28 Statistical Computing courses in Bristol delivered Online

Overview This comprehensive course on Statistical Analysis will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Statistical Analysis comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? At the end of the course there will be an online written test, which you can take either during or after the course. After successfully completing the test you will be able to order your certificate, these are included in the price. Who is This course for? There is no experience or previous qualifications required for enrolment on this Statistical Analysis. It is available to all students, of all academic backgrounds. Requirements Our Statistical Analysis is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 14 sections • 16 lectures • 06:28:00 total length •The Realm Of Statistics: 00:26:00 •Basic Statistical Terms: 00:41:00 •The Center of the Data: 00:07:00 •Data Variability: 00:15:00 •Binomial and Normal Distributions: 00:14:00 •Binomial Probabilities Table: 00:14:00 •Z-Table: 00:04:00 •Introduction to Probability: 00:35:00 •Estimates and Intervals: 00:34:00 •Hypothesis Testing: 00:31:00 •Regression Analysis: 00:11:00 •Algorithms, Analytics and Prediction: 00:47:00 •Learning From Experience: The Bayesian Way: 00:31:00 •Doing Statistics: The Wrong Way: 00:37:00 •How We Can Do Statistics Better: 00:41:00 •Assignment - Statistics Essentials: 00:00:00

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Get involved in a learning adventure, mastering R from foundational basics to advanced techniques. This course is a gateway to the realm of data science. Explore statistical machine learning models and intricacies of deep learning and create interactive Shiny apps. Unleash the power of R and elevate your proficiency in data-driven decision-making.

Duration 2 Days 12 CPD hours This course is intended for New users of IBM SPSS Statistics Users who want to refresh their knowledge about IBM SPSS Statistics Anyone who is considering purchasing IBM SPSS Statistics Overview Introduction to IBM SPSS Statistics Review basic concepts in IBM SPSS Statistics Identify the steps in the research process Review basic analyses Use Help Reading data and defining metadata Overview of data sources Read from text files Read data from Microsoft Excel Read data from databases Define variable properties Selecting cases for analyses Select cases for analyses Run analyses for groups Apply report authoring styles Transforming variables Compute variables Recode values of categorical and scale variables Create a numeric variable from a string variable Using functions to transform variables Use statistical functions Use logical functions Use missing value functions Use conversion functions Use system variables Use the Date and Time Wizard Setting the unit of analysis Remove duplicate cases Create aggregate datasets Restructure datasets Merging data files Add cases from one dataset to another Add variables from one dataset to another Enrich a dataset with aggregated information Summarizing individual variables Define levels of measurement Summarizing categorical variables Summarizing scale variables Describing the relationship between variables Choose the appropriate procedure Summarize the relationship between categorical variables Summarize the relationship between a scale and a categorical variable Creating presentation ready tables with Custom Tables Identify table layouts Create tables for variables with shared categories Create tables for multiple response questions Customizing pivot tables Perform Automated Output Modification Customize pivot tables Use table templates Export pivot tables to other applications Working with syntax Use syntax to automate analyses Create, edit, and run syntax Shortcuts in the Syntax Editor Controlling the IBM SPSS Statistics environment Set options for output Set options for variables display Set options for default working folders This course guides students through the fundamentals of using IBM SPSS Statistics for typical data analysis. Students will learn the basics of reading data, data definition, data modification, data analysis, and presentation of analytical results. In addition to the fundamentals, students will learn shortcuts that will help them save time. This course uses the IBM SPSS Statistics Base; one section presents an add-on module, IBM SPSS Custom Tables. Introduction to IBM SPSS Statistics Review basic concepts in IBM SPSS Statistics Identify the steps in the research process Review basic analyses Use Help Reading data and defining metadata Overview of data sources Read from text files Read data from Microsoft Excel Read data from databases Define variable properties Selecting cases for analyses Select cases for analyses Run analyses for groups Apply report authoring styles Transforming variables Compute variables Recode values of categorical and scale variables Create a numeric variable from a string variable Using functions to transform