about 10 tasks per list). Topics are linear algebra, calculus, statistics probability. University level. Write something about your experience in this topic. I won't consider anyone with a template greeting message. Only original text. I have a budget arount 100$
Description: -An introduction of the matter & a clear statement of the Research Question/s. - Secondary Data Collection (Formatting and Importing in E- Views). -Stating the Data Source and Commenting on the Elements of Descriptive Statistics. -Commenting on some measures of the shape of the distribution. -Estimating, Analyzing and Interpreting in detail the Econometric Model and Final Output....
I need you to make a research paper on the topic with introduction, analysis, statistics, examples, conclusion and with recommendations and suggestions.
namely try and compute the posterior for a Binomial likelihood and Normal prior – with chosen mean and variance – in the case of the coin toss experiment. So to be precise, you are computing the posterior of the parameter p, which is the probability for a Heads to turn up in a throw of an unfair coin, where the posterior is computed given the simulated data that comprises 4 data points...
All you need to develop an AI agent which will predict winner of a match and will suggest how much to bet on which players in order to get maximum profit. We already have an AI agent which predicts 85-86% accurately. You can use this pre built algorithm or can start over. Target is to achieve 93-95% accuracy. The learning process should be reinforcement-learning so that it can learn on continuous ...
I need to create a table showing the effects of multiple planned comparisons on p values if you don't use a correction and showing the progressive risk of false positives with each additional comparison.
Hi I have users on our online platform which are not evenly distributed across. In identified users, we have 70% Female vs 30% Male. Which means if I want to indetify new user with out any previous history on website I will be always biasing towards female My question is how I can Go back to the old look-alike approach and check if and how that was debiased. Thanks in advance
I am looking for long-term writers who can do orders daily. Must be conversant with various writing forms and statistics in SPSS, mathematics and lab reports. I pay $1.2 per 275 words. Payment is made every 14 days. Flexible work environment and readily available wors. Contact me if you agree with these terms and conditions.
create a deep learning model and program with the use of CNN, RNN, LSTM to do Sentiment analysis of the Taobao Product reviews