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Statistical Inference in Wildlife Science

Statistical Inference in Wildlife Science

Statistical Inference in Wildlife Science Goals Concerns with Nulls Better Approaches? Information-theoretic Metareplication Data dredging Important References Goal of Wildlife Research Gain “reliable knowledge” (Romesburg 1981) Hypothetico-deductive approach is preferred Research

By benjamin
(435 views)

Chapter 3 Making Statistical Inferences

Chapter 3 Making Statistical Inferences

Chapter 3 Making Statistical Inferences. 3.7 The t Distribution 3.8 Hypothesis Testing 3.9 Testing Hypotheses About Single Means. Limitations of the Normal Distribution.

By patia
(271 views)

Educational Research

Educational Research

Educational Research. Chapter 5. Hypothesis. The hypothesis states the expected answer to the research question – knowing that the investigation results will lead to its being supported or not supported – or retention or rejection Example:

By helia
(160 views)

Exact calculations of expected power for the Benjamini-Hochberg procedure

Exact calculations of expected power for the Benjamini-Hochberg procedure

Exact calculations of expected power for the Benjamini-Hochberg procedure. DH Glueck 1 , A Karimpour-Fard 1 , L Hunter 1 , J Mandel 1 and KE Muller 2. 1 University of Colorado Denver and 2 University of Florida. December 1, 2007. Power for multiple comparisons.

By queenie
(127 views)

Reduction of post-slaughter beef loss and application of HACCP in Meat processing centres in Ethiopia PhD Proposal Meles

Reduction of post-slaughter beef loss and application of HACCP in Meat processing centres in Ethiopia PhD Proposal Meles

Reduction of post-slaughter beef loss and application of HACCP in Meat processing centres in Ethiopia PhD Proposal Melese Abdisa. Introduction Food shortage is not only due to failure to produce enough amount per capita It is aggravated when the product is affected by

By arnaldo
(223 views)

Homework, Notes 4 Section 11

Homework, Notes 4 Section 11

Homework, Notes 4 Section 11. Question 1. In class we focused on hypothesis tests for p with IID Bernoulli data. Many of the hypothesis tests you will encounter are for m with iid normal data. Fortunately, this is really easy--if you understand the logic!

By leigh
(116 views)

Class 23: Thursday, Dec. 2nd

Class 23: Thursday, Dec. 2nd

Class 23: Thursday, Dec. 2nd. Today: One-way analysis of variance, multiple comparisons. Next week: Two-way analysis of variance. I will e-mail the final homework, Homework 9, to you this weekend.

By brand
(184 views)

The Problem of Detecting Differentially Expressed Genes

The Problem of Detecting Differentially Expressed Genes

The Problem of Detecting Differentially Expressed Genes. Sample 1. Sample 2. Sample M. Gene 1. Gene 2. . . . . . . . . Gene N. Sample 1. Sample 2. Sample M. Gene 1. Gene 2. . . . . . . . . Gene N. Class 2. Class 1. Fold Change is the Simplest Method

By jalen
(159 views)

Comparing Gene Expression Between Affymetrix Arrays

Comparing Gene Expression Between Affymetrix Arrays

Comparing Gene Expression Between Affymetrix Arrays. Biostat 278 January 22 th , 2008. Identification of “Interesting” Genes. Many different methods for finding differentially expressed genes. Depends on experimental design and outcome measures. Observational Methods. Statistical Methods.

By boone
(137 views)

Overview of Lecture

Overview of Lecture

Overview of Lecture. Factorial Designs Experimental Design Names Partitioning the Variablility The Two-Way Between Groups ANOVA Evaluating the Null Hypotheses Main effects Interactions Analytical Comparisons. Factorial Design. Much experimental psychology asks the question:

By heba
(214 views)

Parallelism among age-incidence curves of metabolic syndrome component disorders

Parallelism among age-incidence curves of metabolic syndrome component disorders

Parallelism among age-incidence curves of metabolic syndrome component disorders. Chen Hsin-Jen. Metabolic syndrome (MS). Definition by Adult Treatment Panel III (USA) Abdominal obesity ( 中廣型肥胖 , AOB) ♂ : waist circumference ≧108cm ♀: waist circumference ≧88cm Hyperglycemia ( 高血糖 , HGlu)

By genica
(151 views)

Goucher College Graduate Programs in Education Kristina Gillmeister

Goucher College Graduate Programs in Education Kristina Gillmeister

The Effect of Instrumental Music Instruction on the Standardized Mathematics Assessment Achievement of Elementary School Students in Grades 3 through 5. Goucher College Graduate Programs in Education Kristina Gillmeister. Background. National crisis in mathematics achievement

By alegria
(151 views)

Vulnerability of moose and roe deer to wolf predation in Scandinavia- does habitat matter?

Vulnerability of moose and roe deer to wolf predation in Scandinavia- does habitat matter?

Vulnerability of moose and roe deer to wolf predation in Scandinavia- does habitat matter?. International Master Programme Applied Biology, 2007 By: Lisette Fritzon. Introduction. Ungulates important prey for wolves Threat against wolf recovery Dramatic growth of prey populations

By sharlene
(123 views)

A 20/20 vision of Reionization and Galaxy formation

A 20/20 vision of Reionization and Galaxy formation

A 20/20 vision of Reionization and Galaxy formation. Sangeeta Malhotra School of Earth and Space Exploration Arizona State University. Why Reionization?. As a watermark for galaxy-formation: 10 ionizing photons per Baryon produced by galaxies. Why Reionization?.

By jordana
(137 views)

Overview of ANOVA

Overview of ANOVA

Overview of ANOVA. ANOVA. Analysis of variance IV referred to as a factor Conditions also called level or treatment, with k representing the number of levels Thus, refer to as treatment effect One-way ANOVA. Why ANOVA ?.

By Jimmy
(130 views)

Determining and Interpreting Associations between Variables

Determining and Interpreting Associations between Variables

Determining and Interpreting Associations between Variables. Cross-Tabs Chi-Square Correlation. Types of Relationships between Variables. Non-monotonic - there is no direction to the relationship. Monotonic - there is a general direction of the relationship. Increasing - +ve relation.

By ostinmannual
(75 views)

Week 2 – PART III

Week 2 – PART III

Week 2 – PART III. POST-HOC TESTS. POST HOC TESTS. When we get a significant F test result in an ANOVA test for a main effect of a factor with more than two levels, this tells us we can reject H o i.e. the samples are not all from populations with the same mean.

By domani
(174 views)

PSY 1950 Post-hoc and Planned Comparisons October 6, 2008

PSY 1950 Post-hoc and Planned Comparisons October 6, 2008

PSY 1950 Post-hoc and Planned Comparisons October 6, 2008. Preamble. Presentations Tutoring Problem 1e: If you decide to reject the null hypothesis, you know the probability that you are making the wrong decision Visual depiction of F-ratio. Subpopulations.

By thalia
(109 views)

We’ll now consider contingency tables , a table which cross-tablulates two categorical variables.

We’ll now consider contingency tables , a table which cross-tablulates two categorical variables.

We’ll now consider contingency tables , a table which cross-tablulates two categorical variables. See Table 5.4.1 on page 163 for the notation used in contingency table analysis There are two cases in which this type of data arises:

By cid
(170 views)

Nonparametric Statistics in Criminology

Nonparametric Statistics in Criminology

Nonparametric Statistics in Criminology. An Examination of Crime Trends in New York City, Los Angeles, Chicago, Houston, and Detroit, and Their Relationships to the Size of Their Respective Police Forces. Background Police Information.

By anoki
(135 views)

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