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Books on the topic 'Regressione lineare'

Author: Grafiati

Published: 4 June 2021

Last updated: 21 February 2023

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1

Frost, Irasianty. Einfache lineare Regression. Wiesbaden: Springer Fachmedien Wiesbaden, 2018. http://dx.doi.org/10.1007/978-3-658-19732-2.

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2

Groß, Jürgen. Linear Regression. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-55864-1.

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3

Olive, David J. Linear Regression. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55252-1.

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4

Riedwyl, Hans. Lineare Regression und Verwandtes. Basel: Birkhäuser Basel, 1997. http://dx.doi.org/10.1007/978-3-0348-8897-4.

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5

Weisberg, Sanford. Applied Linear Regression. New York: John Wiley & Sons, Ltd., 2005.

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6

Applied linear regression. 3rd ed. Hoboken, N.J: Wiley-Interscience, 2005.

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7

Applied linear regression. 2nd ed. New York: Wiley, 1985.

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8

Seber, George A. F. Linear regression analysis. 2nd ed. Hoboken, NJ: Wiley-Interscience, 2002.

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9

Weisberg, Sanford. Applied Linear Regression. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471704091.

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10

1946-, Lee A. J., ed. Linear regression analysis. 2nd ed. Hoboken, N.J: Wiley-Interscience, 2003.

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11

T, O'Connell Richard, and Dickey David A, eds. Linear statistical models: An applied approach. Boston: Duxbury Press, 1986.

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12

Bowerman, Bruce L. Linear statistical models: An applied approach. 2nd ed. Boston: PWS-Kent Pub. Co., 1990.

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13

Applied regression analysis, linear models, and related methods. Thousand Oaks, Calif: Sage Publications, 1997.

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14

Chris, Nachtsheim, and Neter John, eds. Applied linear regression models. 4th ed. Boston: McGraw-Hill/Irwin, 2004.

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15

William, Wasserman, and Kutner Michael H, eds. Applied linear regression models. 2nd ed. Homewood, Ill: Irwin, 1989.

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16

Kutner, Michael H. Applied linear regression models. 4th ed. New York, NY: McGraw-Hill, 2003.

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17

Regression and linear models. New York: McGraw-Hill, 1990.

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18

Andersen, Per Kragh, and Lene Theil Skovgaard. Regression with Linear Predictors. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7170-8.

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19

Theil, Skovgaard Lene, and Graversen Therese, eds. Regression with linear predictors. New York: Springer, 2010.

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20

Seber, G. A. F. Nonlinear regression. Hoboken, N.J: Wiley-Interscience, 2003.

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21

1952-, Wild C. J., ed. Nonlinear regression. New York: Wiley, 1989.

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22

Susan, Milton J., ed. A first course in the theory of linear statistical models. Boston: PWS-KENT Pub. Co., 1991.

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23

1953-, Peck Elizabeth A., and Vining G. Geoffrey 1954-, eds. Introduction to linear regression analysis. 5th ed. Hoboken, NJ: Wiley, 2012.

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24

Chatterjee, Samprit. Sensitivity analysis in linear regression. New York: Wiley, 1988.

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25

1953-, Peck Elizabeth A., ed. Introduction to linear regression analysis. 2nd ed. New York: Wiley, 1992.

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26

Fry, John M. (John Michael), 1980-, ed. Regression: Linear models in statistics. London: Springer, 2010.

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27

1953-, Peck Elizabeth A., and Vining G. Geoffrey 1954-, eds. Introduction to linear regression analysis. 3rd ed. New York: Wiley, 2001.

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28

Chatterjee, Samprit, and Ali S. Hadi, eds. Sensitivity Analysis in Linear Regression. Hoboken, NJ, USA: John Wiley & Sons, Inc., 1988. http://dx.doi.org/10.1002/9780470316764.

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29

1953-, Peck Elizabeth A., and Vining G. Geoffrey 1954-, eds. Introduction to linear regression analysis. 4th ed. Hoboken, NJ: Wiley-Interscience, 2006.

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30

Mathematical algorithms for linear regression. Boston: Academic Press, 1991.

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31

1974-, Su Xiaogang, ed. Linear regression analysis: Theory and computing. Hackensack, N.J: World Scientific, 2009.

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32

Mo, Moxiu. Nonparametric estimation by (parametric) linear regression. Toronto: University of Toronto, Dept. of Statistics, 1991.

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33

Gelman, Andrew, and Deborah Nolan. Linear regression and correlation. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198785699.003.0005.

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Abstract:

This chapter addresses the descriptive treatment of linear regression with a single predictor: straight-line fitting, interpretation of the regression line and standard deviation, the confusing phenomenon of “regression to the mean,” correlation, and conducting regressions on the computer. These concepts are illustrated with student discussions and activities. Many examples are of the sort commonly found in statistics textbooks, but the focus here is on how to work the examples into student-participation activities rather than simply examples to be read or shown on the blackboard. Topics include the following relationships: height and income, height and hand span, world population over time, and exam scores.

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34

Linear Regression. Springer, 2003.

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35

Olive, David J. Linear Regression. Springer, 2017.

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36

Groß, Jürgen. Linear Regression. Springer London, Limited, 2012.

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37

Olive, David J. Linear Regression. Springer International Publishing AG, 2018.

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38

Pokropp, Fritz. Lineare Regression und Varianzanalyse. de Gruyter GmbH, Walter, 2015.

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39

Pokropp, Fritz. Lineare Regression und Varianzanalyse. de Gruyter GmbH, Walter, 1994.

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40

Lee, Alan J., and George A. F. Seber. Linear Regression Analysis. Wiley & Sons, Incorporated, John, 2012.

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41

Applied Linear Regression. Wiley & Sons, Incorporated, John, 2014.

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42

Weisberg, Sanford. Applied Linear Regression. Wiley & Sons, Incorporated, John, 2021.

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43

Linear Regression Diagnostics. Franklin Classics, 2018.

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44

Weisberg, S., and Sanford Weisberg. Applied Linear Regression. Wiley & Sons, Incorporated, John, 2005.

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45

Lee, Alan J., and George A. F. Seber. Linear Regression Analysis. Wiley & Sons, Incorporated, John, 2012.

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46

Kuh, Edwin, Roy E. Welsch, and Nber Computer Research Center. Linear Regression Diagnostics. Franklin Classics Trade Press, 2018.

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47

Seber, George A., and Alan J. Lee. Linear Regression Analysis. Wiley & Sons, Incorporated, John, 2012.

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48

Kuh, Edwin, Roy E. Welsch, and NBER Computer Research Center. Linear Regression Diagnostics. Franklin Classics, 2018.

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49

Weisberg, Sanford. Applied Linear Regression. Wiley & Sons, Incorporated, John, 2021.

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50

Weisberg, Sanford. Applied Linear Regression. Wiley & Sons, Incorporated, John, 2021.

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