Ng Das Statistics Ebook Pdf 34
This ebook is an easy-to-digest summary of the concepts found in the ng das statistics textbook. It was created to provide an online reference which can be helpful for students studying Statistics, Data Analysis, and Data Science classes at MIT. This e-book contains statistical concepts covered in chapter 1 through 3, as well as tables surrounding each concept. Some notes are provided at the end of each table to help readers understand where this data came from. Readers should be aware that this is not a text book or handbook for learning methods or theory; it is meant only as a resource to answer questions one might have while reading the textbook. In this eBook, I have tried to avoid any bias or preference towards a particular statistical package or model. Note about Table 1.1: This table was originally created as a word document, and the data from it have been converted into a spreadsheet. This ebook contains all the tables from Chapter 1, which covers basic statistical concepts and terminology, including: how to read a bar graph, mean and standard deviation of a data set, median and mode of a data set, relationship between correlations and covariation/association, characteristics of extreme scores in datasets (e.g., outlier detection), reliability statistics (e.g. confidence interval) and bootstrapping. Other chapters cover: how to read a histogram, the difference between binomial and multinomial models, how to read a scatter plot, measuring dispersion (e.g., spread), confidence intervals for means and standard deviations (including the normal approximation), linear regression (including hand calculations) and goodness of fit tests (e.g., F test). This ebook is an easy-to-digest summary of the concepts found in the ng das statistics textbook. It was created to provide an online reference which can be helpful for students studying Statistics, Data Analysis, and Data Science classes at MIT. This e-book contains tables surrounding each concept in chapter 4 through 6. Some notes are provided at the end of each table to help readers understand where this data came from. Readers should be aware that this is not a text book or handbook for learning methods or theory; it is meant only as a resource to answer questions one might have while reading the textbook. This ebook contains all the tables from Chapter 4, which covers descriptive statistics (i.e., mean, median, mode, standard deviation, variance, covariance), pictorial representation of data-sets (including boxplots and violin plots), measuring skewness/bias of data-sets (including skewness plots) and correlation coefficients (regression analysis). Chapter 5 covers the distribution of sample data (i.e., histograms and boxplots), and chapter 6 covers the relationship between residuals and fitted values (i.e., F-test) and multiple regression examples. This ebook contains all the tables from Chapter 5, which covers probability distributions for data sets, including: how to graph a probability distribution, shape function versus graph, density function versus graph, cumulative distribution functions/probability density functions/normal curves versus probability density curves/Pyramid plots versus histograms.
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