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DEMO - Data Analysis Fundamentals with Excel Course
DEMO - Data Analysis Fundamentals with Excel CourseAnalytics Courses |
| Categories | Most Recent | Top Rated | Popular Courses |
 | Uploader | Date Added | Views | Rating |
| Superadmin | 15.03.16 | 2,149 | No Rating | |
| Description | ||||
| Microsoft Excel is an important tool for information workers that design and perform data analysis. This course provides an overview of the fundamentals, from performing common calculations to conducting Bayesian analysis with Excel. Author Curt Frye starts with the foundational concepts, including an introduction to the central limit theorem, and then shows how to visualize data, relationships, and future results with Excel's histograms, graphs, and charts. He also covers testing hypotheses, modeling different data distributions, and calculating the covariance and correlation between data sets. The course closes with a look at calculating Bayesian probabilities in Excel. Topics include: Calculating mean and median values Analyzing data using variance and standard deviation Minimizing errors Visualizing data with histograms, charts, and more Testing hypotheses Measuring covariance and correlation Performing Bayesian analysis Table of Contents Introduction 3m 13s Welcome 1m 3s What you should know 1m 29s Using the exercise files 41s 1. Foundational Concepts of Data Analysis 28m 22s Calculating mean and median values 6m 28s Measuring maximums, minimums, and other data characteristics 5m 1s Analyzing data using variance and standard deviation 7m 34s Introducing the central limit theorem 1m 13s Analyzing a population using data samples 5m 37s Identifying and minimizing sources of error 2m 29s 2. Visualizing Data 24m 59s Grouping data using histograms 4m 44s Identifying relationships using XY scatter charts 2m 0s Visualizing data using logarithmic scales 4m 27s Adding trendlines to charts 3m 5s Forecasting future results 5m 24s Calculating running averages 5m 19s 3. Testing a Hypothesis 8m 25s Formulating a hypothesis 3m 51s Interpreting the results of your analysis 2m 5s Considering the limits of hypothesis testing 2m 29s 4. Utilizing Data Distributions 28m 53s Using the normal distribution 6m 23s Using the exponential distribution 5m 58s Using a uniform distribution 6m 21s Using the binomial distribution 5m 1s Using the Poisson distribution 5m 10s 5. Measuring Covariance and Correlation 26m 30s Visualizing what covariance means 3m 48s Calculating covariance between two columns of data 5m 8s Calculating covariance among multiple pairs of columns 4m 5s Visualizing what correlation means 6m 8s Calculating correlation between two columns of data 2m 37s Calculating correlation among multiple pairs of columns 4m 44s 6. Performing Bayesian Analysis 22m 18s Introducing Bayesian analysis 2m 28s Analyzing a sample problem: Kahneman's Cabs 4m 26s Creating a classification matrix 4m 40s Calculating Bayesian probabilities in Excel 6m 41s Updating yo1ur Bayesian analysis 4m 3s Conclusion 2m 4s Further resources 2m 4s | ||||
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