variables Use statistical functions Use logical functions Use missing value functions Use conversion functions Use system variables Use the Date and Time Wizard Setting the unit of analysis Remove duplicate cases Create aggregate datasets Restructure datasets Merging data files Add cases from one dataset to another Add variables from one dataset to another Enrich a dataset with aggregated information Summarizing individual variables Define levels of measurement Summarizing categorical variables Summarizing scale variables Describing the relationship between variables Choose the appropriate procedure Summarize the relationship between categorical variables Summarize the relationship between a scale and a categorical variable Creating presentation ready tables with Custom Tables Identify table layouts Create tables for variables with shared categories Create tables for multiple response questions Customizing pivot tables Perform Automated Output Modification Customize pivot tables Use table templates Export pivot tables to other applications Working with syntax Use syntax to automate analyses Create, edit, and run syntax Shortcuts in the Syntax Editor Controlling the IBM SPSS Statistics environment Set options for output Set options for variables display Set options for default working folders Additional course details: Nexus Humans 0G53BG IBM SPSS Statistics Essentials (V26) training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the 0G53BG IBM SPSS Statistics Essentials (V26) course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Are you ready to take your data analysis skills to the next level? Introducing the Statistical Analysis and Data Science bundle - the ultimate collection of courses for anyone looking to dive deeper into the world of data. The bundle features a QLS-endorsed course, which means you will receive a QLS hardcopy certificate upon completion. This certificate is a mark of quality and can help you stand out in a competitive job market. But that's not all - the bundle also includes 10 other relevant courses, all CPD-QS accredited, to ensure you have a comprehensive understanding of statistical analysis and data science. You'll learn everything from the basics of statistical analysis to advanced SAS programming and big data analytics. Our courses were designed by people who are passionate about sharing their knowledge with you. With our easy-to-follow modules, you'll be able to learn at your own pace and from the comfort of your own home. Whether you're a seasoned data analyst looking to expand your skills or a newcomer to the field, the Statistical Analysis and Data Science bundle has everything you need to succeed. So why wait? Enrol now and take the first step towards becoming a data analysis expert! This Diploma in Statistical Analysis at QLS Level 5 Bundle Package includes: Course 01: Diploma in Statistical Analysis at QLS Level 5 10 Premium Additional CPD QS Accredited Courses - Course 01: Data Analytics with Tableau Course 02: Big Data Analytics with PySpark Tableau Desktop and MongoDB Course 03: Data Science & Machine Learning with R Training Course 04: SQL for Data Science, Data Analytics and Data Visualization Course 05: Advanced SAS Programming Using MacrosSQL Course 06: SQL NoSQL Big Data and Hadoop Course 07: Statistical Concepts and Application with R Course 08: Business Data Analysis Course 09: Business Intelligence and Data Mining Diploma Course 10: Data Analysis In Excel Why Prefer This Statistical Analysis and Data Science Bundle? You will receive a completely free certificate from the Quality Licence Scheme Option to purchase 10 additional certificates accredited by CPD Get a free Student ID Card - (£10 postal charges will be applicable for international delivery) Free assessments and immediate success results 24/7 Tutor Support After taking this Statistical Analysis and Data Science bundle courses, you will be able to learn: Develop a comprehensive understanding of statistical analysis and data science principles Gain expertise in data analytics tools such as Tableau, PySpark, MongoDB, R, SQL, SAS, and Hadoop Learn advanced data science techniques, including machine learning, data mining, and business intelligence Acquire skills in data visualisation, data cleansing, and data analysis in Excel Apply statistical concepts and methods to real-world scenarios Build a strong foundation in data-driven decision-making Develop problem-solving skills and learn how to make data-driven decisions ***Curriculum breakdown of Statistical Analysis*** Module 01: The Realm of Statistics Module 02: Basic Statistical Terms Module 03: The Center of the Data Module 04: Data Variability Module 05: Binomial and Normal Distributions Module 06: Introduction to Probability Module 07: Estimates and Intervals Module 08: Hypothesis Testing Module 09: Regression Analysis Module 10: Algorithms, Analytics and Predictions Module 11: Learning From Experience: The Bayesian Way Module 12: Doing Statistics: The