Statistics for Data Analysis Using Excel 2016

Please feel free to save or share this link to refer back to this offering. For in depth information or for scheduling, please visit the activity site directly as detailed in the activity description.
04 Jun

Statistics for Data Analysis Using Excel 2016

Statistics for Data Analysis Using Excel 2016

Tuesday, June 4, 2024 (12:00 AM) to Sunday, May 31, 2026 (11:59 PM)
14 PDCs
Provider: Quality Gurus Inc
Course Name: Statistics for Data Analysis Using Excel 2016

Speaker: Sandeep Kumar
Program Type: Videoconferences, webcasts, audiocasts, podcasts, eBooks, self-directed E-Learning
Registration URL: https://www.qualitygurus.com/link/excel/

Email Details

By the end of this course, participants will be able to: Understand Basic and Advanced Statistical Concepts: Grasp fundamental concepts in both descriptive and inferential statistics. Explain and apply statistical theories to solve real-world business problems. Utilize Microsoft Excel for Statistical Analysis: Perform statistical calculations using Microsoft Excel. Use Excel functions and tools to streamline data analysis and eliminate the need for memorizing complex formulas. Conduct Descriptive Statistics: Calculate and interpret measures of central tendency (mean, mode, median). Compute measures of spread (quartiles, range, interquartile range, standard deviation). Visualize Data Effectively: Create and interpret histograms, box and whisker plots, and scatter plots. Use data visualization techniques to understand data distribution and identify patterns. Apply Probability Concepts: Understand and calculate basic probability, permutations, and combinations. Explore and apply probability distributions such as normal, binomial, and Poisson distributions. Differentiate Between Populations and Samples: Explain the difference between populations and samples. Apply various sampling techniques to gather representative data for analysis. Conduct Hypothesis Testing: Perform one-sample and two-sample hypothesis tests using z-tests, t-tests, p-tests, F-tests, and Chi-Square tests. Interpret p-values and understand their significance in hypothesis testing. Perform Analysis of Variance (ANOVA): Conduct ANOVA manually and using Excel to compare multiple sample means. Understand and interpret ANOVA results to identify significant differences between groups. Make Data-Driven Decisions: Analyze vast amounts of data to extract meaningful insights. Use statistical analysis to make informed, fact-based decisions in a business context. Enhance Data Analysis Skills: Develop a systematic approach to data analysis using statistical methods. Gain proficiency in using Excel for advanced data analysis tasks. Participants will leave the course with a thorough understanding of statistics and the practical skills to perform comprehensive data analysis using Microsoft Excel. They will be equipped to apply statistical techniques to solve business problems and make informed decisions based on data insights.

You're Registered!
Welcome to "Statistics for Data Analysis Using Excel 2016," a comprehensive course designed to teach you both descriptive and inferential statistics through simple yet practical examples. This course will show you how to harness the power of Microsoft Excel to perform statistical calculations effortlessly, eliminating the need to memorize long formulas and equations. By the end of this course, you will be able to use statistics to solve business problems and make fact-based decisions. What You'll Learn: Descriptive and Inferential Statistics: Understand and apply statistical concepts from basic to advanced levels. Microsoft Excel Proficiency: Use Excel to perform statistical calculations, making data analysis straightforward and efficient. Data Interpretation: Make sense of vast amounts of data to make informed decisions based on factual analysis. Data Visualization: Learn to create and interpret histograms, box and whisker plots, and scatter plots to visualize data effectively. Course Structure: This course includes video lectures, practical exercises, and examples to help you understand and apply statistical concepts using Microsoft Excel. Detailed Topics Covered: Section 1: Introduction to Statistics and Data Analysis Basic Concepts: Learn the foundational concepts of statistics and data analysis. Excel for Data Analysis: Get introduced to using Excel for statistical calculations and data analysis. Section 2: Descriptive Statistics Measures of Central Tendency: Calculate and interpret mean, mode, and median. Measures of Spread: Understand and compute quartiles, range, interquartile range, and standard deviation. Section 3: Data Visualization Histograms: Create and interpret histograms to understand data distribution. Box and Whisker Plots: Use box plots to visualize data spread and identify outliers. Scatter Plots: Analyze relationships between variables using scatter plots. Section 4: Probability Basic Probability Concepts: Understand permutations, combinations, and basic probability. Probability Distributions: Explore normal, binomial, and Poisson distributions and their applications. Section 5: Population and Sampling Understanding Populations and Samples: Learn the difference between populations and samples. Sampling Techniques: Discover various sampling methods and their importance in statistics. Section 6: Hypothesis Testing One Sample Tests: Conduct one-sample z-tests, t-tests, and p-tests. Two Sample Tests: Perform two-sample z-tests, t-tests, and p-tests. F Test and Chi-Square Test: Understand and apply these tests for hypothesis testing. Section 7: Analysis of Variance (ANOVA) ANOVA Basics: Learn to perform Analysis of Variance (ANOVA) step by step. Manual Calculations and Excel: Conduct ANOVA calculations manually and using Excel to understand the process thoroughly. Testimonials: What are other students saying about this course? ★★★★★ "Very structured and clear lessons on how each Excel function can be used for different statistical analysis. I have benefited tremendously from attending this course." - Kang Han Qi ★★★★★ "I have learned a lot already and it is still a long way to go!" - Dennis Dominic Mendoza ★★★★★ "Great course, great synergy between theory and practical use." - Patrick Silangit ★★★★★ "This is awesome and really easy to understand the statistical concepts without any stress for a guy like me who used to fail in math classes." - Lester Deepak Martis ★★★★★ "He's better than all my university lecturers, very clear, concise, and seamless progression of the evolution of concepts in a systematic way that makes it easy to understand...Bravo!!" - Ayanda Peter ★★★★★ "A well-planned curriculum, fantastic resources for downloads, professionally presented slides, very easy to understand, truly the best course for every financial analyst." - Arumugam K Chandrasekar ★★★★★ "I am a fan of his teachings. It is recommended to every other person who is not confident in Statistics and wants to be a pro." - Apnatav Bhatia ★★★★★ "Brilliant course. Takes the difficult, sometimes even boring statistics model and breaks them into easy bite-sized portions. Explains the theory behind it and then the Excel way of doing it." - Karthikeyan Stalin ★★★★★ "The self-study step by step and the Excel examples are very great. I can follow the course and practice on my computer alongside. Thank you for putting this whole thing together. Not a very exciting subject to teach so I appreciate being able to put this long course together to make it easy for people like us to utilize and study." - Dr. Stanley Adjabeng Who This Course Is For: Business Analysts Data Analysts Financial Analysts Students and professionals looking to enhance their data analysis skills using Excel Anyone interested in learning statistics to make data-driven decisions