Biostatistik: Eine Einführung für Biologen und by Wolfgang Köhler

By Wolfgang Köhler

Die Auswertung experimenteller Ergebnisse ist für Biologen und Agrarwissenschaftler ein wichtiges Handwerkszeug. Mit dieser intestine verständlichen Einführung in Grundlagen und Anwendungen der Biometrie ist ein schneller Einstieg in die Statistik möglich. Soweit wie möglich wird ohne Formeln und mathematische Symbolik die hinter den Verfahren stehende Grundidee komplexer statistischer Verfahren erläutert. Die five. Auflage enthält zusätzlich Schemata zur Versuchsplanung und Auswertung sowie ein erweitertes Glossar englischer Fachausdrücke.

Table of Contents

Cover

Biostatistik - Eine Einführung für Biologen und Agrarwissenschaftler,
Fünfte, aktualisierte und erweiterte Auflage

ISBN 9783642292705 eISBN 9783642292712

Vorwort zur five. Auflage

Vorwort zur 1. Auflage

Inhaltsverzeichnis

Einleitung

Kapitel I: Merkmalsauswahl

§1 Wahl geeigneter Merkmale
1.1 Objektivität, Reliabilität, Validität
1.2 Die verschiedenen Skalen-Niveaus

Kapitel II: Beschreibende Statistik

§2 Tabellen zur Darstellung monovariabler Verteilungen
§3 Graphische Darstellung monovariabler Verteilungen
3.1 Verschiedene Arten graphischer Darstellung
3.2 Die Schaubilder einiger Verteilungstypen
3.3 Das Summenhäufigkeits-Polygon
3.4 ... als die Bilder lügen lernten
§4 Charakteristische Maßzahlen monovariabler Verteilungen
4.1 Die Lageparameter
4.2 Die Streuungsmaße
4.3 Zur Anwendung der eingeführten Maßzahlen
§5 Graphische Darstellung bivariabler Verteilungen
§6 Zur Korrelationsanalyse
6.1 Der Pearsonsche Maßkorrelationskoeffizient
6.2 Das Bestimmtheitsmaß
6.3 Zur Interpretation von Korrelationskoeffizient und
Bestimmtheitsmaß
6.4 Der Spearmansche Rangkorrelationskoeffizient
6.5 Der Kontingenzkoeffizient
§7 Zur Regressionsrechnung
7.1 Die Ermittlung einer Geradengleichung
7.2 Einige Achsentransformationen
7.3 Einige Datentransformationen

Kapitel III: Einführung in die schließende Statistik

§8 Grundgedanken zur Test-Theorie
8.1 Zielsetzung statistischer Tests
8.2 Fehler 1. paintings und 2. Art
8.3 Einseitige und zweiseitige Fragestellung
8.4 Prüfstatistik und Prüfverteilung
8.5 Vorgehen bei statistischen Tests
§9 Eine Auswahl wichtiger Tests
9.1 assessments bei normalverteilten Grundgesamtheiten
9.2 checks zu ordinalskalierten Daten (Rangtests)
9.3 assessments zu nominalskalierten Daten
§10 Vertrauensbereiche
10.1 Konfidenzintervalle für bei Normalverteilung
10.2 Konfidenzintervalle für die Differenz von _x und _y bei
Normalverteilung

