Statistical Analysis and Modeling in R: Working with Probability Distributions
R Programming 4.0+
| Intermediate
- 12 Videos | 1h 38m 24s
- Includes Assessment
- Earns a Badge
Interpreting data is a core pre-processing step in data analysis and modeling. Use this course to practice using various dynamic statistical tools to explore and understand your data. During this course, you'll explore population distributions to model random variables, work with discrete and continuous probability distributions, and use discrete probability distribution types, such as the uniform, binomial, and Poisson distributions. You'll also examine continuous distributions, such as the normal and the exponential distributions. You'll round the course off by learning how to read and interpret QQ plots, which can be used to compare the distributions of two samples of data. When you're finished, you'll be able to use probability distributions to model events and understand your data.
WHAT YOU WILL LEARN
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discover the key concepts covered in this courserecall the sets of statistical tools used to understand datacompare and contrast population metrics with sample metricsrecall the characteristics of discrete and continuous probability distributionssample and analyze data that follows uniform distributionsample and analyze data which follows binomial distribution
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calculate probabilities of events in the binomial distributionsample and analyze data which follows uniform distributionexamine and interpret normal distributions and exponential distributionsinterpret QQ plots for normally and non-normally distributed datause QQ plots to compare samples from different distributionssummarize the key concepts covered in this course
IN THIS COURSE
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1.Course Overview2m 10sUP NEXT
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2.Statistical Tools for Understanding Data8m 51s
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3.Population and Sample Metric Comparisons7m 37s
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4.Characteristics of Probability Distribution Types11m 52s
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5.Sampling and Analyzing Uniform Distribution Data11m 20s
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6.Sampling and Analyzing Binomial Distribution Data8m 48s
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7.Computing Probabilities in Binomial Distributions10m 20s
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8.Sampling and Analyzing Poisson Distribution Data9m 15s
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9.Examining Normal and Exponential Distributions9m 26s
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10.Interpreting QQ Plots Using R8m 7s
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11.Using QQ Plots in R to Compare Datasets8m 34s
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12.Course Summary2m 4s
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