Wrong Way Module 13: How We Can Do Statistics Better How is the Statistical Analysis and Data ScienceBundle Assessment Process? You have to complete the assignment questions given at the end of the course and score a minimum of 60% to pass each exam. Our expert trainers will assess your assignment and give you feedback after you submit the assignment. You will be entitled to claim a certificate endorsed by the Quality Licence Scheme after you successfully pass the exams. CPD 250 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Professionals looking to expand their skills in data analysis Students interested in a career in data science and analytics Entrepreneurs looking to make data-driven decisions Anyone interested in learning statistical analysis and data science principles Career path Our courses will prepare you for a range of careers, including: Data Analyst: £25,000 - £40,000 Business Analyst: £30,000 - £50,000 Data Scientist: £40,000 - £70,000 Business Intelligence Analyst: £35,000 - £55,000 Big Data Engineer: £50,000 - £80,000 Data Warehouse Architect: £60,000 - £100,000 Certificates CPD QS Accredited Certificate Digital certificate - Included Upon successfully completing the Bundle, you will need to place an order to receive a PDF Certificate for each course within the bundle. These certificates serve as proof of your newly acquired skills, accredited by CPD QS. Also, the certificates are recognised throughout the UK and internationally. CPD QS Accredited Certificate Hard copy certificate - Included International students are subject to a £10 delivery fee for their orders, based on their location. Diploma in Statistical Analysis at QLS Level 5 Hard copy certificate - Included

About Course Master the statistical skills you need to understand and analyze biomedical research data with this Biostatistics Online Course Are you working on public health, clinical medicine, biology or related fields? Are you familiar with the process of obtaining an accurate picture from a large number of data points? This Biostatistics Online Course demonstrates how to use statistical techniques to summarize the characteristics of a data set to draw meaningful conclusions. In this course, you will learn all about Biostatistics and its application in medical and life sciences. This course is a comprehensive introduction to the field of biostatistics, covering a wide range of topics from basic statistical concepts to more advanced biostatistical methods.Biostatistics Online Course modules: Module 1: Introduction to Biostatistics This module provides an overview of biostatistics, its applications in the field of health sciences, and the different types of study designs used in biomedical research. It also introduces the basic concepts of statistics, including data types, variables, inferential statistics, hypothesis testing, and the role of statistics in biostatistics and evidence-based medicine. Module 2: Probability This module covers the basics of probability, including probability distributions, random variables, and sampling distributions. Students will learn how to calculate and interpret probabilities in the context of biomedical research. Module 3: Descriptive Statistics This module covers the different measures of central tendency and variability, as well as graphical representations of data. Students will learn how to describe and summarize data from biomedical studies using these methods. Module 4: Inferential Statistics This module covers the fundamental concepts of inferential statistics, including estimation, hypothesis testing, confidence intervals, and p-values. Students will learn how to use these methods to draw conclusions about populations based on data from samples. Module 5: Regression Analysis This module introduces the basics of regression analysis, including simple linear regression, multiple linear regression, and logistic regression. Students will learn how to use these methods to model relationships between variables and to make predictions. Module 6: Biostatistics Tools This module covers a variety of biostatistical tools that are commonly used in biomedical research, including survival analysis, clinical trials, and epidemiological studies. Students will learn how to use these tools to answer specific research questions. Module 7: Statistical Software and Tools This module introduces students to popular statistical software programs, such as R and SPSS. Students will learn how to import, manage, and analyze data using these software programs, as well as how to perform statistical tests and generate summary statistics. Module 8: Ethical Considerations and Reporting Guidelines This module covers the importance of ethical considerations in biostatistics and the reporting guidelines for statistical analysis in research publications. Students will also learn about best practices for data management and data sharing. Why You Should Take This Course Whether you are a student, researcher, or healthcare