Kapitel IV: Varianzanalyse bei normalverteilten Gesamtheiten

§11 Grundgedanken zur Varianzanalyse
11.1 Zerlegung der Varianz nach Streuungsursachen
11.2 Unterscheidung in feste und zufällige Effekte
§12 Einfaktorielle Varianzanalyse (Modell I)
12.1 Mathematische Bezeichnungen
12.2 Zu den Voraussetzungen der Varianzanalyse
12.3 Zerlegung in Streuungskomponenten
12.4 Durchführung der einfaktoriellen Varianzanalyse (Modell
I)
§13 Zweifaktorielle Varianzanalyse (Modell I)
13.1 Das zweifaktorielle Modell
13.2 Durchführung der zweifaktoriellen ANOVA (mehrfache
Besetzung, Modell I)
13.3 Die zweifaktorielle ANOVA ohne Wiederholungen (Modell I)
§14 Prüfung der Voraussetzungen
14.1 Zwei exams auf Varianzhomogenität
§15 a number of Mittelwertvergleiche
15.1 Einige A-priori-Testverfahren
15.2 Einige A-posteriori-Testverfahren
15.3 Anschlusstests bei signifikanten Wechselwirkungen
§16 Varianzanalyse mit zufälligen Effekten (Modell II)
16.1 Einfaktorielle Varianzanalyse mit zufälligen Effekten
(Modell II)
16.2 Zweifaktorielle Varianzanalyse mit zufälligen Effekten
(Modell II)
16.3 Zweifaktorielle Varianzanalyse mit festen und zufälligen
Effekten (gemischtes Modell)

Kapitel V: Varianzanalyse bei ordinalskalierten Daten

§17 Parameterfreie Verfahren für mehrere unabhängige Stichproben
17.1 Der H-Test (Kruskal-Wallis)
17.2 Der Nemenyi-Test für a number of Vergleiche
§18 Parameterfreie Verfahren für mehrere verbundene Stichproben
18.1 Der Friedman-Test (Rangvarianzanalyse)
18.2 Der Wilcoxon-Wilcox-Test für a number of Vergleiche

Kapitel VI: Regressionsanalyse

§19 Grundgedanken zur Regressionsanalyse
19.1 Interessierende Fragestellungen
19.2 Zu den Voraussetzungen einer Regressionsanalyse
19.3 Mathematische Bezeichnungen
§20 Lineare Regression bei einfacher Besetzung
20.1 Signifikanzprüfung auf Anstieg
20.2 Berechnung von Konfidenzintervallen
20.3 Durchführung der Regressionsanalyse (ohne Wiederholung)
§21 Lineare Regression bei mehrfacher Besetzung
21.1 Prüfung der Linearität
21.2 Durchführung der Regressionsanalyse (mit Wiederholung)
§22 Ergänzungen zur Varianz- und Regressionsanalyse
22.1 Zur Kovarianzanalyse
22.2 Zur multiplen linearen Regression

Kapitel VII: Resampling-basierte Inferenzstatistik

§23 Drei Randomisierungs-Verfahren
23.1 Permutations-Tests
23.2 Die Jackknife-Methode
23.3 Die Bootstrap-Methode

Kapitel VIII: Zur Versuchsplanung

§24 Am Anfang sollte die Versuchsplanung stehen
24.1 Treffgenauigkeit und Präzision
24.2 Einige Grundsätze der Versuchsplanung
24.3 Verschiedene Versuchsanordnungen
24.4 Zur Wahl des Stichprobenumfangs

Kapitel IX: Einige Grundlagen der Wahrscheinlichkeitsrechnung

§25 Bezeichnungen, Axiome, Rechenregeln
25.1 Zufallsereignisse
25.2 Der Wahrscheinlichkeitsbegriff
25.3 Die axiomatische Definition der Wahrscheinlichkeit
25.4 Bedingte Wahrscheinlichkeit und Unabhängigkeit
25.5 Zufallsvariable
25.6 Kombinatorik oder die Kunst des Abzählens
§26 Wahrscheinlichkeitsverteilungen
26.1 Zur Binomialverteilung
26.2 Zur Poissonverteilung
26.3 Zur Normalverteilung
26.4 Standardnormalverteilung und z-Transformation
§27 Prüfverteilungen
27.1 Die Normalverteilung als Prüfverteilung
27.2 Zur t-Verteilung von Student
27.3 Zur 2-Verteilung
27.4 Zur F-Verteilung

Anhang A: Schemata zur Versuchsplanung und Auswertung

Anhang B: Tabellen

Auswahl englischer Fachausdrücke

Literaturverzeichnis

Sachverzeichnis

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