LECTURE 4: Descriptive Statistics
- A very important 1st step in any data analysis
Sources of Information:
* Dytham Chapter 6
Motulsky - Chapter 3
Sokal & Rohlf Chapter 4
Triola Chapter 2
Descriptive
Lab8 Answers (Correlation & Regression)
March 17, 2009
Question 1: The file Lab8Q1.sav contains data from measurements you made of the armspan, height, foot length and gender of individuals in the cla
Lecture 22:
Ethics in Science
Outline:
Ethics & rules concerning research, data,
statistics & graduate studies
Discuss Case-study scenarios
What is Scientific Integrity?
a code of ethics for
teache
Lecture 21: Power Analysis
Power refers to the ability to avoid type-2 errors.
Sources of Information: Sokal & Rohlf p. 159-169 Motulsky Chapter 22 * Peterman, R.M. 1990. Statistical power analysis ca
BIOL 361 Assignment 3 Marking Scheme (2009) TOTAL out of 85 marks Introduction [8 marks] - Identify the topic of the study (if sewage from the City of Waterloo has detrimental effects on ecological he
Reminder
Midterm exam is tonight
Tuesday Feb. 15th at ~8:15 pm
In DC 1350
i.e., right after the first hour of lecture in
our regular room (B1-370)
Bring your student ID to the exam!
LECTURE 14: ANALYS
BIOL 361 ASSIGNMENT 4 (Categorical Data Analysis)
March 10, 2009
This assignment is due before class on Tuesday March 24. It is worth 15% of your final mark. Preamble: You are an entomologist interest
LECTURE 13: ANALYSIS OF VARIANCE II
Outline
post-hoc tests
testing assumptions in ANOVA
non-parametric ANOVA (Kruskal-Wallis test)
Sources of Information: (same as Lecture 12)
Dytham: Chapter 7, p.
Lecture 21: Power Analysis
Power refers to the ability to avoid type-2 errors.
Sources of Information:
Sokal & Rohlf p. 159-169
Motulsky Chapter 22
* Peterman, R.M. 1990. Statistical power analysis ca
Interested in taking BIOL 499 beginning F16?
Information meeting: Wed Feb 3rd at 5:30 pm, in B2 350
course requirements (see uWaterloo calendar, Dept Biology web page
for more info):
BIOL 499 (Senior
Are You Interested in Taking a Biology Field
Course For Credit? (Biology 490A or 490B)
Waterloo Students may choose from ~32
biology field courses offered in 2016
For additional information, please vi
Lecture 23:
Course Overview
Outline:
Review available tests
Big-picture advice
Info about Final Exam
Sources of Information:
Motulsky: Chapters 37 & 38 (Overview)
Overview of Available Statistical
BIOL 361 LAB 1 (Descriptive Statistics) January 18, 2011
1. The instructor will divide students into several groups of ~10-15 people/group and provide each group
with a tape measure. In this lab, you
BIOL361 - LAB 2 (C.I.s and Ho Testing) January 18, 2011
PART A: Start the lab session by collecting data on the reaction times of writing hands vs. non-writing hands
of all members of the BIOL 361 cla
LECTURE 12: ANALYSIS OF VARIANCE I
H1: 1 2
2-samples:
Ho: 1 = 2
ANOVA:
Ho: 1 = 2 = 3 = = k
H1: mean of at least 1 population is different
ANOVA sample variances are used to measure
differences between
Lecture 1
They allow you to extrapolate your data to a more general case - Statisticians say that you
extrapolate from a sample (of data) to a (statistical) population.
The distinction between sample
Lecture 6:
Confidence Intervals
Now, we are ready to learn methods for answering 2
fundamental questions that all biologists must
repeatedly answer in their research:
1. How reliable are the results (
Lecture 7: Hypothesis Testing
Outline:
learn some background theory to hypothesis testing
how to formulate null and alternate hypotheses
how to perform a 1-sample test and interpret & report
the re
LECTURE 3:
INTRODUCTION TO
HYPOTHESIS TESTING
&
EXPERIMENTAL DESIGN
HYPOTHESIS TESTING
All scientific studies involve the collection of data to test
hypotheses.
A hypothesis is a statement of causati
WELCOME to BIOL 361
Biostatistics &
Experimental Design
INTRODUCTION TO BIOLOGY 361
Biology 361 is a practical course in statistics & experimental
design for students of the biological sciences.
Cours
Name: _
Student ID: _
BIOL 361MIDTERM EXAM
Feb. 24, 2015
Page 1 of 7
INSTRUCTIONS: This exam has 4 questions over 7 pages worth a total of 70 marks. The exam is worth
10% of your final course grade. C
Lecture 20: Multiple Linear Regression
Simple linear regression: determines the best least squares
equation to predict 1 Y-variable from a single predictor variable, X.
Multiple linear regression: fin
LECTURE 2:
DATA IN BIOLOGY
Outline:
Define terms for understanding biological data
Overview of important principles for collecting data for
biological studies.
Sources of Information
Dytham:
Chapter