professional, biostatistics is an essential skill for understanding and interpreting biomedical research. This course provides a comprehensive and accessible introduction to the field of biostatistics, covering all the essential topics that you need to know. By taking this course, you will learn how to: Design and conduct biomedical studies Collect and manage data Analyze data using statistical methods Interpret statistical results Communicate statistical findings effectively This course is ideal for students in the fields of public health, medicine, nursing, epidemiology, and other health sciences. It is also beneficial for researchers, healthcare professionals, and anyone else who wants to learn more about biostatistics. Enroll today and start your journey to becoming a biostatistics expert! To find more course in this topic, search more . What Will You Learn? Design and conduct biomedical studies Collect and manage data Analyze data using statistical methods Interpret statistical results Communicate statistical findings effectively Course Content Introduction to Biostatistics Introduction to Biostatistics Probability Module 2 Probability Descriptive Statistics Descriptive Statistics Inferential Statistics Inferential Statistics Regression Analysis Regression Analysis Biostatistics Tools Biostatistics Tools Statistical Software and Tools Statistical Software and Tools Ethical Considerations and Reporting Guidelines Ethical Considerations and Reporting Guidelines A course by Xpert Learning RequirementsBasic understanding of Mathematics and Statistics Audience Students in health sciences Researchers Healthcare professionals Anyone interested in learning about biostatistics Audience Students in health sciences Researchers Healthcare professionals Anyone interested in learning about biostatistics

Duration 5 Days 30 CPD hours This course is intended for This course is designed for students who want to learn the R programming language, particularly students who want to leverage R for data analysis and data science tasks in their organization. The course is also designed for students with an interest in applying statistics to real-world problems. A typical student in this course should have several years of experience with computing technology, along with a proficiency in at least one other programming language. Overview In this course, you will use R to perform common data science tasks.You will: Set up an R development environment and execute simple code. Perform operations on atomic data types in R, including characters, numbers, and logicals. Perform operations on data structures in R, including vectors, lists, and data frames. Write conditional statements and loops. Structure code for reuse with functions and packages. Manage data by loading and saving datasets, manipulating data frames, and more. Analyze data through exploratory analysis, statistical analysis, and more. Create and format data visualizations using base R and ggplot2. Create simple statistical models from data. In our data-driven world, organizations need the right tools to extract valuable insights from that data. The R programming language is one of the tools at the forefront of data science. Its robust set of packages and statistical functions makes it a powerful choice for analyzing data, manipulating data, performing statistical tests on data, and creating predictive models from data. Likewise, R is notable for its strong data visualization tools, enabling you to create high-quality graphs and plots that are incredibly customizable. This course will teach you the fundamentals of programming in R to get you started. It will also teach you how to use R to perform common data science tasks and achieve data-driven results for the business. Lesson 1: Setting Up R and Executing Simple Code Topic A: Set Up the R Development Environment Topic B: Write R Statements Lesson 2: Processing Atomic Data Types Topic A: Process Characters Topic B: Process Numbers Topic C: Process Logicals Lesson 3: Processing Data Structures Topic A: Process Vectors Topic B: Process Factors Topic C: Process Data Frames Topic D: Subset Data Structures Lesson 4: Writing Conditional Statements and Loops Topic A: Write Conditional Statements Topic B: Write Loops Lesson 5: Structuring Code for Reuse Topic A: Define and Call Functions Topic B: Apply Loop Functions Topic C: Manage R Packages Lesson 6: Managing Data in R Topic A: Load Data Topic B: Save Data Topic C: Manipulate Data Frames Using Base R Topic D: Manipulate Data Frames Using dplyr Topic E: Handle Dates and Times Lesson 7: Analyzing Data in R Topic A: Examine Data Topic B: Explore the Underlying Distribution of Data Topic C: Identify Missing Values Lesson 8: Visualizing Data in R Topic A: Plot Data Using Base R Functions Topic B: Plot Data Using ggplot2 Topic C: Format Plots in ggplot2 Topic D: Create Combination Plots Lesson 9: Modeling Data in R Topic A: Create Statistical Models in R Topic B: Create Machine Learning Models in R