Iain Pardoe - Applied Regression Modeling

Здесь есть возможность читать онлайн «Iain Pardoe - Applied Regression Modeling» — ознакомительный отрывок электронной книги совершенно бесплатно, а после прочтения отрывка купить полную версию. В некоторых случаях можно слушать аудио, скачать через торрент в формате fb2 и присутствует краткое содержание. Жанр: unrecognised, на английском языке. Описание произведения, (предисловие) а так же отзывы посетителей доступны на портале библиотеки ЛибКат.

Applied Regression Modeling: краткое содержание, описание и аннотация

Предлагаем к чтению аннотацию, описание, краткое содержание или предисловие (зависит от того, что написал сам автор книги «Applied Regression Modeling»). Если вы не нашли необходимую информацию о книге — напишите в комментариях, мы постараемся отыскать её.

Master the fundamentals of regression without learning calculus with this one-stop resource The newly and thoroughly revised 3rd Edition of
delivers a concise but comprehensive treatment of the application of statistical regression analysis for those with little or no background in calculus. Accomplished instructor and author Dr. Iain Pardoe has reworked many of the more challenging topics, included learning outcomes and additional end-of-chapter exercises, and added coverage of several brand-new topics including multiple linear regression using matrices.
The methods described in the text are clearly illustrated with multi-format datasets available on the book's supplementary website. In addition to a fulsome explanation of foundational regression techniques, the book introduces modeling extensions that illustrate advanced regression strategies, including model building, logistic regression, Poisson regression, discrete choice models, multilevel models, Bayesian modeling, and time series forecasting. Illustrations, graphs, and computer software output appear throughout the book to assist readers in understanding and retaining the more complex content.
covers a wide variety of topics, like:
Simple linear regression models, including the least squares criterion, how to evaluate model fit, and estimation/prediction Multiple linear regression, including testing regression parameters, checking model assumptions graphically, and testing model assumptions numerically Regression model building, including predictor and response variable transformations, qualitative predictors, and regression pitfalls Three fully described case studies, including one each on home prices, vehicle fuel efficiency, and pharmaceutical patches Perfect for students of any undergraduate statistics course in which regression analysis is a main focus,
also belongs on the bookshelves of non-statistics graduate students, including MBAs, and for students of vocational, professional, and applied courses like data science and machine learning.

Applied Regression Modeling — читать онлайн ознакомительный отрывок

Ниже представлен текст книги, разбитый по страницам. Система сохранения места последней прочитанной страницы, позволяет с удобством читать онлайн бесплатно книгу «Applied Regression Modeling», без необходимости каждый раз заново искать на чём Вы остановились. Поставьте закладку, и сможете в любой момент перейти на страницу, на которой закончили чтение.

Тёмная тема
Сбросить

Интервал:

Закладка:

Сделать
The difference from earlier calculations is that this time is the focus of - фото 262

The difference from earlier calculations is that this time картинка 263is the focus of inference, so we have not assumed that we know its value. One consequence for the probability calculation is that in the fourth line we have “ картинка 264.” To change this to “ картинка 265” in the fifth line, we multiply each side of the inequality sign by “ картинка 266” (this also has the effect of changing the direction of the inequality sign).

This probability statement must be true for all potential values of Applied Regression Modeling - изображение 267and Applied Regression Modeling - изображение 268. In particular, it must be true for our observed sample statistics, Applied Regression Modeling - изображение 269and Applied Regression Modeling - изображение 270. Thus, to find the values of that satisfy the probability statement we plug in our sample statistics to - фото 271that satisfy the probability statement, we plug in our sample statistics to find

This shows that a population mean greater than would satisfy the expression - фото 272

This shows that a population mean greater than would satisfy the expression In other words we have found that the lower - фото 273would satisfy the expression In other words we have found that the lower bound of our confidence interval - фото 274. In other words, we have found that the lower bound of our confidence interval is картинка 275, or approximately The value 201115 in this calculation is the margin of error To find the - фото 276. The value 20.1115 in this calculation is the margin of error.

To find the upper bound, we perform a similar calculation:

To find the values of that satisfy this expression we plug in our sample - фото 277

To find the values of that satisfy this expression we plug in our sample statistics to find This - фото 278that satisfy this expression, we plug in our sample statistics to find

This shows that a population mean less than would satisfy the expression - фото 279

This shows that a population mean less than would satisfy the expression In other words we have found that the upper - фото 280would satisfy the expression In other words we have found that the upper bound of our confidence interval - фото 281. In other words, we have found that the upper bound of our confidence interval is картинка 282, or approximately Again the value 201115 in this calculation is the margin of error We can - фото 283. Again, the value 20.1115 in this calculation is the margin of error.

We can write these two calculations a little more concisely as

As before we plug in our sample statistics to find the values of that satisfy - фото 284

As before, we plug in our sample statistics to find the values of that satisfy this expression This shows that a population mean between - фото 285that satisfy this expression:

This shows that a population mean between and would satisfy the expression - фото 286

This shows that a population mean between and would satisfy the expression In other words we have found that a 95 co - фото 287and would satisfy the expression In other words we have found that a 95 - фото 288would satisfy the expression In other words we have found that a 95 confidence interval for for this - фото 289. In other words, we have found that a 95% confidence interval for картинка 290for this example is ( картинка 291, картинка 292), or approximately ( картинка 293, картинка 294). It is traditional to write confidence intervals with the lower number on the left.

More generally, using symbols, a 95% confidence interval for a univariate population mean, results from the following where the 975th percentile comes from the - фото 295, results from the following:

where the 975th percentile comes from the tdistribution with degrees of - фото 296

where the 97.5th percentile comes from the t‐distribution with картинка 297degrees of freedom. In other words, plugging in our observed sample statistics, and we can write the 95 confidence interval as In this expression - фото 298and we can write the 95 confidence interval as In this expression is the - фото 299, we can write the 95% confidence interval as In this expression is the margin of error For a lower or higher level of - фото 300. In this expression, is the margin of error For a lower or higher level of confidence than 95 the - фото 301is the margin of error.

Читать дальше
Тёмная тема
Сбросить

Интервал:

Закладка:

Сделать

Похожие книги на «Applied Regression Modeling»

Представляем Вашему вниманию похожие книги на «Applied Regression Modeling» списком для выбора. Мы отобрали схожую по названию и смыслу литературу в надежде предоставить читателям больше вариантов отыскать новые, интересные, ещё непрочитанные произведения.


Отзывы о книге «Applied Regression Modeling»

Обсуждение, отзывы о книге «Applied Regression Modeling» и просто собственные мнения читателей. Оставьте ваши комментарии, напишите, что Вы думаете о произведении, его смысле или главных героях. Укажите что конкретно понравилось, а что нет, и почему Вы так считаете.

x